6G: The Intelligent Network of Everything – A

Comprehensive Vision, Survey, and Tutorial

Harri Pennanen, Member, IEEE, Tuomo Hänninen, Oskari Tervo, Antti Tölli, Senior Member, IEEE, Matti
Latva-aho, Fellow, IEEE

Abstract—The global 6G vision has taken its shape after an up-to-date review is given on the worldwide research
years of international research and development efforts. This activities toward 6G, followed by a contemporary survey of the
work culminated in ITU-R’s Recommendation on ”IMT-2030 main 6G vision and survey articles. Finally, the contributions
Framework”. While the definition phase of technological re-
of the article are presented.
arXiv:2407.09398v2 [cs.IT] 21 Jul 2024

quirements is currently ongoing, 3GPP’s standardization process

on 6G networks is expected to start in 2025 and worldwide
commercialization around 2030. It is timely to present an up-
to-date overview of the 6G research field. This article serves as A. A Brief History of Mobile Communications
a comprehensive guide to 6G by providing an overall vision, a The generations 1G to 6G are briefly reviewed, with a focus
contemporary survey of the main literature, and an informative
on the disruptive nature of each generation. This evolution is
tutorial-type presentation style. In our vision, 6G will be based
on three fundamental elements: wireless, artificial intelligence summarized in Figure 1.
(AI), and the Internet of Everything (IoE). Consequently, 6G 1) 1G: Mobile Meets Telephony: Mobile communications
can ultimately become the Intelligent Network of Everything while began over four decades ago in the 1980s, when 1G networks
serving as an enabling platform for the next major disruption in were introduced. 1G was based on analog communication with
mobile communication, called mobile intelligence. The potential
of mobile intelligence is that anything can be made connected,
voice-only services. There were numerous regional mobile
intelligent, and aware of its environment. This will revolutionize systems under the umbrella of 1G, such as the Advanced
the way how devices, systems, and applications are designed; Mobile Phone System (AMPS) in North America, the Nordic
how they operate and interact with humans and each other; Mobile Telephone (NMT) in Nordic countries, and the To-
and how they can be used for the benefit of people, society, and tal Access Communication System (TACS) in the United
the world in general. After high-level visioning, the main details
of 6G are discussed, including fundamental elements, disruptive
Kingdom (UK). 1G started the era of mobile telephony. The
applications, key use cases, main performance requirements, disruptive feature of mobile telephony was that one could
potential technologies, and defining features. A special focus is make a phone call anywhere to anybody (in the coverage area).
given to a comprehensive set of potential 6G technologies, each In practice, however, the number of users was rather limited
of which is introduced in a tutorial manner, with a discussion on because mobile phones were expensive, large in size (they
the vision, introduction, past, present, opportunities, challenges,
literature, and future research directions. Finally, we speculate
could not fit in a pocket), and heavy to carry. Consequently,
on what comes after 6G and sketch the first high-level vision the disruptive nature of 1G and mobile telephony remained
of 7G. All in all, the objective of this article is to provide a modest during the 1980s.
thorough guide to 6G in order to serve as a source of knowledge 2) 2G: Mobile Telephony: The real disruption occurred
and inspiration for further research and development work in in the 1990s when 2G networks were introduced. 2G was
academia, industry, and standardization bodies.
based on digital communication, allowing calling, texting,
Index Terms—5G, 6G, 7G, Artificial Intelligence, Beyond 6G, and limited data services. Due to digital signal processing
Deep Intelligence, Deep Learning, Edge Intelligence, Federated technology, transceivers became more complex, powerful, and
Learning, Hyperverse, IMT-2030, Internet of Everything, Ma-
chine Learning, Metaverse, Mobile Intelligence, Mobile Net- energy efficient, making phones fit in pockets and having great
works, Smart Society, Transfer Learning voice quality. The dominant 2G system was the Global System
for Mobile Communications (GSM), which was first used in
Europe and later around the world. Other 2G systems were
I. I NTRODUCTION
Digital AMPS and cdmaOne in North America and Personal
This section takes a glance at the past, present, and future Digital Cellular (PDC) in Japan. In the 2G era, the game
of mobile communications by introducing the evolution from changer was the evolution from analog to digital technology,
1G to 6G. After that, a special attention is given on 5G by making mobile phones affordable, small, and easy to carry.
providing a brief overview on its fundamentals, background, People were able to call and text anyone anywhere due to high
and standardization. The focus is then shifted to 6G. A generic penetration rate and broad coverage. 2G freed the potential
development process and its timeline is discussed first. Then, of mobile telephony and became a huge success, changing
This research was supported by the Research Council of Finland (former everyday life and interactions between people.
Academy of Finland) 6G Flagship Programme (Grant Number: 346208). 3) 3G: Mobile Meets Internet: In the 2000s, 3G networks
H. Pennanen, T. Hänninen, O. Tervo, A. Tölli, and M. Latva-aho are with were introduced, with data-centric communication as a key
Centre for Wireless Communications, University of Oulu, P.O. Box 4500,
FIN-90014 University of Oulu, Finland (e-mail: harri.pennanen@oulu.fi, feature. Calling and texting were also included. The radio
tuomo.hanninen@oulu.fi, antti.tolli@oulu.fi, matti.latva-aho@oulu.fi). access technology used in 3G was code-division multiple

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version
may no longer be accessible.
 2

1G 2G 3G 4G 5G 6G

• 1980s • 1990s • 2000s • 2010s • 2020s • 2030s

• NMT/AMPS • GSM • UMTS • LTE • NR •?
• MOBILE • MOBILE • MOBILE • MOBILE • MOBILE • MOBILE
TELEPHONY TELEPHONY INTERNET INTERNET INTELLIGENCE INTELLIGENCE

Fig. 1. Evolution of mobile networks from 1G to 6G.

access (CDMA), allowing for more efficient spectrum use. 5) 5G: Mobile Meets Intelligence: In 2019, the first 5G
Turbo coding enabled 3G communication links to approach networks, based on 3GPP’s 5G System technology (Release 15
the Shannon capacity limit in practice. High data rates were [1]), were rolled out. 5G was designed for software-native net-
possible due to the significantly increased system bandwidth. working, service-oriented architecture, enhanced mobile inter-
CDMA2000 was used in North America, while the dominant net, mission-critical communications, and massive Internet of
3G system elsewhere in the world was the Universal Mobile Things (IoT) connectivity. In general, 5G is a flexible network
Telecommunications System (UMTS). 3G provided a platform with greatly expanded capabilities, providing a robust platform
for the next major disruption, called mobile internet (i.e., for novel wireless services and applications, particularly for
mobile broadband). However, mobile internet did not boom vertical industries. The 5G System introduced a new core
in the early phase of 3G since mobile phones did not have network (i.e., 5G Core) and a new radio interface (i.e., 5G
touch screens, and their operating systems were not properly New Radio (NR)) as part of the access network. The 5G Core
optimized for the mobile internet usage. In addition, the ma- supports service-based architecture (SBA), software-defined
jority of Internet content was not optimized for mobile phone networking (SDN), network function virtualization (NFV), and
usage. In other words, the ecosystem for mobile internet was network slicing. The key technologies of 5G radio access
immature at that time. This led to a clumsy user experience network (RAN) include millimeter wave (mmWave) commu-
of mobile internet. However, all started to change after the nications, massive MIMO, small cells, flexible OFDM-based
introduction of the iPhone in 2007 and the iPhone 3G in 2008. transmission scheme, cellular/industrial IoT, edge computing,
The iPhones had touch screens and their operating systems and private networks. 5G also introduced support for non-
were properly optimized for the mobile internet. Touch screens terrestrial networks (NTNs), integrated access and backhaul
and mobile applications disrupted the whole mobile phone (IAB), NR position, unlicensed NR, unmanned aerial systems
industry. The golden age of the mobile internet, touch screen (UAS), and NR V2X. Currently, there are four 5G Releases
devices, and mobile applications started at the verge of the 4G published in 3GPP, i.e., Releases 15 (2018), 16 (2020), 17
era in the late 2000s. (2022), and 18 (2023). The most disruptive feature of the latest
Release 18 (i.e., 5G-Advanced) is the introduction of artificial
4) 4G: Mobile Internet: The first commercial 4G networks intelligence/machine learning (AI/ML) to mobile networks.
were launched in 2009. 4G was designed for broadband mobile This is the turning point when mobile meets intelligence in
internet with higher data rates. The air interface technology the network design.
was changed from 3G’s CDMA to orthogonal frequency-
division multiplexing (OFDM). OFDM was chosen due to 6) 6G: Mobile Intelligence: Commercial 6G networks are
its robustness, flexibility, and straightforward support for expected to be launched around 2030. Currently, 6G is in the
multiple-input multiple-output (MIMO) and lower-complexity development phase and standardization will start in 2025. Key
receivers. 4G was the first large-scale wireless system to technologies under development include terahertz (THz) com-
exploit full-dimension MIMO channels. 4G was able to adapt munications, ultra-massive MIMO, reconfigurable intelligent
to the prevailing channel and interference conditions. This with surfaces (RISs), ultra-dense networks (UDNs), network/edge
the increased system bandwidth and spectrum re-farming en- intelligence, integrated non-terrestrial and terrestrial networks
abled high-rate communications and flexible use of broadband (INTNs), integrated sensing and communication (ISAC), 6G
mobile internet. The mobile internet boomed in the 4G era and V2X communications, cellular-connected unmanned aerial
became an essential part of everyday life. The 3rd Generation vehicle (UAV) communications, and THz IAB. Ultimately,
Partnership Project (3GPP) developed Long-Term Evolution 6G aims to be ”the Intelligent Network of Everything”,
(LTE) (Release 8) was the dominant 4G system commonly with extreme performance (capacity, rates, latency, reliabil-
used around the world. The evolution of LTE included LTE- ity, connection density, coverage, and mobility), pervasive
Advanced (LTE-A) (Release 10) and LTE-A Pro (Release 13). AI/ML (core, edge, and air interface), ubiquitous Internet
The main technological components of the evolution were of Everything (IoE) (sensors, devices, machines, vehicles,
carrier aggregation, enhanced MIMO, relaying, coordinated drones, robots, etc.), and beyond-communication capabilities
multi-point (CoMP) transmission/reception, dual connectivity, (computation, caching, sensing, positioning, and energy). The
and licensed-assisted access. LTE evolution also introduced 6G ecosystem is expected to provide a fruitful platform for
support for vehicle-to-everything (V2X) communications and the next major disruption, known as mobile intelligence (also
Machine-Type Communications (MTC). known as wireless intelligence and connected intelligence).
 3

Mobile intelligence will revolutionize the design, operation, 18, i.e., 5G-Advanced, was completed by the end of 2023.
and interactions of devices, systems, and applications. In the Currently, Release 19 is in preparation and expected to be
big picture, mobile intelligence will be deeply integrated into finalized by mid-2025. The main features of Releases 15-19
the future society, providing diverse benefits at all its levels. are summarized in Table I.
Releases 15 and 16 completed 3GPP’s IMT-2020 submis-
eMBB sion. ITU-R’s evaluation and selection process culminated in
February 2021, when ITU-R published Recommendation ITU-
R M.2150-0 ”Detailed specifications of the radio interfaces
of IMT-2020” [14]. This document presented three approved
IMT-2020 compliant RITs, i.e., 3GPP 5G set of RITs (5G-
SRIT), 3GPP 5G-RIT, and 5Gi. The first technology refers to
5G Non-Stand Alone, whereas the second represents 5G Stand
5G Alone. 5G Non-Stand Alone interacts closely with 4G LTE,
especially in terms of initial access and spectrum sharing. This
Non-Stand Alone version enabled a faster and smoother launch
of 5G. 5G Stand Alone works independently without the aid
of 4G LTE. The first commercial 5G networks were launched
during the first half of 2019. Most of the first 5G deployments
mMTC URLLC were based on the Non-Stand Alone version operating at 3.5
Fig. 2. Key use cases of 5G. gigahertz (GHz) carrier frequency.
3) Release 15: 5G Phase 1: Release 15 (7/2017-12/2018)
introduced the first phase of 5G. The corresponding 5G System
B. 5G in a Nutshell consists of three main parts: the core network (5G Core), RAN
This section presents a brief overview of 5G. The main (5G RAN, including NR), and user equipment (UE) [1]. The
aspects are reviewed, including the introduction, background, 5G Core was designed to support flexible functionalities via
and standardization. More comprehensive overviews of 5G its cloud-native service-oriented architecture, enabling novel
have been given in the following publications: 5G NR [2], services and business opportunities. The main features of 5G
[3], 5G Evolution [4]–[6], and 5G-Advanced [7]–[9]. Core are SDN, SBA, NFV, and network slicing [5], [15].
1) Introduction: 5G refers to mobile communication net- The 5G RAN was designed to support high-speed mobile
works that meet the performance and service requirements internet, mission-critical communication, and massive IoT
of International Mobile Telecommunications for 2020 and connectivity. The main features of 5G RAN include mmWave
beyond (IMT-2020) systems set by the International Telecom- communications (24.25–52.6 GHz), massive MIMO, OFDM
munication Union Radiocommunication Sector (ITU-R). The with flexible numerology, ultra-lean transmission, dynamic
main performance requirements of 5G include 20 Gbit/s peak time-division duplex (TDD), forward compatibility, and edge
rate, 100 Mbit/s user-experienced rate, 1 ms latency, 1-10-5 computing [16]. In addition to a new set of features, each
reliability, and 1 million/km2 connection density [10]. 5G release specifies enhancements to a set of existing features. In
supports a variety of use cases, from enhanced Mobile Broad- Release 15, the main enhanced features are MTC, IoT, mission
band (eMBB) to Ultra-Reliable Low-Latency Communications critical, and V2X communications. The Release 15 work items
(URLLC) and massive MTC (mMTC) [11], as illustrated in are reviewed in [1].
Figure 2. Consequently, 5G enables diverse services across a 4) Release 16: 5G Phase 2: Release 16 (1/2019-6/2020)
wide range of vertical domains. The 5G System, standardized introduced the second phase of 5G. The main new features are
by 3GPP, is the dominant 5G technology used worldwide. private networks, industrial/cellular IoT, NR unlicensed, NR
2) Background: The research on 5G began in the early positioning, self-organized network (SON) properties, local
2010s in academia and industry. At that time, ITU-R also area network services, wireless-wireline convergence, high-
started its development work toward IMT-2020. The role speed train scenario, and maritime communication services
of ITU-R was to build an overall vision, define perfor- [13]. The main enhanced features include URLLC, V2X,
mance/service requirements, evaluate candidate radio interface mission-critical services, location services, network slicing,
technologies (RITs), and select IMT-2020 compliant (5G) and SBA [13]. Further details on the Release 16 work items
systems by the end of 2020. In 2014, the most cited 5G can be found in [13].
paper, ”What Will 5G Be?”, was published [12]. In this early 5) Release 17: 5G Evolution: Release 17 (7/2020-3/2022)
phase, this study identified the key elements of 5G, providing continued the work on 5G evolution. The main new features
important guidelines for further research and development include operation at higher mmWave frequencies (52.7–71
work. The first standardization efforts by 3GPP were taken in GHz), RAN slicing, IAB, UAS, and NTNs [5]. The existing
2016. At the end of 2018, 3GPP completed the first standard features that are further enhanced include, among others,
for the 5G System, i.e., Release 15 [1]. Release 15 was massive MIMO, cellular/industrial IoT, URLLC, V2X, mul-
the first phase of 5G. The second phase, Release 16 [13], ticast/broadcast, positioning, network slicing, edge comput-
was finalized in mid-2020. Release 17, a continuation of 5G ing, network automation, non-public networks, and wireless-
evolution, was frozen in the first quarter of 2022. Release wireline convergence [5]. The work items of Release 17 are
 4

TABLE I
S UMMARY OF 3GPP 5G R ELEASES 15-19

Release 15 Release 16 Release 17 Release 18 Release 19

Timeline 07/2017–12/2018 01/2019–06/2020 07/2020–03/2022 04/2022–12/2023 01/2024–06/2025

Evolution type 5G-Advanced

5G Phase 1 5G Phase 2 5G Evolution 5G-Advanced
Evolution

SDN - SBA - NFV -

network slicing - edge Private networks - IoT NTNs - RAN slicing AI/ML - mobile IAB AI/ML (air interface)
Main features - unlicensed spectrum - mmWave (higher) - - dual multi-SIM - - network energy
computing - mmWave
- mMIMO - positioning - SON NR light - IAB - UAS mobile small data savings - ambient IoT

discussed in [17]. network vendors carry out the deployment and commercializa-
6) Release 18: 5G-Advanced: Release 18 (4/2022-12/2023) tion phases. The role of ITU-R is to build a vision of IMT for
introduced the first standard of 5G-Advanced, representing a 2030 and beyond (i.e., IMT-2030), define performance/service
significant evolution step for 5G [7]. A major milestone is the requirements and evaluation criteria, evaluate candidate RITs,
introduction of AI/ML technology, which provides intelligent and finally select IMT-2030 compliant (i.e., 6G) systems
network features for 5G. Other novel features include mobile around 2030. In November 2022, ITU-R published its first
IAB, support for UAVs, mobile-terminated small data, and technological report on IMT-2030, i.e., Report ITU-R M.2516-
a dual multi-subscriber identity module (SIM) [7]. Enhance- 0, titled ”Future technology trends of terrestrial IMT systems
ments are provided for coverage, mobility, MIMO, multicast- toward 2030 and beyond”. The report focused on emerging
ing/broadcasting, spectrum sharing, multi-carrier, sidelink, and services and applications, technology trends and enablers, and
NTNs [7]. An overview of the Release 18 work items can be enhanced radio interface and network technologies. In Novem-
found in [18]. ber 2023, ITU-R’s visioning phase culminated in the publica-
7) Release 19: 5G-Advanced Evolution: Release 19 tion of Recommendation ITU-R M.2160-0, titled ”Framework
(1/2024-6/2025) will be the first evolution of 5G-Advanced. and overall objectives of the future development of IMT for
3GPP agreed on its content in December 2023, and the work 2030 and beyond”. This document discussed the trends, usage
began in the beginning of 2024. Release 19 continues the 5G scenarios, capabilities, and ongoing development of IMT-2030.
evolution toward 6G, and can be seen largely as preparation The next phase is to define the performance/service re-
studies toward 6G, while still continuing the development quirements and evaluation criteria/methodology of IMT-2030
based on commercial deployment needs. One focus will be between 2024 and 2026. The final phase is to evaluate and
on developing further use cases, such as the NTN evolution select compliant RITs and complete IMT-2030 specifications
for NR and IoT, femto cells, wireless access backhaul, low- in the time frame of 2027-2030. ITU-R also defines the fre-
power wake-up signals, ambient IoT, and multi-hop relays. quency bands for IMT-2030 through World Radio Conferences
Another focus area is to further improve the eMBB experience, (WRCs), organized every three to four years. While WRC
such as extended reality (XR), mobility, MIMO operation, and 2023 paved the way toward the candidate spectrum bands for
duplex. Some interesting starting studies toward 6G technolo- IMT-2030 (i.e., 4.4–4.8 GHz, 7.1–8.4 GHz, and 14.8–15.3
gies include channel modeling for 7-24GHz, which is one of GHz), final allocations will be made at the future WRCs,
the important new 6G bands in the 6G roadmap and channel especially at the WRC 2027. 3GPP also plays a key role
modeling for sensing use cases. In addition, improvements of in the standardization of 6G. When 5G evolution approaches
the other key performance indicators will continue in terms of its limits, the standardization efforts start to shift toward 6G.
network energy saving enhancements, AI/ML for air interface, The 6G standardization process is estimated to begin in 2025,
mobility, and next-generation RAN (NG-RAN), as well as the Release 20 (7/2025–12/2026) being the first specification to
enhancements on SON and minimization of drive tests (MDT). study 6G and Release 21 (1/2027–6/2028) the first official
6G standard. The worldwide commercialization phase of 6G
C. 6G Development Process networks is anticipated to start around 2030. The estimated
The development of 6G follows a process similar to that timeline for the development process of 6G is summarized in
of 5G. In short, the mobile network industry carries out Figure 3.
the process from research and development to testing and
implementation. Academia also participates in the research D. 6G Research Activities
and development work, often cooperating with the industry. The research on 6G was initiated in 2018. This section high-
Standardization and regulations are handled by the interna- lights the primary research steps taken worldwide since then.
tional and national standardization bodies and regulatory or- Many different types of activities are introduced, including ini-
ganizations. Mobile network operators, service providers, and tiatives, projects, collaborations, funding, experiments, events,
 5

2018-2019 2020-2021 2022-2023 2024-2025 2026-2027 2028-2030

ACADEMIA 6G RESEARCH - DEVELOPMENT - EXPERIMENTS

INDUSTRY 6G RESEARCH - DEVELOPMENT - IMPLEMENTATION - DEPLOYMENT

ITU-R IMT-2020 IMT-2030 VISION - REQUIREMENTS - EVALUATION - SELECTION

3GPP 5G RELEASES 15-20 6G REL 21-22

Fig. 3. Estimated timeline for 6G development process.

and publications. For clarity, the activities are introduced in reported joint cooperation in 6G development.
a chronological order. Further details on the following 6G In August, Keysight Technologies joined the Finnish 6G
activities can be found in [19], where a comprehensive list Flagship Program, strengthening its testing and experimental
of 6G research progress is provided. The main benchmarks of capabilities. Huawei announced that it had already begun
6G research are summarized in Figure 4. to study 6G at its Canadian research center in Ottawa. In
1) Activities in 2018: The first research activities on 6G November, China’s Ministry of Science and Technology stated
were conducted in 2018 in terms of projects, events, and that it is going to establish two national 6G groups. One will
publications. The first large-scale 6G project, with a total promote 6G research and development work, consisting of
volume of 249 million euros, was launched in April in governmental departments, while the other will be formed
Finland by a consortium of the Finnish leading academic by academic and industrial organizations, focusing on the
and industrial organizations. The 6G Flagship Program is an technical part of 6G. Rohde & Schwarz reported collabora-
eight-year research initiative that aims to develop and test tion with a group of German research institutions to study
6G enabling technologies. In September, the first annual 6G communications at THz frequencies. The Indian company
special issue, entitled ”6G: What is Next?”, was published by Tech Mahindra and Finnish government-led Business Finland
the Institute of Electrical and Electronics Engineers (IEEE) agency signed a Memorandum of Understanding (MoU) for
Vehicular Technology Magazine. In this special issue, the first the joint exploration of 5G/6G, with an agreement to establish
6G vision paper was published under the title ”6G Vision and an innovation lab in Finland.
Requirements: Is There Any Need for Beyond 5G?” [20]. The A handful of 6G events were arranged around the world
paper contemplated the need for 6G, with a positive conclusion in 2019. The first 6G conference was held in March, i.e.,
by reviewing each generation’s strengths and deficiencies. In the annual 6G Wireless Summit organized by the Finnish 6G
November, another 6G vision paper was published by the Flagship Program. As an outcome of the Summit, the first 6G
Finnish 6G Flagship Program, sketching its tentative vision white paper, ”Key Drivers and Research Challenges for 6G
for 6G and emphasizing the importance of interdisciplinary Ubiquitous Wireless Intelligence” [22], was published. A few
research in wireless communications, computer engineering, 6G panels/workshops were organized at major conferences.
electronics, and material science [21]. In December, Carleton Different research groups around the world began to propose
University organized the first workshop series on 6G, covering their own visions of what 6G might be in the 2030s. These
physical (PHY) layer technologies, network architectures, and 6G vision papers discussed many aspects of 6G, such as key
AI/ML methods. trends, main requirements, system architectures, potential tech-
2) Activities in 2019: The 6G research activities began to nologies, possible applications, opportunities, and challenges.
spread around the world in 2019. In January, South Korean In September, IEEE Vehicular Technology Magazine released
LG Electronics opened a center for 6G research at the Ko- its second special issue on 6G.
rean Advanced Institute of Science and Technology (KAIST). 3) Activities in 2020: 6G research continued to spread
Samsung also established a new 6G research unit called the around the world in 2020. In January, Japan’s government
Advanced Communications Research Center. In March, the organized a 6G panel with academic and industrial repre-
Federal Communications Commission announced that it will sentatives to plan a comprehensive strategy for Japan’s 6G
open the spectrum from 95 GHz to 3 THz for experimental research. In February, the ITU-R Working Party 5D (WP 5D),
usage and 6G research in the United States (US). In April, in charge of IMT systems, decided to begin the visioning work
the UK launched a five-year project to study optical wireless toward IMT-2030. In May, the Chinese technology vendor
technologies for 6G and beyond. China Mobile and Tsinghua ZTE and mobile network operator China Unicom agreed to
University reported their cooperation to study 6G technologies collaborate on 6G research, including the joint development,
in May. In June, SK Telecom partnered with Ericsson and verification, and trials of 6G enabling technologies. Later in
Nokia to conduct 6G research. South Korea and Finland May, the Alliance for Telecommunications Industry Solutions
 6

trends and aspects of 6G. In November, China launched the

first experimental ”6G” satellite to test THz communication
in space. The University of Surrey opened a 6G Innovation
Finnish 6G First 6G Center and published a white paper, introducing its 6G vision
2018 [34].
Flagship Vision Article
In 2020, a few 6G conferences were organized virtually.
The 6G theme spread to all major telecommunication confer-
6G Wireless First 6G White ences in the forms of keynote speeches, plenary talks, panels,
2019 workshops, and forums. Many major technology companies
Summit Paper
published white papers to reveal their initial 6G visions. IEEE
Vehicular Technology Magazine and IEEE Access released
ITU IMT-2030 Next G special issues on the 6G-specific topics. Numerous 6G vision
2020
Phase 1 Alliance and survey papers were also published in 2020.
4) Activities in 2021: At the beginning of 2021, many
European Union (EU)-funded 6G projects were launched,
including Hexa-X, RISE-6G, 6G BRAINS, and DEDICAT 6G.
SNS JU 2021 Hexa-X
The Hexa-X initiative is the EU’s 6G flagship project that aims
to develop 6G technology enablers to connect human, physical,
and digital worlds. RISE-6G studies smart and sustainable
ITU IMT-2030 wireless environments using RISs, focusing on the propagation
2022
FTT Report modeling, investigation of fundamental limits, algorithmic
designs, prototyping, and trialing. 6G BRAINS targets to
develop AI-driven resource allocation solutions by exploiting
ITU IMT-2030 THz and optical frequencies to enable massive connectivity in
2023 Hexa-X-II
Framework industrial environments. The objective of the DEDICAT 6G
project is to design smart 6G connectivity mechanisms that
support the dynamic distribution of intelligence and enable
ITU IMT-2030 3GPP secure human-centric applications.
2024
Phase 2 5G Rel-19 Also in January, a team of five German Fraunhofer research
institutes established the 6G Sentinel project to develop key
technologies for 6G, with the main focus on THz communica-
tions and flexible network solutions. The Japanese government
Fig. 4. Main benchmarks of 6G research.
reported that it is planning to invest 482 million dollars for its
6G research and development work, i.e., 60 % of the funding
for public-private sectors to develop 6G technologies and 40 %
(ATIS) released a call to action to advance the US toward to set up a research facility to test the developed technologies.
a global leadership in 6G and beyond. The aim was to In March, ITU-R WP 5D established the 6G Vision Group
build close collaboration between the government, academia, and started the development work toward ”IMT-2030 Frame-
and industry to provide a comprehensive path from research work”. The one6G association was established to promote
and development to standardization and commercialization. In 6G development by bringing together industrial and academic
June, Finland’s 6G Flagship Program published eleven 6G players around the world. In April, the German government
white papers, providing a comprehensive study on different announced that it will fund Germany’s 6G research into key
aspects of 6G [23]–[33]. Later in autumn, the 6G Flagship technologies and innovative products with 700 million euros
Program released an online webinar series, in which each by 2025. LG reported a recent collaboration with Keysight
white paper was introduced and thoroughly discussed. Technologies and KAIST to develop 6G enabling technologies,
In August, the South Korean government announced that it especially for THz communications. A few months later, LG
is planning to allocate 169 million dollars for the development announced a successful demonstration of wireless THz trans-
of 6G technologies during the period from 2021 to 2026, and mission over a 100 meter long outdoor link. Furthermore, LG
then start a pilot project for 6G services, with five focus areas: demonstrated 6G RF front-end technology, jointly developed
immersive content, digital healthcare, autonomous vehicles, with Fraunhofer Research Institute, for sub-THz frequencies
smart factories, and smart cities. In October, the Next G using Keysight’s testbed equipment at the Korean Science and
Alliance was established to promote 6G in North America. Technology Exhibition 2021.
The founding members included numerous major players in In June, Vodafone Germany announced that it will open
the mobile industry. The target of the Next G Alliance is a new 5G/6G research and development center in Dresden.
to ensure that North America is a global leader in the 6G Finland’s 6G Flagship Program and Japan’s Beyond 5G Pro-
development. ITU-R WP 5D released a Liaison statement, motion Consortium agreed on a collaboration for joint research
inviting external organizations to contribute to the IMT-2030 and development on 6G technologies, aiming to contribute
visioning work by providing views on different technological to the regulation and standardization of 6G. Samsung and
 7

the University of California, Santa Barbara demonstrated China Mobile, reported that it had obtained a data rate of
an end-to-end sub-THz link with fully digital beamforming 206.25 Gbit/s for a wireless THz transmission in a laboratory
at a 140 GHz carrier frequency at the IEEE International environment. The Next G Alliance published a white paper
Conference on Communications (ICC) 2021. In July, the titled ”Green G: The Path toward Sustainable 6G”. The
University of Texas partnered with a group of American and University of Oulu announced a partnership with Jio Estonia
Korean technology companies to establish a joint 6G research to study 6G technologies, particularly for non-terrestrial com-
and development center, with a special focus on wireless munications, holographic radio, and three-dimensional (3D)
ML, advanced sensing, innovative networking, new spectrum connected intelligence.
technologies, and satellite communications. Ericsson and the In February, Keysight Technologies announced a partnership
Massachusetts Institute of Technology reported a collaboration with Samsung to develop, test, and verify 6G technologies.
on two 6G-related project, focusing on neuromorphic com- The Next-Generation Mobile Networks (NGMN) Alliance
puting and ”zero-energy” devices. The Chinese technology published a white paper on 6G use cases, categorizing them
company OPPO announced the establishment of a research into four main classes, i.e., enhanced human communications,
team to study 6G requirements, technologies, and system enhanced machine communications, enabling services, and
architectures. OPPO also released a 6G white paper on AI- network evolution. At the Mobile World Congress (MWC)
based intelligent networking. Mobile network operators LG 2022, LTE showcased its cutting-edge RIS technology, in-
UPlus and KDDI reported that they have signed an MoU cluding four different prototypes, i.e., liquid crystal RIS, PIN
to study novel business opportunities for 5G networks and diode RIS, transparent planar RIS, and transparent flexible
develop 6G enabling technologies. RIS. At the same venue, the US technology company VMware
According to Nikkei’s report in September, the distribution reported its collaboration with German research institutes to
of 6G patents among major countries is as follows: China accelerate 6G research, focusing on the fusion of cloud,
40.3 %, US 35.2 %. Japan 9.9 %, Europe 8.9 %, and South networking, and AI technologies.
Korea 4.2 %. In late 2021, Huawei reported that it had demon- In April, Kyocera, a Japanese technology firm, announced
strated a 240 Gbit/s data rate over a 500 meter outdoor link that it has developed a transmissive metasurface that can be
operating at a 220 GHz carrier frequency with a bandwidth used to extend coverage in 5G and 6G networks by redirecting
of 13.5 GHz. In November, the University of Oulu and the radio signals to avoid obstacles. In May, an MoU was signed
University of Tokyo agreed on a bilateral partnership in 6G between the European 6G Smart Networks and Services
research. Ericsson and King Abdullah University of Science Industry Association (6G-IA) and the Japanese Beyond 5G
and Technology announced a cooperation on 6G research with Promotion Consortium to accelerate the development of 6G
the main emphasis on ML-assisted massive MIMO, RISs, networks and deepen the cooperation between Europe and
and THz communications. The EU founded the European Japan. Samsung released a new white paper, ”6G Spectrum:
Smart Networks and Services Joint Undertaking (SNS JU) Expanding the Frontier”, discussing spectrum policies and
targeting to guarantee Europe’s industrial leadership in 5G/6G potential frequency bands for 6G. The Finnish leading aca-
and advancing green/digital transition. The funding budget for demic and industrial organizations established a national 6G
SNS JU is 900 million euros for the period 2021-2027. In coalition, called 6G Finland, aiming to strengthen national 6G
December, SNS JU accepted its first Work Program 2021- cooperation, form new international partnerships, and promote
2022 with a budget of 240 million euros for the research and Finland’s 6G expertise on a global scale. LG demonstrated its
innovation work on 5G evolution and 6G. The Next G Alliance 6G relevant full-duplex and power amplifier technologies at
and South Korea’s 5G Forum signed an MoU to accelerate the the IEEE ICC 2022. The Next G Alliance and the Japanese
development of 6G networks. Beyond 5G Promotion Consortium agreed on 6G cooperation
Numerous, mostly virtual or hybrid, 6G events were ar- by signing an MoU in May.
ranged in 2021, including conferences, workshops, panels, In June, the Next G Alliance published a white paper titled
forums, plenary talks, and keynote speeches. In terms of ”6G Applications and Use Cases”, focusing on four categories,
publications, many IEEE journals and magazines released i.e., networked robotics, XR, distributed communication and
the 6G-specific special issues. Furthermore, many technology sensing, and personalized user experiences. Nokia, NTT, and
companies, academic organizations, and research coalitions NTT Docomo formed a 6G partnership to demonstrate an
published 6G white papers. In addition, several 6G vision and AI/ML-enhanced air interface and sub-THz communication
survey papers were published. A handful of the first 6G books at 140 GHz spectrum. The Singaporean Nanyang Techno-
were also released. logical University announced the use of Keysight’s test and
5) Activities in 2022: Many different types of activities measurement solutions to verify its on-chip THz electronic-
occurred in January. The project TiC6G was launched by photonic 6G device technologies. The Japanese companies
the University of Glasgow, with a group of academic and NTT Docomo, Fujitsu, and NEC reported to perform joint
industrial partners, aiming to test prototype devices at THz 6G indoor and outdoor trials. 6G-IA and the Chinese IMT-
frequencies using the university’s new cutting-edge labora- 2030 Promotion Group signed an MoU for 6G cooperation.
tory equipment. The Japanese operator Nippon Telegraph The Open RAN (O-RAN) Alliance reported a launch of its
and Telephone (NTT) reported that it will build a 6G pilot Next Generation Research Group, focusing on the utilization
network for the Osaka World Expo 2025. The Chinese Purple of O-RAN technologies in 6G.
Mountain Laboratories, together with Fudan University and In July, LG Uplus and Nokia signed an MoU for collabora-
 8

tion in 5G/6G standardization. Nokia announced its leadership Trends” [35]. It was reported that India’s Department of
in a German 6G light house project 6G-ANNA, aiming to Telecommunications suggests opening up the frequency range
promote 6G development and standardization in Germany. The from 95 GHz to 3 THz for experimenting and testing of 6G
Next G Alliance published a white paper on the technologies technologies and products. Nokia announced its leadership
required to meet the demands of its 6G vision. The UK in the German government-supported KOMSENS-6G project,
government reported to grant 25 million pounds funding for which focuses on the integration of sensing and communica-
the research and development work on 6G technologies. In tion. The Japanese Beyond 5G Promotion Group and North-
August, the Next G Alliance and European 6G-IA signed eastern University agreed on a 6G collaboration by signing
an MoU for the agreement of 6G research collaboration, an MoU to foster the development of 6G networks. NTT
including joint workshops, webinars, and trials. While already Docomo and SK Telecom announced their partnership in the
supporting 6G research at the University of Texas at Austin, fields of smart-life and metaverse, searching for opportunities
the Northeastern University, the University of Surrey, and to jointly produce immersive XR content. Ericsson reported
Viavi Solutions announced a new funding program to advance its ten-year 6G research initiative in the UK, focusing on the
worldwide 6G development in academia and industry. The areas of AI, cognitive networks, and network security. Nokia
Next G Alliance reported the establishment of a 6G research announced the launch of a new 5G/6G R&D center in Portugal.
council, aiming to promote cooperation between academia and The UK government reported a 110 million pound grant for
industry and align North America’s 6G strategy with the US 5G/6G research and development. 28 million is dedicated to
and Canadian governments. the collaboration of academia (Universities of York, Bristol,
In September, LG reported its final THz communication test and Surrey) and industry (Nokia, Ericsson, and Samsung),
at the Fraunhofer Heinrich-Hertz Institute in Berlin, with a while 80 million is invested in a new 5G/6G R&D laboratory.
successful information transfer over a 320 meter outdoor link All types of physical, hybrid, and virtual 6G events were held
at a frequency range between 155 and 175 GHz. The Finnish in 2022. Numerous IEEE special issues on 6G were released.
University of Oulu and Japanese National Institute of Com- Moreover, many 6G white papers, visions, surveys, and books
munication and Technology (NICT) announced a cooperation were written.
in B5G/6G research. Rohde & Schwarz and China Mobile 6) Activities in 2023: In January, the European Hexa-
reported their partnership in the development of ISAC solu- X-II flagship project (i.e., a continuation of Hexa-X) was
tions for 6G. The Singaporean Infocom Media Development launched. Europe’s 6G-IA and the European Telecommuni-
Authority and the Singapore University of Technology and cations Standards Institute (ETSI) agreed on a close 5G/6G
Design revealed their collaboration to establish a 6G Research cooperation with each other by signing an MoU, with the
and Development (R&D) laboratory in Singapore, being the goal of advancing 6G pre-standardization activities. The ATIS
first in kind in Southeast Asia. Nokia informed its 5G/6G and O-RAN Alliance agreed on a partnership via an MoU
collaboration with Vodafone New Zealand. to foster the development of O-RAN technologies. Rohde
In October, Keysight Technologies and the Indian Institute & Schwarz announced its channel measurement campaign
of Technology, Madras signed an MoU, expanding their co- conducted in urban micro outdoor and indoor scenarios at
operation from 5G to 6G design. Deutsche Telekom reported frequencies of 158 GHz and 300 GHz, contributing to the
its leadership in the German government-funded project 6G- ITU-R report titled ”Technical feasibility of IMT in bands
TakeOff, aiming to develop an architectural framework for above 100 GHz”. Finland’s University of Oulu and South
the integration of terrestrial and non-terrestrial networks in Korea’s Electronics and Telecommunications Research Insti-
6G. The European Commission granted funding for Hexa-X- tute announced the launch of their new collaboration project,
II, the second phase of the EU’s 6G flagship program, with 6GBRIDGE-6GCORE, aiming to develop a service-centric 6G
Nokia continuing in lead. 35 research projects were chosen system architecture.
in the EU’s 250 million euros call to develop advanced 5G In February, Ericsson reported its co-leadership with Swe-
and future 6G technologies, with the goal of strengthening den’s KTH Royal Institute of Technology to coordinate a new
the European expertise in the development of future mobile 6G research project, called DETERMINISTIC6G, which fo-
networks. Ericsson and the University of Texas at Austin cuses on developing technological enablers for time-sensitive
deepen their collaboration into 6G-empowered XR. VMware communications applicable to diverse verticals. The University
announced that it is launching the Next G-AI Research and of Sheffield announced the opening of the new UK Research
Innovation Center in Montreal, Canada, gathering multidis- and Innovation National 6G Radio Systems Facility, with top-
ciplinary expertise to advance the technological development notch 6G R&D capabilities and support from more than 40
of 5G and 6G systems. Samsung Electronics reported the companies and academic organizations. Nokia, NTT Docomo,
founding of a new 6G research group in the UK, which is and NTT reported two major milestones achieved on the
part of the Samsung’s global 6G development strategy. The evolution road toward 6G, including sub-THz communica-
German government-funded project 6G NeXt was kicked-off, tion (25 Gbit/s at 144 GHz) and the integration of AI into
with Deutsche Telekom in lead, and the goal of developing air interface (ML-based waveform), implemented as proof
a flexible infrastructure platform to study and test future XR of concepts at Nokia Bell Labs in Germany. Finland’s 6G
applications. Flagship and Brazil’s research institute Inatel announced their
In November, ITU-R WP 5D completed its work on the partnership in developing advanced 6G solutions for rural and
first report on IMT-2030, i.e., ”IMT-2030 Future Technology remote areas. At the MWC 2023, Nokia demonstrated network
 9

sensing capabilities using its prototype radio equipment. Also at LG Sciencepark in Seoul, sending data over 500 meters at
at the MWC, Bosch reported its collaboration with Nokia on THz frequencies. In October, Nokia opened a 6G laboratory
6G-based IoT solutions for industry 4.0 applications. Taiwan’s at its Global R&D center in Bangalore, India to promote 6G
operator Chunghwa Telecom and Ericsson signed an MoU at development, especially in the network sensing technology.
the MWC, joining forces to advance 5G and 6G standardiza- InterDigital and the University Carlos III of Madrid agreed on
tion. a 6G research partnership, focusing on joint communication
In March, India’s government unveiled a national 6G initia- and sensing. Ericsson established a new 6G research team at
tive, targeting to launch 6G networks in India by 2030. Anritsu its R&D center in Chennai, India.
and Danish Aalborg University announced their collaborative In November, the government of South Korea revealed its
6G project on channel sounding for joint communication and 6G development plan, with a total budget of 325 million
sensing at mmWave and sub-THz frequencies. In April, the dollars. The University of Glasgow launched a 6G research
Spanish operator Telefonica, NEC, Bluespecs, and IMDEA laboratory, named ”Terahertz On-chip Circuit Test Cluster
Research Institute reported the launch of the ENABLE-6G for 6G Communications and Beyond”. The 6G-SANDBOX
project, funded by the EU and Spain’s government. The project initiative and Taiwanese Industrial Technology Research In-
aims to develop mechanisms to tackle the challenges 6G stitute signed an MoU to advance 6G cooperation between
will encounter in terms of performance, energy efficiency, Europe and Taiwan. ITU-R completed its visioning work
network sensing, and privacy/security. Keysight Technologies, by publishing the first Recommendation document on IMT-
the University of Surrey, and the National Physical Laboratory 2030, i.e., ”IMT-2030 Framework” [36]. In December, SNS JU
demonstrated over 100 Gbit/s data rates at a 300 GHz carrier and the Next G Alliance released a document titled ”EU-US
frequency using their new sub-THz 6G testbed. Beyond 5G/6G Roadmap” to characterize their collaboration in
In May, the Next G Alliance released a white paper on the the development of 6G networks for 2025 and beyond. 3GPP
6G roadmap for vertical industries. The French technology completed Release 18 and agreed on the content of Release
company Capgemini announced the opening of a new 6G 19.
research lab in India to enable testing and experimentation of 7) Activities in 2024: In January, ITU-R began the second
novel 6G solutions. Brazil’s government reported the alloca- phase of IMT-2030 development, i.e., defining its requirements
tion of 36 million dollars to three research centers to advance and corresponding evaluation methodologies. 3GPP began the
the development of 5G, 6G, and O-RAN technologies. Rohde preparation of Release 19, continuing the development of 5G-
& Schwarz and the French Institute of Electronics, Microelec- Advanced toward 6G. NTT Docomo introduced their forth-
tronics and Nanotechnology announced their cooperation in coming AI-empowered 5G/6G technologies, such as human-
THz communication research, with successful communication augmented mobile platform to express immersive sensory
over 645 meters using a THz backhaul link operating at a perceptions in the metaverse environments.
frequency of 300 GHz. In February, SK Telecom and Intel reported that they have
In June, the Next G Alliance published a white paper on developed an AI-empowered ”Inline Service Mesh” technol-
6G technologies for the wide-area cloud evolution. InterDigital ogy for the 6G core network to reduce latency and increase ser-
and the University of Surrey announced a 6G research partner- vice efficiency. China Mobile announced the launch of its 6G
ship to study joint communication and sensing and RIS tech- test satellite, claiming it to be the first of its kind in the world.
nologies. India’s Department of Telecommunications reported Samsung and Princeton University announced their partnership
the establishment of the Brahat 6G Alliance, consisting of 75 in innovative 6G research through the Princeton’s NextG
companies, with the goal of strengthening India’s 6G exper- Initiative Corporate Affiliates Program, aiming to develop
tise and facilitating market access of Indian telecommunica- new technological innovations and foster cooperation between
tion products and services. In July, Northeastern University academia, industry, and regulators. Other collaborators in this
launched an Open Testing and Integration center to develop program are Nokia Bell Labs, Ericsson, Vodafone, MediaTek,
and test advanced O-RAN technologies. The GSM Association Intel, and Qualcomm Technologies. SK Telecom and Rohde &
and the European Space Agency joined forces by signing an Schwarz joined a group of industrial players collaborating in
MoU to advance the integration of terrestrial and satellite 6G spectrum trials at sub-THz frequencies. The existing part-
networks in 5G and 6G. NTT and Fujitsu demonstrated a data ners include NTT Docomo, NTT, NEC Corporation, Fujitsu,
rate of 30 Gbit/s over a 0.5 meter link distance at 300 GHz Keysight Technologies, Nokia, and Ericsson. Nokia and the
operating frequency using beamforming. Indian Institute of Science announced their 6G collaboration,
In August, the Next G Alliance published 6G white papers focusing on three 6G research areas: network architecture,
on social/economic opportunities and spectrum considerations. radio technologies, and AI/ML-aided air interface. At the
The Next G Alliance also signed an MoU with the Indian MWC 2024, Ericsson and Turkcell partnered in 6G research to
Brahat 6G Alliance on 6G collaboration. In September, the promote technological advances in Turkie. Also at the MWC,
NGMN Alliance released a 6G report from the perspective of Ericsson and Turk Telecom agreed on 6G cooperation by
network operators, titled ”6G Position Statement: An Operator signing an MoU.
View”. InterDigital and the Indian Institute of Technology, In March, Nvidia announced that its 6G research cloud plat-
Kanpur agreed on a 6G cooperation with a special focus on form, based on a digital twin technology, is available, allowing
extreme MIMO. LG Electronics and LG Uplus reported a simulations and testing in the realistic 6G environments. In
record-breaking 6G spectrum test in an outdoor environment April, Viavi Solutions reported its progress with Northeastern
 10

University in the development of a large-scale digital twin requirements, application scenarios, system architectures, and
of a 6G network. The 6G Non-Terrestrial Networks project, promising technologies. AI-empowered 6G was considered in
funded by SNS JU, published a white paper on its vision of [41], covering the network architecture, AI-enabled technolo-
NTNs in 6G networks, highlighting the importance of non- gies, 6G for AI, and hardware-aware communications. In [42],
terrestrial access and discussing the markets, coverage, and the proposed 6G vision emphasized mobile ultra-broadband,
design of NTNs. The University of Glasgow reported that it super IoT, and AI, with a discussion on THz communications,
has designed a digitally controlled metasurface antenna for symbiotic radio, satellite-aided IoT, deep learning (DL), and
the mmWave frequencies, paving the way toward advanced 6G reinforcement learning.
antenna technologies. TDRA, the telecommunication regulator The peak of 6G visions was in 2020. Numerous papers
of the United Arab Emirates, unveiled its 6G roadmap, which were published. The work [43] contemplated what 6G should
promotes the nation’s leadership in the 6G development. be in the 2030s, discussing potential applications, main chal-
In May, the South Korean mobile operator KT Corporation lenges, key features, enabling communication technologies,
and Nokia announced their partnership in developing O- and beyond technology impact. In [44], the authors envisioned
RAN technologies for 6G networks. The National Telecom- the evolution toward the 6G era, focusing on the potential
munications and Information Administration of the US re- and challenges of AI/ML. The covered topics include the
leased a request for comment on 6G, asking for opinions evolution from mobile edge computing to edge AI, distributed
of experts from academia and industry on the timing of tri- AI, communications for ML, and ML for communications. In
als/commercialization, societal benefits, and disaster resilience the 6G vision of [45], the focus was on overcoming the chal-
of 6G. A Japanese consortium, NTT Docomo, NICT, Pana- lenges related to coverage, capacity, data rates, and mobility.
sonic, and SKY Perfect JSAT Corporation, informed their In [46], the authors explored AI-enabled wireless networks
successful field test in the 38 GHz spectrum band to simulate toward 6G, discussing AI for the PHY, medium access control
the usage of high-altitude platform stations (HAPSs) at an (MAC), and network layers. The paper [47] identified six
altitude of 4 kilometers using a small plane Cessna. The main requirements, fundamental design dimensions, and key
test was claimed to be the world’s first in kind, providing technologies for 6G. The study [48] focused on 6G enabling
practical progress toward the use of NTNs at high altitudes technologies in three categories: disruptive communications,
in 6G. In June, Nokia and the Gati Shakti Vishwavidyalaya innovative network architectures, and integrated intelligence.
university announced that they have formed a partnership to In [49], 6G was studied in terms of key features, open
conduct 5G/6G research on transportation and smart factory challenges, possible solutions, and research activities. In [50],
use cases. Nokia and Nordic mobile operator Telia reported the most cited 6G vision paper discussed a comprehensive
their successful field trial at the upper 6 GHz spectrum, agreed set of topics, including driving applications, key trends, per-
on at the WRC 2023. These results pave the way toward the formance metrics, new service classes, technological enablers,
needed capacity enhancements in the 6G era using the mid- open issues, and future guidelines. The paper [51] focused on
band spectrum. communication trends, service requirements, network features,
applications, enabling technologies, research progress, techno-
logical challenges, and future research directions. In [52], the
E. Literature Review on 6G Visions and Surveys authors introduced a vision for 6G and beyond, discussing THz
This section reviews the main 6G literature in terms of communications, intelligent wireless environments, pervasive
vision and survey articles. AI, network automation, reconfigurable transceiver front-ends,
1) 6G Vision Articles: The first 6G vision articles were backscatter communications, internet of space things, cell-free
written in 2018. In [20], the authors speculated the need massive MIMO, and beyond 6G technologies. The 6G vision
for 6G by discussing the strengths and weaknesses of each in [53] focused on communication, networking, and computing
generation. In [21], the paper introduced the 6G vision of the technologies.
Finnish 6G Flagship Program, focusing on interdisciplinary In [54], a speculative study was presented on 6G, with a dis-
research between wireless communications, computer engi- cussion on tentative vision, usage scenarios, key technologies,
neering, electronics, and material science. In 2019, a handful and main challenges. The article [55] provided an in-depth
of 6G papers were published. In [37], the authors introduced discussion on 6G enabling technologies. In [56], the authors
their 6G vision, discussing usage scenarios, target require- envisioned that 6G will act as an enabling platform to connect
ments, integrated space-air-ground-underwater networks, AI- the digital, physical, and biological worlds. In their 6G vision
based network design, and promising technologies. The paper [57], the authors focused on network architecture based on
[38] presented a 6G vision from the perspectives of time- the convergence of information, communication, and compu-
frequency-space resource usage, promising techniques toward tation technologies. The work [58] discussed the integration
6G, ML-aided intelligent transmission, and key challenges. of comfort, intelligence, and security in 6G networks. The
In [39], 6G was envisioned as a key enabler on the road paper [59] proposed an AI-empowered architecture to enable
to a ”global brain”. The paper focused on new services, their vision of intelligent 6G networks by introducing four
performance requirements, pervasive AI, THz and visible layers, i.e., intelligent sensing layer, data mining and analytics
light communications (VLC), as well as the synergy between layer, intelligent control layer, and smart application layer. In
communication, computation, caching, and control. In [40], 6G [60], 6G was considered in terms of the system architecture,
was studied in terms of research activities, key drivers, main network dimensions, possible technologies, promising appli-
 11

cations, and performance indicators. a discussion on societal and technological trends, emerging
In 2021-2024, a few 6G visions were introduced each year. applications and their requirements, research and standardiza-
In [61], the authors’ vision was based on four new paradigm tion efforts, and technology enablers. In [78], a survey was
shifts, including integrated space-air-ground networks, spec- conducted on the evolution from 5G to 6G networks. In [79],
trum operation at sub-6 GHz, mmWave, THz, and optical a comprehensive review was presented on the potential 6G
frequencies, AI-empowered mobile networks, and comprehen- technologies for achieving high data rates, enhanced energy
sive network security. In [62], the vision of the 6G ecosystem efficiency, full coverage, security and privacy, URLLC, and
was built on the current research status and anticipated future network intelligence. In [80], 6G was reviewed in terms of use
trends. The article [63] studied broadband connectivity for cases and applications, performance requirements, spectrum
6G to score the target data rate of 1 Tbit/s. The authors technologies, technical enablers, open challenges, and future
introduced a comprehensive set of technological enablers at research avenues.
the spectrum, infrastructure, and algorithmic levels. In [64], a The authors of [81] studied the evolution from 5G to 6G
top-down vision of the 6G ecosystem was provided, discussing by highlighting the shortcomings of 5G and the societal,
lifestyle and societal changes, applications and their technical economic, technological, and operational aspects of 6G. In
requirements, key challenges and opportunities for all layers, [82], the evolution of wireless networks to 6G was explored by
new spectrum bands and deployment scenarios, design prin- discussing the evolution of network architecture, application
ciples and required changes in radio access and core network areas, driving technologies, and ML techniques. In [83], 6G
architectures, novel PHY layer solutions, propagation char- was surveyed in terms of communication aspects, network
acteristics, real-time signal processing, and radio frequency architecture, and AI-enabled technologies. Recent advances
(RF) transceiver design. The work [65] introduced the 6G and open problems in 5G/6G research were studied in [84].
vision of the EU’s 6G flagship program Hexa-X. The five main The work [85] reviewed 6G communication technology from
contributions include a joint academic and industry perspective the aspects of usage scenarios, application opportunities, and
of 6G; review of concurrent 6G initiatives; identification of six potential technologies. In [86], the authors surveyed key 6G
key challenges; insightful discussion on application scenarios; technologies from the perspective of interactivity, connectivity,
and analysis of technological transformations in the radio, and intelligence. The paper [87] explored the five facets of
network, and orchestration domains. 6G, i.e., next-generation architectures, spectrum, and services;
In [66], the proposed 6G vision focused on immersive, networking; IoT; wireless positioning and sensing; and appli-
intelligent, and ubiquitous applications and the needed tech- cations of DL. A comprehensive survey of 6G and its recent
nologies. The paper [67] introduced its 6G exploration with research advances was provided in [88]. The paper reviewed
a discussion on the evolution of mobile networks, key fea- the global 6G vision, network requirements, application sce-
tures and the required capabilities, architectural perspectives, narios, network architecture, core technologies, and existing
hardware-software evolution, European 6G projects, and main testbeds.
applications and their challenges. A vision of 6G hyper- The authors of [89] identified 12 scientific challenges for 6G
connectivity, with nearly unlimited data rates, coverage, and to rethink the theoretical foundations of traditional communi-
computing, was given in [68]. In [69], the authors introduced a cation and to tackle the new paradigm of the convergence of
value-oriented 6G by defining multi-dimensional performance communication and beyond-communication technologies. The
indicators, enabling technological elements, and a case study work [90] examined 6G architectures and technologies to form
on intelligent multiple access. The work [70] briefly presented an enabling platform for innovative future applications. The
the 6G vision of the NGMN Alliance, focusing on the key use survey [91] built a comprehensive picture of 6G by analyzing
cases. The paper [71] introduced an evolutionary framework recent advances, key enablers, and technological challenges.
for 6G. The aspects explored are ITU-R activities, usage In [92], the authors provided an insightful analysis of 6G
scenarios, required capabilities, and potential technologies. In enabling technologies and discussed the design of a compre-
[72], the authors focused on building a 6G vision based on hensive 6G network architecture. The article [93] reviewed
four use cases, i.e., Internet of Senses, connected intelligent the key technologies of 6G networks, focusing on the extreme
machines, digitalized and programmable physical world, and performance that they can provide in diverse dimensions. In
connected sustainable world. In [73], the European 6G vision [94], 6G evolution was discussed, with a special focus on
was introduced, based on the perspective of the EU’s collab- the usage scenarios of IMT-2030. The work [95] explored
orative 6G research program SNS JU. the evolution from 5G-Advanced to 6G from the perspective
2) 6G Survey Articles: The first 6G survey article [74] was of three novel services, including immersive communications,
published in 2020, reviewing architectural framework, core everything connected, and high-accuracy sensing. In [96], the
technologies, application scenarios, and future challenges. The authors designed and reviewed an end-to-end 6G system,
work [75] provided a 6G survey on network requirements, based on the views of the EU’s 6G flagship project Hexa-X-II.
core features, potential applications, novel services, research
progress, and open challenges. In [76], the work provided a
comprehensive picture of the road toward 6G by reviewing F. Contributions of the Article
the key drivers, application scenarios, target requirements, In this section, the contributions of this article are sum-
development efforts, and technological enablers. The authors marized. For clarity, they are presented in the order of their
in [77] provided a thorough survey of the 6G frontiers, with appearance in the article.
 12

tutorial for 6G, all in the same package. To the best of

I. Introduction
our knowledge, this is one of the most comprehensive 6G
•A Brief History of Mobile Communications articles written in the literature.
•5G in a Nutshell • Evolution from 1G to 6G: We provide an insightful
•6G Development Process introduction to the evolution of mobile communications
•6G Research Activities by presenting the essentials of each generation. In partic-
•Literature Review on 6G Visions and Surveys ular, we discuss how disruptive different generations have
•Contributions of the Article been and envision what will be the next major disruption
enabled by 6G.
II. 6G Vision • Overview of 5G: We present a compact overview of 5G.
The focus is on 3GPP’s 5G System and Releases 15, 16,
17, 18, and 19.
III. Fundamental Elements of 6G
• Development Process of 6G: We describe the devel-
opment process of 6G at a high level. Specifically, we
IV. Disruptive Applications for 6G discuss the roles of academia, industry, ITU-R, and 3GPP.
The estimated timeline is also introduced.
•Human-Machine Interactions
• Research Activities toward 6G: We review the main
•Smart Environments
worldwide 6G research activities in a chronological order
•Connected Autonomous Systems
(2018-2024). Various types of activities are considered,
such as projects, collaborations, funding, standardization,
V. Key Use Cases for 6G experiments, events, and publications.
• Literature Review on 6G Visions and Surveys: We
•Communication-Oriented Use Cases
review the main 6G vision and survey articles.
•Beyond-Communication-Oriented Use Cases
• 6G Vision: We introduce an insightful and coherent
6G vision. In our vision, we identify the big picture,
VI. Main Performance Requirements for 6G fundamental elements, disruptive applications, key use
cases, target requirements, potential technologies, and
VII. AI/ML for 6G defining features. Our vision is well aligned with ITU-R’s
”IMT-2030 Framework”, but more far-reaching.
•Introduction to AI and ML
• Fundamental Elements of 6G: We identify and discuss
•Promising ML Methods for 6G
three fundamental elements of 6G, i.e., wireless, AI, and
IoE.
VIII. Potential Technologies for 6G • Disruptive Applications for 6G: We define 12 disruptive
applications for 6G in three categories, i.e., human-
•Spectrum-Level Technologies
machine interactions, smart environments, and connected
•Antenna System Technologies
•Transmission Scheme Technologies
autonomous systems.
•Network Architectural Technologies • Key Use Cases for 6G: We identify eight pri-
•Network Intelligence Technologies mary use cases in two different categories for 6G,
•Beyond-Communication Technologies i.e., five communication-oriented and three beyond-
•Energy-Aware Technologies communication-oriented.
•End-Device-Oriented Technologies • Main Performance Requirements for 6G: We review
•Service-Oriented Technologies the main performance requirements of IMT-2030, intro-
•Security Technologies duced by ITU-R, and compare them to the typically
proposed values in the 6G literature.
IX. Defining Features for 6G • AI/ML for 6G: We provide a brief introduction to the
concepts of AI and ML, and discuss three promising ML
methods for 6G.
X. 6G in a Nutshell
• Potential Technologies for 6G: We identify a compre-
hensive set of potential 6G technologies. Each technology
XI. 7G Vision: A High-Level Sketch is reviewed in a tutorial manner, along with a survey of
the main literature. Specifically, we discuss the vision, in-
XII. Conclusion troduction, past, present, opportunities, challenges, litera-
ture, and future directions. To the best of our knowledge,
Fig. 5. Content of the article. this is the most comprehensive set of 6G technologies
reviewed in the literature.
• Comprehensive Vision, Survey, and Tutorial on 6G: • Defining Features for 6G: We specify 12 main features
The main contribution of this article is to provide an that define the essence of 6G.
insightful vision, contemporary survey, and instructive • 6G in a Nutshell: We provide a compact summary of our
 13

6G vision in bullet points so that the readers can obtain • Big Picture: Based on the current trends, we envision
the big picture of 6G at one glance. that the next major disruption in mobile communications
• 7G Vision: To place our 6G vision in a broader perspec- will be the 6G-enabled mobile intelligence. Mobile in-
tive, we discuss what comes after 6G and sketch the first telligence refers to the fusion of wireless, AI, and IoE
high-level vision on 7G. The focus is on the main dis- technologies at all levels of society. Mobile intelligence
ruption, fundamental elements, and possible applications has the potential to make anything connected, smart,
of 7G. To the best of our knowledge, this is the first 7G and aware of the surrounding environment. Consequently,
vision in the literature. mobile intelligence will revolutionize the design, op-
The remainder of this paper is organized as follows. In eration, interactions, and use of devices, systems, and
Section II, our 6G vision is introduced. Three fundamental applications. We envisage that 6G can ultimately become
elements of 6G are identified in Section III. Section IV defines the Intelligent Network of Everything and serve as an
a comprehensive set of disruptive 6G applications. Key use enabling platform for the mobile intelligence. The 6G-
cases are proposed for 6G in Section V. Section VI reviews the enabled mobile intelligence will create a smart wireless
main performance requirements that 6G is expected to satisfy. world, where there are unprecedented opportunities to
AI/ML is discussed for 6G in Section VII. In Section VIII, a produce greater value for the benefit of people, society,
comprehensive set of potential 6G technologies is reviewed. and the world in general. Eventually, mobile intelligence
Twelve features that define the essence of 6G are identified will penetrate all walks of life and become an essential
in Section IX. Section X summarizes our 6G vision in the part of the future society.
bullet points. In Section XI, the post-6G era is speculated and • Fundamental Elements: To provide a major disruption,
a high-level vision is sketched for 7G. Finally, conclusions are 6G needs to be based on three profound elements:
drawn in Section XII. The list of abbreviations can be found in wireless, AI, and IoE. Wireless consists of connectivity,
Appendix. The outline of the article is summarized in Figure computation, sensing, and energy dimensions. AI refers to
5. the extensive use of AI at all levels of the 6G ecosystem,
including the network core, network edges, air interface,
devices, services, and applications. IoE refers to the
massive number of network-connected objects, such as
sensors, devices, machines, vehicles, drones, robots, etc.
Further details on the fundamental elements are provided
in Section III.
• Disruptive Applications: 6G is expected to support a
wide range of game-changing applications. We divide the
main ones into three categories: human-machine inter-
actions, smart environments, and connected autonomous
systems. The concept of human-machine interactions
refers to the different ways in which humans interact
with machines, devices, and smart entities. We define
five key interactions: metaverse, XR, holographic-type
communications, digital twins, and Tactile Internet. To
support such data-hungry and time-sensitive applications,
6G must provide ultra-high data rates and extremely low
latency. The concept of smart environment is defined as
an entity that exploits wireless, AI, and IoE technologies
to produce greater value. We specify four main environ-
ments, i.e., smart society, smart city, smart factory, and
smart home.
Fig. 6. 6G vision: smart wireless world via 6G-enabled wireless intelligence.
For smart environments, 6G needs to provide customized
wireless network services with IoE communications,
beyond-communication capabilities, and secure network
II. 6G V ISION solutions. Connected autonomous systems refer to entities
In this section, our 6G vision is introduced. First, the big that can operate independently without human involve-
picture of 6G is discussed. Then, the focus is shifted to the ment, relying on versatile technologies, such as AI,
main details. Specifically, a brief introduction is provided to control, sensing, positioning, and connectivity. We define
the fundamental elements, disruptive applications, key use three systems: connected autonomous vehicle systems,
cases, target performance requirements, potential technologies, connected autonomous aerial vehicle systems, and con-
and defining features. These topics are discussed in detail nected autonomous robotic systems. Such systems set
in their dedicated sections later in the paper. It is worth stringent performance requirements for 6G, particularly
mentioning that our 6G vision is well aligned with ITU-R’s in terms of reliability, availability, latency, and mobility.
one, although more far-reaching with a broader perspective. A detailed discussion of 6G applications is provided in
 14

Section IV. The 6G vision of the smart wireless world to-device (D2D), V2X, and cellular-connected UAV com-
with the aforementioned applications is illustrated in munications extend the support for the IoE-type connec-
Figure 6. tivity in the 6G era. The main service-oriented technolo-
• Key Use Cases: Since 6G is expected to significantly gies are private networks, which significantly broaden the
expand the capabilities of mobile networks, we intro- service and business opportunities of mobile networks
duce five communication-oriented and three beyond- in diverse vertical domains. A holistic network security
communication-oriented use cases accordingly. In the architecture is vital for the success of 6G, providing
communication domain, there are six main performance trustworthy, secure, and privacy-protected use. In Section
dimensions that must be optimized for 6G, i.e., capacity, VIII, the potential 6G technologies are reviewed in a
latency, reliability, density, coverage, and mobility. The tutorial manner.
corresponding use cases are ultra-broadband multime- • Defining Features: We introduce 12 features that define
dia communications, extreme time-sensitive and mission- the essence of 6G: extreme capacity & performance,
critical communications, ultra-massive communications, ultra-flexible & agile, highly intelligent & aware, ubiq-
global-scale communications, and hyper-mobility com- uitously available & reliable, truly green & sustainable,
munications. In addition to the enhanced communication and thoroughly secure & trustworthy. The core of 6G will
features, 6G aims to extend its capabilities beyond com- be extreme performance, especially in terms of capacity,
munication. The corresponding use cases include network latency, reliability, density, coverage, and mobility. 6G
intelligence, network sensing, and network energy. Fur- needs to be flexible and agile to adapt to versatile wireless
ther details on these use cases are provided in Section environments and application scenarios. A high level of
V. intelligence and awareness requires pervasive AI and
• Performance Requirements: To support diverse use accurate sensing, providing many benefits from efficient
cases and applications, the performance requirements of network optimization and increased automation to object
6G need to be pushed to their limits. ITU-R has intro- recognition and velocity estimation. To support diverse
duced example target values for nine main performance services, 6G must be broadly available and reliable. To
metrics: peak rate (50/100/200 Gbit/s), user experienced obtain significant ecological benefits, sustainability and
rate (300/500 Mbit/s), spectral efficiency (1.5X/3X), greenness need to be integral parts of 6G. Since 6G will
area traffic capacity (30/50 Mbit/s/m2 ), latency (0.1–1 be a pivotal part of the future society, it needs to be
ms), reliability (1-10-5 –1-10-7 ), connection density (106 – secure and trustworthy. Further discussion on the defining
108 /km2 ), mobility (500–1000 km/h), and positioning features can be found in Section IX.
accuracy (1–10 cm). Compared to the targets proposed
in the 6G literature, ITU-R’s values are rather moderate. WIRELESS
A more detailed discussion on the target requirements is
provided in Section VI.
• Potential Technologies: A vast variety of advanced 6G
technologies are required to support the expected require-
ments, use cases, and applications. A comprehensive set
of key technologies is identified and reviewed in ten
different network categories, including spectrum, antenna 6G
systems, transmission scheme, network architecture, net- ELEMENTS
work intelligence, beyond-communication, energy aware-
ness, end-devices, services, and security. At the core
of spectrum-level technologies is THz communications,
providing extremely high data rates. Extreme antenna
systems, such as ultra-massive MIMO and RISs, offer
high spectral efficiency and extended coverage. An ultra- IoE AI
flexible transmission scheme based on a multi-waveform
Fig. 7. Fundamental elements of 6G.
design, with flexible numerology, and fast grant-free
access will form the basis for the 6G air interface.
Integrating non-terrestrial access to the network design III. F UNDAMENTAL E LEMENTS OF 6G
leads to a 3D space-air-ground architecture, with potential
global-scale coverage. This section discusses the foundational building blocks of
In the network intelligence domain, AI/ML plays a rev- 6G. To become a highly disruptive network, 6G needs to be
olutionary role by empowering the network core, edges, based on three fundamental elements, i.e., wireless, AI, and
and air interface. Integrating communication, computa- IoE, as illustrated in Figure 7.
tion, sensing, and energy greatly expands the capabilities • Wireless: In the context of 6G, wireless refers to a variety
of mobile networks. Green communication and network- of technologies including connectivity, sensing, position-
ing provide significant ecological benefits, making 6G ing, and energy. Extreme connectivity lays the foundation
more energy-efficient and sustainable. Advanced device- for 6G and its numerous applications. There are six main
 15

performance dimensions that need to be pushed to the 6G APPLICATIONS

extreme levels, i.e., capacity, latency, reliability, density,
HUMAN-MACHINE INTERACTIONS
coverage, and mobility. Consequently, 6G is expected to
support a vast range of communication scenarios, includ-
ing ultra-fast mobile internet, time-sensitive and mission-
METAVERSE EXTENDED HOLOGRAPHIC DIGITAL TWINS TACTILE
critical connectivity, ultra-dense IoT, global coverage, and REALITY COMMUNICATION INTERNET
hyper-mobility communications. Beyond-communication SMART ENVIRONMENTS
wireless technologies, such as high-resolution sensing,
accurate positioning, and wireless energy, expand the
capabilities of mobile networks beyond the current hori-
SMART SOCIETY SMART CITY SMART FACTORY SMART HOME
zon. For example, mobile networks can provide novel
services, like object recognition/identification, location- CONNECTED AUTONOMOUS SYSTEMS
based services, and wireless powering of lightweight IoT
devices.
• Artificial Intelligence: The extensive use of AI forms VEHICLE AERIAL VEHICLE ROBOTIC
the basis for the 6G network intelligence. AI will be SYSTEMS SYSTEMS SYSTEMS

exploited at all levels of the network, including the

Fig. 8. Disruptive applications for 6G.
core, edge, and air interface. While AI will upgrade
the core network from cloud to cloud intelligence, the
network edge will evolve from edge computing to edge the next-generation Internet [97] or successor of the mobile
intelligence. AI has the potential to profoundly change internet [98]. The evolution toward this emerging paradigm
the way how mobile networks are designed, operated, has been driven by advances in key technological areas,
and managed. Ultimately, pervasive AI/ML can make 6G such as XR, AI/ML, and 5G/B5G/6G [97], [98]. It has been
more intelligent, efficient, flexible, scalable, autonomous, proposed that a generic evolution road to a fully immersive
automated, proactive, economical, ecological, trustwor- metaverse consists of three main phases: digital twins, digital
thy, and secure. natives, and surreality [97], [99]. The goal of the first phase
• Internet of Everything: IoE refers to the massive num- is to form digital mirror worlds of real-life objects, systems,
ber of diverse types of connected objects/entities, such and entities using digital twins. The second phase aims to
as sensors, devices, machines, vehicles, drones, robots, create native digital content inside the virtual world. The third
systems, networks, processes, and applications. IoE can phase completes the evolution of the metaverse by producing
be seen as a major extension of IoT. Whereas IoT is surrealistic virtual worlds that seamlessly merge reality with
often seen as connected sensors, IoE is a much broader digitality. The current evolutionary state of the metaverse is
concept. Strong support for IoE enables novel function- still in its infancy and far from its ultimate vision. In this
alities and applications for different objects and entities. picture, 6G is expected to provide a fruitful platform for the
IoE is a paradigm shift from human- to machine- and metaverse to grow toward its vision [100]–[104].
application-centric communications, where the connectiv- The term ”metaverse” was first used in science fiction in
ity of objects/entities is at the center of attention. This will 1992 [98]. In the 2010s, the term metaverse re-emerged and
significantly extend the applicability of mobile networks evolved toward the current vision. Simultaneously, metaverse
to versatile vertical industries. began to gain more attention in science, becoming a popular
topic on the verge of the 2020s. The COVID-19 pandemic
IV. D ISRUPTIVE A PPLICATIONS FOR 6G has further increased interest in the metaverse since many
In this section, we introduce 12 disruptive 6G applications in physical activities have moved to the virtual space [98]. The
the categories of human-machine interactions, smart environ- metaverse is widely recognized in the technology industry.
ments, and connected autonomous systems. These applications Major technology companies are investing in the development
are summarized in Figure 8. of practical metaverse applications. For example, Facebook
was renamed Meta in 2021 to better describe the company’s
vision [98]. In practice, there exist some applications that are
A. Human-Machine Interactions considered rudimentary versions of the metaverse, mainly in
Human-machine interactions refer to the ways in which gaming. Second Life, Roblox, and Fortnite are examples of
humans interact with machines, devices, and different types such gaming platforms [97]. In the standardization domain,
of smart entities. In the following, we review five main there exist two metaverse-related standards [97], i.e., ISO/IEC
interactions for 6G, including metaverse, XR, holographic- 23005 and IEEE 2888. ISO/IEC 23005 focuses on stan-
type communications, digital twins, and Tactile Internet. dardizing the interfaces between the real-virtual and virtual-
1) Metaverse: Metaverse is a computer-generated virtual virtual worlds. IEEE 2888 complements ISO/IEC 23005 by
shared space [97]. The grand vision of the metaverse is standardizing the synchronization between the real and virtual
a fully immersive, interoperable, and hyper-spatio-temporal worlds. Further details on the fundamentals, latest advances,
virtual ecosystem merging the physical, human, and digital and future challenges of the metaverse can be found in recent
worlds [97], [98]. This vision is sometimes referred to as survey papers: generic [97]–[99], [105]–[107] and 6G-related
 16

[100]–[104]. communications to the destination, and finally presented by a

2) Extended Reality: XR is a broad term that covers all holographic display [113]. There are three main types of dis-
types of combined scenarios between real and virtual envi- plays: XR HMDs, volumetric displays, and light-field displays
ronments. Virtual reality (VR), augmented reality (AR), and [113]. XR HMDs are close to the user’s eyes, with two view
mixed reality (MR) fall under the umbrella of XR [108]. angles and looser requirements for data transfer. Volumetric
VR refers to all virtual scenarios, whereas AR adds virtual displays are suitable for mobile devices due to their small
content to the real environment. MR is a blend of the real and size and limited viewing angles. Light-field displays have
virtual environments. Currently, XR is most commonly used the highest quality with thousands of view angles, multi-user
for entertainment purposes, such as gaming. Other application support, and extremely high requirements for holographic-type
scenarios are work, education, business, healthcare, marketing, communications.
and training, to mention a few. XR is expected to merge Since the late 2000s, an increasing number of demonstra-
deeply into society and profoundly change how people live, tions on end-to-end holographic systems have been carried out
experience, and interact [108]. Traditionally, XR systems have [113]. However, the quality of holographic experience is still
mainly focused on two out of the five human senses, i.e., rather limited due to the limited (rate/latency) performance
sight and hearing, through audiovisual data. The sense of of existing communication networks. Immersive high-quality
touch through haptic technologies is also popular nowadays. holograms (e.g., using light-field displays) require extremely
Haptic technologies exploit vibrations, motions, and forces high data rates (even Tbps-level) and ultra-low latency (even
to mimic the experience of touch. Haptic information in sub-millisecond-level) [113], [114]. It is expected that 6G and
combination with audiovisual data makes the XR experience future wired networks will satisfy these extreme requirements
more immersive. The ultimate goal is to also add the senses of and enable novel holographic applications and business op-
smell and taste to achieve a fully immersive experience. This portunities. Potential holographic application scenarios include
5-sense experience will be a major step and will make XR a education, training, healthcare, gaming, sports, and marketing
particularly attractive technology. [113]. Holographic telepresence enables remote participation
Although VR/AR has been developed for decades [108], XR in meetings and events, as realistic holograms. HMD-based
is still far from its potential. Existing XR devices (i.e., head- holograms can be used as a part of education and training
mounted displays (HMDs)) are rather expensive, relatively to make them more interactive, educational, and efficient.
large/heavy, and often wired, limiting their popularity. Today, In healthcare, holograms can assist in surgeries and remote
the leading high-end XR HMDs are Apple Vision Pro and Mi- diagnostics. Holographic technologies enable more immersive
crosoft HoloLens 2. To become mainstream, XR devices need ways to experience sports and gaming. For example, a game
to be affordable, lightweight, and wireless. Current wireless can be projected onto a 3D hologram. In marketing, holo-
XR devices rely primarily on wireless fidelity (WiFi) connec- graphic advertisements with a 5-sense technology can provide
tions. However, the limited latency and reliability properties of a real-like experience and may revolutionize the whole in-
WiFi links may limit the quality of the XR experience. 5G has dustry. More information on holographic-type communications
a better service quality, making it a promising technology for can be found in [113]–[115].
wireless XR. 5G is currently adopting support for wireless XR. 4) Digital Twins: A simple definition of a digital twin
However, future immersive XR applications will be extremely is a virtual digital copy of a physical object or entity. This
data-hungry and delay-sensitive, thereby setting stringent re- real-world object/entity can be, for example, a sensor, device,
quirements for wireless connections. Since 5G cannot meet machine, vehicle, UAV, robot, process, system, network, or
these demands, 6G is expected to take wireless multi-sensory even human. Conceptually, a digital twin can be divided
XR to the next level, potentially making it truly immersive, into three parts, i.e., the physical object, digital object, and
mainstream, and ubiquitous. For example, 6G-level XR is connections between them [116]. With these connections,
expected to form the core for advanced metaverse applications. a comprehensive amount of data can be collected from a
For more information on the 5G XR standardization, wireless physical object to form an accurate digital copy. With the aid
challenges for XR, and ISAC for XR, see [109]–[111], [108], of digital twins, one can monitor, analyze, evaluate, control,
and [112], respectively. and manage a physical object/entity through the collected
3) Holographic-type Communication: Holographic-type information [116]. Digital twins can provide many advantages
communication refers to the transfer of holograms from a [116], for example, facilitate product development and testing,
source to a (remote) destination via wireless/wired networks improve the efficiency and reliability of processes, and reduce
[113]. A hologram is a realistic 3D representation of an object the operational and maintenance costs of systems. There are
based on the depth and parallax information [113]. Unlike a numerous application scenarios for digital twins [116], in-
traditional 3D image, a hologram changes according to the cluding manufacturing, product development, process design,
viewer’s position [114]. Holography refers to a technology system maintenance, network management, robotics, construc-
creating holograms [113]. Specifically, a camera array is tion, healthcare, automotive industry, smart factory, smart city,
placed around a 3D object to collect image information from and metaverse. Generally, the digital twin technology is seen
multiple angles and views. This information is then processed as a key element in the realization of the fourth industrial
to generate a 3D hologram. To summarize an end-to-end revolution (i.e., industry 4.0) [116].
holographic system, holograms are generated using hologra- The first precursor of the digital twin concept dates back to
phy (or stored) at the source, transferred via holographic-type the 1960s, when NASA started to model and analyze space
 17

systems on the ground [117]. The basic architecture of a IoT/IoE, cloud/edge computing, big/small data, and data secu-
digital twin, consisting of real space, virtual space, and the rity/privacy, are exploited to produce greater value. A greater
communication link between them, was introduced in 2002, value can be, for example, a better quality of life for an indi-
under the name ”mirrored spaces model” [116]. This landmark vidual, more efficient manufacturing for a company, or better
is seen as the beginning of modern digital twin research. Due services for the residents of a city. 6G is seen as a common
to advances in key technologies, such as AI/ML, IoT, 5G/6G, enabler for mainstreaming many types of smart environments.
distributed computing, and XR [116], the attention toward In the following, we discuss four smart environments: smart
digital twins (in industry and academia) has been growing society, smart city, smart factory, and smart home.
since the 2010s. Today, the use of digital twins is spreading 1) Smart Society: At a fundamental level, a smart society
widely across industries. The digital twin concept is one of the can be defined as a concept that exploits a vast variety of ad-
major research areas in the field of technology [116]. However, vanced digital technologies to provide benefits to all levels of
the digital twin technology is still at a rather early stage in the society. By utilizing these technologies, a smart society is
its evolution path and far from its envisioned potential. It is expected to offer diverse benefits for individuals, communities,
expected that digital twins will shape the future by connecting and private/public sectors. Possible benefits for people include
the physical and digital worlds in a revolutionary way, thus a better quality of life in terms of improved services related to
becoming an integral part of a 6G-enabled smart society. In living conditions, healthcare, work, education, social benefits,
the context of 6G and wireless networks, the latest information free-time activities, and public safety. The potential benefits
on digital twins can be found in [116]–[127]. for the private sector include new business opportunities, more
5) Tactile Internet: In a broad sense, Tactile Internet is efficient processes (e.g., manufacturing, testing, and design),
considered as a communication system that can provide real- reduced costs (e.g., production, operation, and maintenance),
time control and interactivity between humans and machines, and reduced environmental impact. A smart society comprises
with the aid of haptic information (e.g., touch, vibration, and numerous vertical segments, such as smart governance, smart
motion) in addition to traditional audiovisual data [128]. In economy, smart healthcare, smart energy, smart grid, smart
other words, Tactile Internet can be seen as a paradigm shift industry, smart infrastructure, smart education, smart cities,
from conventional content-based communications to control- smart organizations, smart mobility, smart agriculture, smart
based communications [129]. Tactile Internet is considered the culture, smart security, etc.
next evolution step of the Internet, after the mobile internet 2) Smart City: By relying on advanced information and
and IoT [128]. Tactile Internet can be exploited for a wide communication technologies, the concept of a smart city aims
range of applications [128], such as industrial automation, to improve the city’s management, operation, maintenance,
robotics, gaming, healthcare (e.g., remote surgery), intelligent and services to offer diverse advantages and a better qual-
transportation/vehicle systems, and education/training. To re- ity of life for its residents. The synergy among advanced
alize Tactile Internet, it requires ultra-low latency (up to 1 ms) digital technologies provides a fruitful platform to enable
with high reliability (up to 1-10-7 ), availability, and security smart cities worldwide. Smart cities will be more efficient
[128], [130]. These requirements are highly dependent on the in numerous ways and will offer a broad range of improved
application scenario. and novel services for their residents. A smart city consists of
The concept of Tactile Internet was first introduced in 2014 diverse elements [132], [133], such as smart governance, smart
[130]. In 2016, a working group was established for the economy, smart environment (nature), smart transportation,
first standards (i.e., IEEE P1918.1) related to Tactile Internet smart traffic, smart water, smart waste, smart sanitation, smart
[128]. The main objective of IEEE P1918.1 was to specify the schools, smart buildings, smart homes, smart lighting, smart
architectural basis for Tactile Internet. In the research domain, culture, smart sports, smart activities, smart parking, smart
5G was first seen as an enabler for Tactile Internet due to shopping, and so on. The opportunities, challenges, priorities,
its support for URLLC with a latency of up to 1 ms [128]. and realizations of smart cities depend on many different
However, 5G was not designed to support Tactile Internet and factors, such as the population, location, climate, environment,
its demanding applications. Hence, 5G is not able to serve as and area of the city [132], [133]. Thus, each city is different,
an enabling platform for Tactile Internet in practice. Despite and smart elements need to be designed accordingly. Currently,
the lack of broad support, 5G still has the potential to enable numerous smart city plans and projects are ongoing around
light versions of tactile applications and pave the way for 6G the world [132], [133]. It is envisioned that smart cities will
networks as a true enabler. 6G is expected to provide a fruitful prosper in the 6G era since key technologies have become
platform for Tactile Internet and enable the broad use of sufficiently mature to enable such complex entities [133]–
novel real-time interactive applications [131]. 6G’s capabilities [135]. Recent information on smart cities is available in [132]–
go way beyond 5G’s in every aspect, especially in terms of [137].
performance, intelligence, flexibility, and security, all of which 3) Smart Factory: A smart factory is a concept that merges
are essential for realizing Tactile Internet in practice. Further advanced information, communication, networking, comput-
details on Tactile Internet can be found in [128], [129], [131]. ing, and control technologies and processes to increase the
intelligence, automation, efficiency, productivity, quality, flex-
B. Smart Environments ibility, adaptability, and predictability of a factory [138], [139].
A smart environment refers to an entity in which A smart factory is at the core of industry 4.0 [138], [139].
advanced digital technologies, such as 5G/6G, AI/ML, Industry 4.0 refers to the new era of smart manufacturing,
 18

where the integration of advanced digital technologies (e.g., 1) Connected Autonomous Vehicle Systems: Connected au-
IoT, AI, big data, and cloud computing) become mainstream, tonomous vehicle systems (CAVSs) refer to intelligent vehicle
revolutionizing the entire industrial sector. Smart factories entities that consist of connected autonomous vehicles (CAVs)
provide diverse benefits, such as improved monitoring, man- capable of independently driving on the roads with no (or
agement, maintenance, and repair of processes; increased little) human involvement to transport people and goods.
manufacturing efficiency; reduced manufacturing costs; higher Autonomous vehicles, commonly known as self-driving cars,
quality products; faster production cycles; more robust pro- exploit AI-empowered computing and control by relying on
cesses; enhanced security; better prevention of threats/hazards; comprehensive real-time navigation, tracking, and sensing
and novel production solutions. Although a smart factory is information about the vehicle itself and its surrounding en-
currently a relatively immature concept, it is expected to vironment. The term CAV is commonly used to define an
reach an adequate level of maturity in the 6G era. Detailed autonomous vehicle that is capable of connecting to other
discussions on smart factories and industry 4.0 can be found vehicles, traffic infrastructure, cellular networks, and other
in [138]–[142]. road users. These different types of connectivity in vehicular
4) Smart Home: A smart home refers to a home that systems fall under the umbrella of V2X communications. The
is equipped with an intelligent, connected, automated, and level of autonomy in vehicles is divided into six categories
integrated control, computing, and communication system that by the Society of Automotive Engineers [149], i.e., Level 0:
provides comprehensive management and monitoring of the no automation, Level 1: driver assistance (hands on), Level 2:
entire home ecosystem, including heating, air conditioning, partial automation (hands off), Level 3: conditional automation
water, electricity, energy consumption, lighting, entertainment, (eyes off), Level 4: high automation (mind off), and Level 5:
appliances, household robots, air quality, smoke/gas/leak de- full automation.
tection, home access, security, and privacy. AI, IoT, and
The development of autonomous vehicles has gradually
wireless connectivity are vital elements of a smart-home
evolved from small individual experiments of partially auto-
ecosystem. The concept of a smart home (also known as
mated cars to thorough testing of truly self-driving cars around
an automated home) has been studied for over two decades.
the world and launching of numerous pre-commercialized and
However, to date, there have been no real breakthroughs.
commercialized local intelligent transportation services. The
Currently, there is a wide range of smart home products in
future trends in autonomous vehicles can be divided into two
the market. Typical ones include lighting, security cameras,
main branches. First, the automotive industry is evolving to-
wireless network elements, voice assistants, TVs, speakers,
ward fully electric cars, with increasing levels of intelligence,
etc. There are also numerous service providers with (mainly)
automation, and autonomy. It is expected that the level of
WiFi-based cloud services. Although there are many prod-
automation of different driver-assistance features will grad-
ucts and services, the markets and solutions are somewhat
ually move toward level 5 (full automation). Second, private
fragmented. Moreover, there is still a lack of comprehensive
companies are launching different types of pre-commercialized
smart and automated home solutions that include all vital
and commercialized local intelligent transportation services
elements. Common policies and standardization are also in-
around the world. This trend will continue in three main ways,
adequate, especially in terms of data security and privacy. A
i.e., more services, locations, and coverage.
real breakthrough in smart homes is still awaiting.
Smart homes are anticipated to become popular in the 6G Since 5G is not optimized for intelligent vehicles, it will
era due to the maturation of key technologies, such as intelli- reach its limits in providing ubiquitous and reliable connec-
gent cloud with AI-empowered computing and control, high- tivity for CAVSs. 6G, instead, will be developed to provide
accuracy sensing and indoor localization, seamless wireless better support for CAVs and intelligent transportation systems.
connectivity and IoT support, as well as data security and pri- It is envisioned that 6G will serve as a fruitful platform to
vacy. This will open new business opportunities for technology enable a large-scale usage of CAVs as a part of intelligent
companies (such as mobile network operators, vendors, and vehicular and transportation systems [150], [151]. In the 6G
service providers) to provide customized and comprehensive era, there will be many application scenarios for CAVs, such
smart home solutions with plug-and-play styles. This requires as individual consumer products, public transportation, private
cooperation between technology companies, constructors, and transportation, freight traffic, and product delivery. In the
building/homeowners. Further discussions on the smart home literature, autonomous vehicles have been extensively studied.
concept can be found in [143]–[148]. The earliest considerable works were published in the 1990s.
However, it was until the 2010s when the research really
C. Connected Autonomous Systems boomed. Since then, numerous aspects of autonomous vehicles
Connected autonomous systems refer to intelligent entities have been covered, such as 6G/B5G/5G, AI/ML, control,
that are capable of operating independently without human navigation, sensing, communication, safety, traffic efficiency,
influence by relying on a wide range of technologies, ranging security, privacy, liability issues, regulations, social perspec-
from computation and control to sensing, navigation, and tives, intelligent transportation systems, and smart cities. In
communication. In this section, three types of connected the context of mobile networks, it is vital to develop advanced
autonomous systems are discussed, including connected au- V2X communications for CAVs and the Internet of Vehicles
tonomous vehicle systems, connected autonomous aerial vehi- (IoV) scenarios. Detailed discussions on 6G communications
cle systems, and connected autonomous robotic systems. for CAVs are available in [150]–[158].
 19

2) Connected Autonomous Aerial Vehicle Systems: Con- 6G USE CASES

nected autonomous aerial vehicle systems (CAAVSs) refer
to intelligent, cooperative, and independent entities, which COMMUNICATION-ORIENTED
manage their individual units of intelligent aerial vehicles
(typically UAVs) capable of flying independently with no (or
little) human influence, relying on AI-driven control systems
ULTRA-BROADBAND EXTREME ULTRA-MASSIVE GLOBAL-SCALE HYPER-MOBILITY
with advanced computation, navigation, sensing, and com- MISSION-CRITICAL
munication features. Note that a special case of CAAVS is BEYOND-COMMUNICATION-ORIENTED
a single connected autonomous aerial vehicle (e.g., a con-
nected autonomous UAV). A typical example of CAAVS is
an autonomous UAV swarm. An autonomous UAV swarm
comprises a set of UAVs that cooperatively perform diverse NETWORK NETWORK NETWORK
INTELLIGENCE SENSING ENERGY
tasks as independent intelligent entities. Potential application
scenarios include surveillance, environmental and industrial Fig. 9. Key use cases for 6G.
monitoring, malfunction detection, disaster aid, search oper-
ations, precision agriculture, and entertainment. In addition,
autonomous UAVs for delivering items (i.e., air cargo) or and introducing new beyond-communication ones. Following
carrying people (i.e., air taxis) can be considered CAAVSs. this evolution, we introduce five communication-oriented and
Currently, there exist many pre-commercialized and commer- three beyond-communication-oriented use cases, supporting a
cialized air cargo and taxi services worldwide. These services wide range of new 6G-level application scenarios. These use
are expected to continue to spread both horizontally and cases are summarized in Figure 9.
vertically. 6G is seen as a promising platform to enable
CAAVSs since it can potentially provide ubiquitous, high- A. Communication-Oriented Use Cases
performance, and reliable mobile connectivity for UAVs. Fur-
ther information on UAVs and UAV swarms can be found in 6G is expected to push the communication performance
[159]–[162] and [163]–[166], respectively. into its limits. The corresponding performance dimensions are
3) Connected Autonomous Robotic Systems: Connected au- capacity, latency, reliability, density, coverage, and mobility.
tonomous robotic systems (CARSs) refer to intelligent robotic We identify five communication-oriented use cases to cover
entities that can independently and cooperatively perform all of these dimensions.
complex tasks assigned to them without external human con- • Ultra-Broadband Multimedia Communications: The
trol. The core of CARSs is an AI/ML-based control system goal of this use case is to provide wide support for
that requires advanced computation, data analytics, sensing, immersive multimedia content in diverse environments,
positioning, communications, and security capabilities. CARSs from dense hotspots to sparse rural areas. Examples
are connected to a wireless network, allowing communication of data-hungry application scenarios are wireless multi-
and information exchange between a cloud server and other sensory XR, holographic-type communications, informa-
nodes in the network. Network connectivity enables novel tion showers, and ultra-broadband mobile internet. Due to
capabilities, features, and applications of robotic systems, the nature of demanding applications, this use case needs
while advancing collaboration and interaction among them. to support many different performance requirements, such
CARSs have the potential to significantly widen the applica- as very high link- and network-level capacities, low
bility of robotics to new areas and tasks. CARSs can adapt latency, and high reliability. The key enablers include
to dynamic environments and changing conditions. CARSs massive radio resources for capacity (more spectrum,
are applicable to numerous verticals, including manufacturing, cells, and antennas), fast network mechanisms for low
warehousing, logistics, transportation, aviation, healthcare, and latency, and robust communication methods for reliabil-
services. CARSs are expected to play a key role in future ity. Achieving these requirements simultaneously is an
smart factories by expanding their capabilities, increasing application-specific trade-off since each one of them is
flexibility, improving efficiency, and reducing costs. From a (more or less) conflicting to each other. Note that this
wider perspective, CARSs are seen as a means of taking use case can be considered as an extension of 5G eMBB.
robotics to the next level by freeing its potential. In this regard, • Extreme Time-Sensitive and Mission-Critical Commu-
6G is considered a promising platform for providing cus- nications: This use case is intended to support time-
tomized network solutions to ensure secure high-performance sensitive and mission-critical applications in versatile
connectivity with minimal delays, extreme levels of reliability, environments, such as smart factories, smart hospitals,
and advanced IoT capabilities. Further details on connected autonomous vehicle systems, and emergency operations.
robotics can be found in [140], [167]–[171]. Extreme reliability and very low latency are required
since there is no room for severe errors. The main
enablers for extreme reliability include network- and link-
V. K EY U SE C ASES FOR 6G
level diversity methods, high channel coding rates, robust
6G is expected to greatly expand the capabilities of mobile modulation orders, and advanced retransmission mecha-
networks by enhancing ”traditional” communication features nisms. Extremely low latency can be attained through
 20

flat higher-layer management procedures, bringing con- caching. This use case requires powerful computation
tent close to end-devices, minimized control signaling, and storage abilities, advanced AI/ML methods, abun-
fast network access mechanisms, and short transmission dant data acquisition, and efficient AI/ML model train-
frames. Since reliability and low latency are conflicting ing/inference.
requirements, there is always a trade-off between them. • Network Sensing: This use case aims to expand the
Note that this use case can be seen as an extension of 5G capabilities of cellular networks to sensing and position-
URLLC. ing. Example applications include object identification,
• Ultra-Massive Communications: This use case aims to shape recognition, activity detection, range estimation,
support an ultra-massive number of different types of velocity evaluation, and movement tracking. This use
devices in diverse application scenarios. The range of case is enabled by the integration of communication and
devices is wide, including IoT sensors, devices, wear- sensing.
ables, machines, robots, vehicles, drones, etc. Application • Network Energy: The aim of this use case is to support
scenarios vary from smart environments (e.g., cities, wireless energy transfer (WET) services to power net-
factories, hospitals, buildings, warehouses, etc.) to wide- work nodes, such as IoT sensors and low-power devices.
area IoT (e.g., environmental/industrial monitoring) and In particular, wireless energy services aim to advance the
low-power sensor networks. Due to versatile devices long life-time, low-complexity, autonomy, mobility, and
and applications, many performance dimensions need novel usages of low-energy networks. This use case can
to be considered, such as connection density, coverage, provide customized energy services to diverse vertical
mobility, capacity, and reliability. The key enablers for industries. Energy beamforming is a key technology to
massive connectivity include flexible spectrum operation, provide wireless energy capabilities.
fine-grained frame structure, massive grant-free network
access, robust transmission techniques, and efficient re- VI. M AIN P ERFORMANCE R EQUIREMENTS FOR 6G
source management. This use case is an extension of 5G
mMTC. In this section, the main performance requirements are
• Global-Scale Communications: The goal of the use case discussed for 6G. In November 2023, ITU-R introduced 15
is to provide worldwide super-coverage, including remote performance capabilities for IMT-2030 in Recommendation
areas on the land, at the sea, and in the air. This use ITU-R M.2160-0, i.e., ”IMT-2030 Framework” [36]. The
case supports diverse global-level application areas, in- numerical target values were defined for nine of them. In the
cluding remote mobile internet, global IoT, environmental following, we review these target requirements and compare
monitoring, industrial tracking, and maritime/aerial com- them to those of IMT-2020 described in Recommendation
munications, to mention a few. Aligned with the United ITU-R M.2083-0 [11]. In addition, we present some typical
Nations Sustainable Development Goals, digital divide values proposed in the 6G literature (see [88], and the ref-
may be alleviated by providing decent-quality communi- erences therein). The target requirements are summarized in
cations to remote and developing areas around the world. Table II. At the end of this section, we briefly list the rest
Global coverage is enabled by integrated terrestrial and of the IMT-2030 capabilities identified by ITU-R. Note that
non-terrestrial networks that exploit satellite, aerial, and ITU-R has not defined any target values for these capabilities
mobile communications. since most of them are difficult to measure numerically.
• Hyper-Mobility Communications: This use case is • Peak Data Rate: The peak data rate is defined as the
meant to support communications at high velocities, even maximum achievable rate when allocating all available
up to 500–1000 km/h. Example application scenarios radio resources to a single link and assuming ideal
are high-velocity transportation systems, such as high- conditions. In IMT-2020, the target peak rate is 20 Gbit/s
speed trains. The main enablers include flexible operation for downlink transmission. The target values of ITU-R
within a suitable spectrum range, fast handovers, and for IMT-2030 are 50, 100, and 200 Gbit/s, depending on
enhanced mobility management techniques. In general, the usage scenario. In the literature, the most common
lower frequencies are better for higher-mobility scenarios target rate for 6G is 1 Tbit/s.
due to their wider coverage and less frequent handovers. • User Experienced Data Rate: The user experienced data
rate refers to the achievable rate which can be obtained
by 95 % of the users in the coverage area (i.e., the 5 %
B. Beyond-Communication-Oriented Use Cases
point of the cumulative distribution function of the user
Since 6G is expected to extend its capabilities beyond throughput). The target value of IMT-2020 is 100 Mbit/s,
communication, we introduce three corresponding use cases whereas ITU-R suggests 300 and 500 Mbit/s for IMT-
to cover the network-enabled intelligence, sensing, and energy 2030. Greater values can be explored as well. Typically
dimensions. proposed values in the 6G literature are 1 and 10 Gbit/s.
• Network Intelligence: The target of this use case • Peak Spectral Efficiency: The peak spectral efficiency
is to provide AI/ML-assisted intelligent network ser- represents the maximum achievable user throughput per
vices and applications, such as intelligence as a ser- unit bandwidth. For IMT-2030, ITU-R proposes 1.5/3
vice, network-assisted intelligent systems (industry, trans- times higher spectral efficiency than that of IMT-2020.
portation, health, etc), computation offloading, and edge Greater values may also be studied. In the 6G literature,
 21

TABLE II
M AIN PERFORMANCE REQUIREMENTS FOR 6G

Performance Requirements IMT-2020 (ITU-R) IMT-2030 (ITU-R) 6G (Literature)

Peak Data Rate 20 Gbit/s 50/100/200 Gbit/s 1 Tbit/s

User Experienced Data Rate 100 Mbit/s 300/500 Mbit/s 1/10 Gbit/s

Peak Spectral Efficiency 1X 1.5X/3X 2X–3X

Area Traffic Capacity 10 Mbit/s/m2 30/50 Mbit/s/m2 1/10 Gbit/s/m2

Latency Latency 1 ms 0.1–1 ms 0.1 ms

Reliability 1-10-5 1-10-5 –1-10-7 1-10-7 –1-10-9

Connection Density 106 /km2 106 –108 /km2 107 –108 /km2

Mobility 500 km/h 500–1000 km/h 1000 km/h

Positioning Accuracy ND 1–10 cm 0.1–10 cm

typical targets are 2–3 times higher (i.e., 60–90 bit/s/Hz) • Mobility: Mobility is the highest device velocity sup-
than that of 5G (i.e., 30 bit/s/Hz). ported by the network for a communication link of a
• Area Traffic Capacity: The area traffic capacity is certain quality. The maximum mobility in IMT-2020 is
defined as the total aggregated throughput per unit area. 500 km/h, whereas ITU-R recommends 500–1000 km/h
Compared to IMT-2020’s 10 Mbit/s/m2 , ITU-R recom- for IMT-2030. The most common target value in the 6G
mends the values of 30 and 50 Mbit/s/m2 for IMT-2030, literature is 1000 km/h.
while greater values could also be examined. The values • Positioning Accuracy: The positioning accuracy is a
typically presented in the 6G literature are much higher quantifiable value that represents the difference between
than those of ITU-R, i.e., 1 and 10 Gbit/s/m2 . the network-estimated location of the device and its real
• Latency: The user plane latency is the time spent by the location. There is no position accuracy target defined for
network from sending a packet to receiving it, assuming IMT-2020. ITU-R suggests that the positioning accuracy
unloaded conditions. IMT-2020’s latency requirement is could range from 1 to 10 cm. In the 6G literature, the
1 ms. According to ITU-R, the target values could range proposed targets range from millimeter to centimeter
from 0.1 to 1 ms for IMT-2030. The target of 0.1 ms is levels.
typical in the 6G literature. The remaining six IMT-2030 capabilities include coverage,
• Reliability: Reliability is defined as the success proba- sustainability, interoperability, security and resilience, sensing-
bility of a packet transmission within the required time. related capabilities, and applicable AI-related capabilities.
The reliability requirement of IMT-2020 is 1-10-5 . While Further details on these capabilities can be found in [36].
ITU-R suggests that the success probabilities could be
in the range of 1-10-5 –1-10-7 for IMT-2030, the values VII. AI/ML FOR 6G
from 1-10-7 up to 1-10-9 have been proposed in the 6G AI/ML is expected to play a revolutionary role in 6G
literature. networks. The extensive use of AI/ML can fundamentally
• Connection Density: The connection density is defined change the way how mobile networks are designed, operated,
as the total number of devices that can be served with and managed. In this section, we provide a brief introduction
a certain quality per unit area. For IMT-2030, ITU-R to the fundamentals of AI/ML and review three promising ML
proposes 106 –108 /km2 connection densities which are methods for 6G.
1–100 times higher than that of IMT-2020. In the 6G
literature, commonly suggested densities are 107 /km2 – A. Introduction to AI and ML
108 /km2 . A volumetric-based measure has also been In the following, the concepts of AI and ML are introduced,
proposed in the literature, with a typical value of 100/m3 . focusing on their past, present, and future. Furthermore, the
main types of learning and training are described.
 22

1) Artificial Intelligence: AI can be seen as a process in of research on neural networks, connectionism learning began
which a computer program performs functions that are con- to dominate in the 2000s in the form of DL, which is
sidered intelligent from a human perspective, such as planning, typically realized through multi-layered neural networks [176].
learning, reasoning, and decision making, in order to perform DL showed excellent performance in many problem settings
a specific task. Consequently, AI can make different types of when the training datasets were sufficiently large. DL became
objects and entities intelligent, such as software applications, popular due to advances in computational power and the rise
devices, and systems. The research field of AI is considered of big data technology [176]. Currently, DL is the dominant
to be born in 1956, when the term AI was first introduced by AI technology used in research and applications. ML is widely
the organizers of the first AI event at the Dartmouth College used in the modern society, benefiting diverse verticals, such
in the US [172]. This AI workshop was based on the idea that as technology industry, healthcare, manufacturing, economics,
any feature of intelligence can, in principle, be simulated by a marketing, security, and agriculture. ML is constantly expand-
machine. Since the late 1950s, AI has been actively researched ing its frontiers and integrating deeper into devices, systems,
with constant progress, except for a few skeptical periods in and applications. Further details on the past, present, and
the late 1970s and between the late 1980s and the early 1990s future of ML can be found in [176].
[172]. Over the years, typical research areas were computer 3) Main Types of ML: There are three main types of
board games, natural-language processing, and robotics. ML algorithms: supervised, unsupervised, and reinforcement
The potential of AI was recognized early on, but with unre- learning [173].
alistic optimism in practical implementations. After decades of • Supervised Learning: Supervised learning aims at find-
great expectations, the use of AI finally boomed in the 2010s. ing a mapping between inputs and outputs by analyzing
This was due to advances in key areas, such as computer labelled training data containing input-output pairs [173].
technology, ML, and big data. Since the 2010s, the world’s Typical tasks for supervised learning are classification and
top technology companies have invested heavily in AI. A regression [173]. In communication, supervised learning
detailed history of AI is presented in [172]. Today, AI is is promising for detection and prediction.
used everywhere. Through a vast variety of applications, AI • Unsupervised Learning: In unsupervised learning, the
has penetrated deeper into the different levels of modern training data are unlabelled and contain only inputs,
society. Typical applications include Internet search engines, without any indication of the desired outputs [173]. The
recommendation systems, online advertising, social media, goal of unsupervised learning is to recognize patterns
entertainment, gaming, voice assistants, smart phones, smart behind data generation. Unsupervised learning is typically
home devices/appliances, online food delivery, electric scooter applied to density estimation, clustering, feature extrac-
services, assisted/self-driving cars, drones, robots, etc. In the tion, and dimensionality reduction [173]. In communi-
future, the use of AI will significantly increase in all areas of cation, unsupervised learning is particularly suitable for
life and society. problems related to compressing and clustering.
2) Machine Learning: ML can be seen as a process in • Reinforcement Learning: Unlike the other two methods,
which a computer program learns from training data to per- reinforcement learning dynamically interacts with the op-
form a specific task to which the program is not explicitly erating environment by receiving feedback (i.e., a reward)
programmed. In other words, ML transforms experience into after choosing an output (i.e., an action) for a given input
expertise. ML is a key tool to realize AI functions [173], (i.e., an observation) [173]. Feedback provides informa-
currently dominating in AI research and applications. ML al- tion on how well the chosen action satisfies the prede-
gorithms learn through training. More training results in better fined targets of the learning algorithm. Reinforcement
performance. In general, (data-based) ML is a preferable solu- learning is particularly suitable for problems involving
tion over conventional (model-based) mathematical methods to sequential decision making [173]. In communications,
problems where there exist a model or algorithm deficit [173]. reinforcement learning naturally lends itself to resource
A model deficit refers to the non-existence of a mathematical allocation problems.
model for the problem at hand. In the case of an algorithm
deficit, a mathematical model is available, but the problem is 4) Main Types of Training: In ML, there are two main types
too complicated to be solved using conventional mathematical of training: offline and online [177].
algorithms. It is worth mentioning that for some multi-phase • Offline Learning: Offline learning refers to a learning
problems, it may be preferable to use a combination of model- process executed over the entire training dataset before
and data-based approaches [174]. the corresponding ML algorithm is taken into action to
As a technological term, ML was first introduced in 1959 in solve the problems at hand [177]. Offline learning is cost-
the context of a computer trained to play the game of checkers inefficient and poorly scalable for large-scale real-world
[175]. However, it was until the 1990s when ML started to applications that change (rapidly) over time and space
bloom. Until then, the dominant methods in AI research were due to the massive and expensive (re-)training processes
based on reasoning (from the 1950s to the early 1970s) and [177].
knowledge (from the mid-1970s to the early 1990s) concepts, • Online Learning: Online learning refers to an incremen-
such as inductive logical programming and expert systems, tal learning process, in which the training data instances
respectively [176]. In the mid-1990s, statistical learning, such appear in a sequential order, and the learner is updated
as kernel methods, became mainstream [176]. After decades one by one [177]. Online learning is particularly suitable
 23

TABLE III
S UMMARY OF ML METHODS FOR 6G

ML methods Vision Description Opportunities Challenges

Deep Learning Multi-layer artificial neural

Key ML method for 6G Excellent performance Lots of training
networks

Federated Learning Reduced latency & Efficiency & scalability &

Distributed ML for 6G Local learning at devices
enhanced privacy asynchronous nature

Transfer Learning Enhanced ML training for knowledge transfer from Reduced training and
Negative transfer
6G source to target learner computation

for real-world applications under rapidly changing con- convolutional neural networks, recurrent neural networks, gen-
ditions [177]. Compared to offline learning, online learn- erative adversarial networks, deep neural networks, and deep
ing requires fewer computation and storage resources, belief networks [178]. DL can be applied according to the
is faster and cheaper to implement, and can instantly supervised, unsupervised, or reinforcement learning principles.
adapt to varying conditions. However, online learning is DL has proven to be an efficient and accurate method if the
challenging and may face efficiency and robustness issues available training datasets are sufficiently large [178].
in practice due to the poor quality of the training data Generally, DL is applicable to diverse engineering problems.
[177]. In the context of wireless networks, DL is well-suited to
many types of communication problems [178]–[182], such
DL as network resource management, network access, data traf-
fic prediction, routing, user scheduling, resource allocation,
channel estimation, and signal detection. DL is a particularly
promising technology for 6G networks since it fits well
(POWERFUL) for diverse 6G-specific challenges at different levels of the
network [183]–[186]. Such challenges are related to space-air-
ground integration, cell-free network design, network slicing,
network security, edge caching, joint communication and
6G ML
sensing, massive MIMO, RISs, etc. Although DL algorithms
have been extensively studied, there are still many challenges
to be solved to satisfy the stringent 6G requirements. DL has
been reviewed for wireless networks and 6G in [178]–[182],
(LIGHT) (DISTRIBUTED) [187] and [183]–[186], [188], [189], respectively.
2) Federated Learning: FL is a distributed ML method,
TL FL
in which each involved edge device trains its local learning
Fig. 10. Key ML methods for 6G. model based on local data at the device itself and sends only
the resulting model parameters, instead of raw data samples,
to a centralized server/cloud, updating the aggregated global
B. Key ML Methods for 6G learning model and broadcasting the updated parameters back
In this section, we discuss three ML methods that can pro- to the edge devices [190]–[192]. This process is repeated until
vide diverse benefits to 6G networks. These methods include the desired level of convergence is achieved. A distributed FL
DL, federated learning (FL), and transfer learning (TL), as process can also be performed without a central server by
illustrated in Figure 10. The opportunities and challenges of sharing the local parameters among the involved edge devices
these methods are summarized in Table III. [192]. Due to its distributed nature, FL provides potential ben-
1) Deep Learning: DL is a popular sub-class of ML, efits compared with centralized ML methods, including saved
exploiting multi-layer artificial neural networks that loosely wireless resources, reduced latency, and enhanced privacy
mimic the function of a biological brain [178]. Each layer [192]. Since only model parameters (not extensive training
consists of connected nodes (i.e., artificial neurons) with non- data) are communicated between the edge devices and the cen-
linear processing capabilities [178]. DL can solve complex tralized server, the amount of exchanged data is significantly
problems by transforming, progressively layer-by-layer, the reduced, leading to the possible savings of communication
raw input data into a higher-level representation, according resources. The FL process with local training at each device
to the objective of the given problem, through the non- and global updating at the parameter server may reduce latency
linear processing of the nodes [178]. Numerous artificial since the computational complexity of such algorithms is much
neural network architectures have been developed to solve lower than that of the centralized algorithm, resulting in faster
different types of problems. A few classical networks include computation time and shorter computation delays. However,
 24

the distributed process is iterative, and thus, the possible in the wireless research community [206]. In this context,
latency reductions also depend on the speed of convergence. TL algorithms have been proposed to address specific issues
Protected privacy is inherent in FL since the device-specific in resource/spectrum management, energy-efficient design,
training data remain in the device itself. caching, sensing, localization, and security [206]. In particular,
FL can be applied to many common problems in wireless TL has been recognized as a promising ML method for 6G
networks, such as resource/spectrum management, resource to address emerging challenges in data collection by sharing
allocation, user behavior prediction, channel estimation, signal knowledge between different learning algorithms, potentially
detection, and security/privacy issues [190]–[193]. FL has also leading to more efficient training processes, improved learning
been proposed to assist in diverse emerging technologies, such performance, mitigated signaling overhead, and enhanced data
as RISs, non-orthogonal multiple access (NOMA), integrated privacy [206]–[208]. In the context of 6G, advanced types of
terrestrial and non-terrestrial networks, edge caching, vehic- TL are of special interest, including DTL, FTL, and online TL.
ular networks, etc [192]–[194]. Although FL is applicable to Further research is required to realize practical TL algorithms
numerous functions in future mobile networks, there are still that address the special features, requirements, and application
many fundamental challenges to be addressed before practical scenarios of 6G. TL has been comprehensively reviewed for
realizations. Typical challenges are related to communication generic purposes, wireless networks, and 6G in [205], [206],
overhead, asynchronous communication, learning efficiency, and [207], respectively.
joint communication and computation design, resource allo-
cation, scalability, network heterogeneity, and security/privacy 6G TECHNOLOGIES
[190]–[195]. In the context of 6G, FL is a promising ML
SPECTRUM ANTENNA
method to enable distributed and privacy-preserving learning.
However, the research and development work of mobile FL
is still at a rather early stage, requiring extensive efforts in
academia and industry in the near future. Recent survey papers THz OWC mMIMO RIS HMIMO
have reviewed FL in terms of 6G [191], [192], [194], [196]–
[198], wireless/mobile networks [190], [193], [195], [199]– TRANSMISSION ARCHITECTURE
[201], and IoT [202]–[204].
3) Transfer Learning: TL is a branch of ML, which objec-
tive is to transfer knowledge from source domains to target
learning processes at target domains to enhance the quantity MULTI- MODCOD NOMA GFMA INTNs UDNs IAB CF-
WAVE mMIMO
and quality of training data, reduce the computational demands
of training processes, and improve the speed, accuracy, and INTELLIGENCE BEYOND-COMMUNICATION
robustness of target learners [205], [206]. In other words,
less training data needs to be collected to implement efficient
learning algorithms with improved performance and reduced
CORE EDGE AIR i3C ISAC WET
demands [205]. Since the collection of adequate training data
is often time-consuming, costly, or sometimes infeasible, TL
saves time and expenses, or even enables the use of ML in ENERGY-AWARE END-DEVICE
otherwise impractical situations [205]. To attain the aforemen-
tioned benefits, the challenge is to find proper source domains
to transfer useful knowledge instead of harmful one (i.e., GREEN RF-EH BACK D2D V2X C-UAVs
negative transfer [205]), which may lead to poor performance NETS SCATTER

of the TL algorithms. More precisely, source domains should

SERVICE SECURITY
be sufficiently related/similar to target domains to avoid the
pitfall of transferring knowledge that has a negative impact on
the target learners. In general, there are three main challenges
in TL: what, when, and how to transfer [206]. Based on these PRIVATE HOLISTIC
NETS SECURITY
challenges, TL can be categorized in four groups, including
feature-, parameter-, relational-, and instance-based [205]. TL Fig. 11. Potential technologies for 6G.
can also be classified into three categories based on the
problem perspective: inductive, transductive, and unsupervised
[206]. TL can be combined with other ML methods, such as VIII. P OTENTIAL T ECHNOLOGIES FOR 6G
DL (i.e., deep transfer learning (DTL)) and FL (i.e., federated Since 6G will be a largely complex and heterogeneous
transfer learning (FTL)) [206], [207]. entity, there needs to be a comprehensive set of technological
Due to its benefits, TL has gained popularity in the field elements upon which such a network can be built. In this
of ML. There are diverse application scenarios for TL, section, we identify and review 27 potential 6G technologies
such as recommendation systems, bioinformatics, healthcare, in 10 different technological categories. These technologies
transportation, computer vision, computing, and communi- and categories are introduced in Figure 11. For clarity, each
cations [205]. Recently, TL has attracted increasing interest technology is introduced using the same template: vision,
 25

TABLE IV
S UMMARY OF SPECTRUM - LEVEL TECHNOLOGIES FOR 6G

Spectrum-Level
Technologies Vision Description Opportunities Challenges Past Present

THz Extreme capacity Operation at Propagation losses Research since

Massive spectrum & HW impairm 5G mmWave
Communications for 6G 0.1-10 THz band early 2010s

IR 0.3-400 THz
Complementary & VLC 400-750 Enormous Research since
Optical Wireless Blocked easily & Commercial FSO
access and THz & UV spectrum & 2000s (VLC) &
Communications reliability issues Expermental VLC
backhaul for 6G 0.75-30 PHz low-cost 1960s (FSO)

introduction, past and present, opportunities and challenges, 1) THz Communications:

literature and future directions. In the vision part, we envision
briefly what is the expected role of that particular technology • Vision: Due to massive amount of spectrum available at
in 6G. In the introduction, the description and basic principles THz frequencies, THz communication has been identified
of the technology are discussed, along with the main bene- as one of the key enabling technologies to fulfill the
fits, shortcomings, and application scenarios. In the past and extreme capacity requirements of 6G. The THz spectrum
present part, we provide a brief introduction to the background is also seen as a key enabler for beyond-communication
and current status of the technology. Then, we discuss the technologies, such as high-accuracy sensing and localiza-
opportunities that the technology is expected to offer and the tion.
main challenges on the road. In the final part, we review recent • Introduction: THz communication refers to the operation
survey papers in the literature and discuss future research at THz frequencies, ranging from 0.1 to 10 THz [209].
directions. THz spectrum, in relation to the cm- and mmWave
bands, is illustrated in Figure 12. THz communication can
achieve extremely high data rates because of the massive
A. Spectrum-Level Technologies for 6G
spectrum available in the THz band [209]. However,
To fulfill the demanding performance, service, and applica- the communication ranges are short since propagation
tion requirements of 6G, it is vital to support a massive fre- losses are high at the THz spectrum [210]. Due to
quency range from sub-6 GHz and centimeter wave (cmWave) the aforementioned properties, THz communication is
to mmWave and THz bands. At the cost of smaller system applicable to data-hungry and close-proximity network
bandwidths, lower carrier frequencies with favorable propa- scenarios. Other potential application scenarios range
gation characteristics are preferable for wider coverage and from nano- to space-scale communications and from
higher mobility scenarios, such as rural areas, wide-area IoT, sensing to localization [209].
and high-mobility systems. At the cost of harsher propagation • Past and Present: In the literature, THz research on
conditions, higher frequencies with larger bandwidths enable mobile networks started to gain increasing interest around
higher capacity and throughput in denser network scenarios, the mid-2010s [211]. However, back then, the main focus
such as hotspot, urban, and sub-urban areas. In this picture, of higher frequency research was on mmWave communi-
THz communication is seen as a promising technology to cation for 5G. Since 5G, with mmWave operation as a key
achieve extremely high data rates. In addition, optical wire- technology, was launched in the late 2010s, the worldwide
less communication (OWC) is a potential candidate to offer research focus was shifted to THz communications for
complementary frequency resources for special scenarios, such 6G. Currently, academia is extensively studying THz
as short-range indoor access and long-range outdoor backhaul communication from a wide range of perspectives, from
links. These two technologies are summarized in Table IV and theoretical aspects and channel modeling to transceiver
discussed in detail below. designs, assisting technologies, and performance evalua-
cmWave THz tions [209]. In addition, cooperation between academia
and industry is narrowing the gap between theory and
practice, producing fruitful ideas and leading to novel
3 GHz 30 GHz 100 GHz 300 GHz 10 THz designs and demonstrations.
In the industry, the focus is on practical implementa-
tions, prototyping, and trialing. For example, Samsung,
mmWave
LG, Nokia, and Keysight Technologies have showcased
successful THz communications at frequencies above 100
Fig. 12. cmWave, mmWave, and THz spectrum bands. GHz [19]. In 2021, Samsung demonstrated THz com-
munication at a 140 GHz carrier frequency with 2 GHz
 26

bandwidth, achieving a data rate of 6.2 Gbit/s over a 50- massive MIMO can be used for high-accuracy sensing
feet distance. In 2022, LG Electronics performed a trial and localization, enabling services beyond communica-
with a successful THz outdoor link over a distance of 320 tion. THz communication can be applied in numerous
meters, operating at a frequency range of 155-175 GHz. scenarios, such as data-hungry applications (holographic
In 2023, Nokia, with NTT and NTT Docomo, showcased telepresence, wireless XR, information showers), close-
a data rate of 25 Gbit/s via THz communication at a proximity communications (D2D, intra-device connectiv-
144 GHz operating frequency. Also in 2023, Keysight ity), integrated communication, sensing, localization, and
Technologies, along with its partners, obtained over a 100 imaging (object/gesture recognition, health monitoring,
Gbit/s data rate at a 300 GHz carrier frequency. air quality detection, object scanning, dark vision), wire-
In the spectrum regulatory domain, WRC 2019 defined less backhaul/fronthaul (IAB), satellite communications,
the conditions for the use of a spectrum ranging from 275 and nano-scale communications (nano-networks) [209].
to 450 GHz by land mobile and fixed services [212]. As a There are many challenges in integrating THz commu-
result, there is currently a spectrum of 160 GHz for THz nication as a key part of 6G networks and freeing its
communications, with no specific conditions to protect great potential. The main challenges include high propa-
Earth exploration satellite services. Further spectrum poli- gation losses (spreading and molecular absorption losses),
cies for THz communications will be defined in the future easy blockages, severe hardware impairments (oscillator
WRCs. In the standardization domain, IEEE specified phase noise and RF non-linearity), and complex hardware
the first standard (IEEE Std. 802.15.3d-2017) for fixed design (signal generation and detection) [214]. Due to
wireless point-to-point THz communications at 252-321 the high molecular absorption loss (especially above 800
GHz frequencies, with target applications of wireless GHz), there are large chunks of spectrum in the THz
backhaul/fronthaul, wireless links in data centers, kiosk band that may be unsuitable for mobile communications
downloading, and intra-device communications [213]. [214]. Other parts of the spectrum, where attenuation is
Although there are no standards for mobile THz commu- tolerable, are called transmission windows and considered
nications, IEEE Std. 802.15.3d-2017 will pave the way more preferable for 6G purposes [214]. There are massive
toward 6G THz standardization. In 2021, the IEEE Com- amounts of spectrum in these windows, ranging from tens
munications Society’s Radio Communications Committee to even hundreds of GHz.
established a special interest group on THz communica- In general, high propagation losses at THz frequencies,
tions to advance research, development, and standardiza- especially along with low transmission powers, lead to
tion activities toward 6G and beyond [209]. In the existing short communication distances, which is a major draw-
mobile networks, 5G is the first generation that operates at back in the context of mobile networks [210]. This
frequencies higher than 6 GHz. Specifically, 5G supports calls for ultra-dense cell deployments. In addition, a
mmWave communications at two frequency ranges, i.e., potential solution to this so-called distance problem is
FR2-1: 24.5-52.6 GHz (Release 15 [1]) and FR2-2: 52.7- to use ultra-massive MIMO beamforming to combat
71 GHz (Release 17 [17]). 6G will continue this trend by harsh propagation conditions by high array gains [210].
going beyond 100 GHz, becoming the first generation to In theory, ideal beamforming gains can compensate or
enter THz frequencies. even overcome free-space pathloss at higher frequencies
• Opportunities and Challenges: The main goal of THz [215]. In practice, however, accurate beamforming is very
communication is to provide extremely high data rates difficult at THz frequencies. For very narrow THz beams,
and capacities at the link and system levels by exploiting even a slight misalignment can significantly degrade
the massive spectrum available at THz frequencies. Un- link performance. Thus, beam misalignment is a major
locking the potential of the THz spectrum opens many problem in THz ultra-massive MIMO communications.
opportunities for 6G. In particular, a massive spectrum Cell and device discovery is also challenging. To some
is the key in achieving one of the main 6G targets of 1 extent, the lessons learned from mmWave research can
Tbit/s peak rate, which in turn enables new revolutionary be used in THz studies. For example, lower frequencies
applications, such as holographic-type communication with favorable propagation characteristics can be used for
and wireless XR [209]. To provide extreme system- initial access.
level capacity in hotspot areas, ultra-dense THz cell A major challenge is how to handle hardware impair-
deployments come into play. In addition to ultra-high data ments, such as phase noise and power amplifier non-
rates, operation at the THz spectrum can provide many linearity, as they become more severe at higher frequen-
other benefits, such as decreased latency, improved PHY cies. To a certain extent, a wider SCS can alleviate hard-
layer security, close-proximity connectivity, and beyond- ware impairments in multi-carrier-based systems. Another
communication services [209]. solution is to employ single-carrier waveforms for the
Due to the larger bandwidths, the frame duration is operation at very high frequencies since they are more ro-
shorter, leading to decreased latency. Since THz signals bust against phase noise and other hardware impairments
propagate relatively short distances, they are more diffi- [216]. In terms of transceiver hardware, signal genera-
cult to eavesdrop or attack. THz communication naturally tion and detection are particularly challenging for THz
lends itself to close-proximity connectivity due to its short communications [210], and novel solutions are required
coverage. Due to the very narrow beams, THz ultra- for cost-, power-, and energy-efficient communications.
 27

As THz communication is prone to blockages, a possible network layers.

solution is to utilize RIS technology, which can reflect the The article in [209] examined THz research advance-
transmitted signals to bypass blockages [217], [218]. With ments over the last decade and presented future directions
controlled reflections, RISs can also be used to alleviate for the next decade, covering topics from devices, chan-
the distance problem by extending the coverage of THz nels, and communications to networking and experiments.
communications [217], [218]. In [234], THz-band ISAC was reviewed. The focus was
• Literature and Future Directions: In the literature, THz on the antenna array design, hybrid beamforming, RISs,
mobile communication has been actively studied since and ML. The work [236] considered AI/ML-assisted
the mid-2010s, and it has been one of the major 6G THz communications. In [237], the authors focused on
topics since the late 2010s. The THz literature covers near-field communications at THz frequencies for 6G. In
a broad range of topics, such as device technologies, [238], a thorough survey was provided on THz commu-
channel modeling, communication designs, networking nication and sensing toward 6G and beyond. The paper
aspects, application scenarios, regulation/standardization, [239] discussed THz channel propagation, measurements,
and experiments [209]. The latest THz research has been and modeling for 6G. The authors in [240] reviewed the
comprehensively reviewed in numerous studies [209], PHY layer aspects of THz ISAC. THz/mmWave beam
[210], [213], [214], [217]–[241]. management was investigated in [241].
In [219], a survey was conducted on THz communi- There are still many open problems to be addressed in
cations, reviewing key transceiver technologies, system future research toward efficient THz communications and
designs, applications, and challenges. The work in [214] networking in the 6G era. At a high level, the main
provided a comprehensive study on wireless communica- future topics can be divided into different categories, such
tions above 100 GHz, with the main focus on THz appli- as fundamentals, device technology, channel modeling,
cations, transceiver architectures, beamforming designs, communication designs, networking, and experiments. As
and channel properties toward 6G and beyond. In [220], discussed in the aforementioned surveys, the key areas
a short survey discussed the significance, standardization, that need further research include overcoming the dis-
scenarios, applications, and open problems of THz com- tance problem (ultra-massive MIMO, RISs, UDNs), close
munications in the context of beyond 5G networks. THz proximity scenarios and applications (D2D, machine-
communication systems were reviewed in [221] from to-machine (M2M), vehicle-to-vehicle (V2V)), suitable
the perspective of signal generation, channel modeling, THz spectrum bands for 6G, alleviating hardware im-
contender technologies, applications, standardization, and pairments (multi-waveform design), efficient transceiver
future directions. design (electronic/photonic transceivers, signal genera-
In [222], the THz band was considered for sensing, tion/detection, RF design), integrated THz communica-
imaging, and localization applications, especially in the tion and sensing, and practical channel and simulation
context of 6G use cases. THz ultra-massive MIMO was models (realistic link- and system-level performance eval-
comprehensively examined in [210] and [227]. Standard- uation).
ization for sub-THz communications in IEEE 802.15.3d For THz ultra-massive MIMO, the essential research di-
was discussed in [213]. 6G THz networks were stud- rection is to develop accurate beamforming and practical
ied from the full-communication stack perspective in initial access methods. In the RIS domain, it is important
[223], addressing link- and system-level challenges. RIS- to study coverage extension and blockage avoidance to
assisted THz communication was explored for 6G net- alleviate the distance and blockage problems. To achieve
works in [217], [218], [235]. In [224], a tutorial was extreme capacities at the system level, an ultra-dense
provided on signal processing techniques for THz com- network design needs to be further studied with extra-
munications, with an emphasis on ultra-massive MIMO small THz cell deployments. More research is required to
and RIS systems. provide support for a wide range of close-proximity ser-
In [225], key technologies for 6G THz communications vices and applications. In particular, THz-enabled D2D-
were reviewed, considering channel modeling, multi- type connections are essential for the success of IoT, IoV,
beam antennas, front-end chip design, baseband signal and the Internet of UAVs (IoU). To meet 6G performance
processing, and resource management. The authors of expectations, it is crucial to find and study the most
[226] discussed THz communications for the 6G era in suitable THz frequency bands for mobile networks.
terms of ISAC, ultra-massive MIMO, RISs, and ML. In Flexible multi-waveform design is a promising approach
[228], seven defining features of THz communications to alleviate hardware impairments by utilizing single-
were examined, i.e., quasi-opticality of the THz band, carrier waveform at higher THz frequencies and pro-
THz wireless architectures, synergy with lower frequency viding flexible spectrum use at lower frequencies via
bands, ISAC, PHY layer designs, spectrum access, and multi-carrier technology. Major efforts are required for
real-time network optimization. THz channel characteris- practical THz transceiver design, particularly in terms
tics, modeling, and measurements were surveyed for 6G of electronic vs. photonic components, signal generation
in [230], [232], [233]. 6G THz precoding was discussed and detection, and RF/antenna designs. An important
in [229]. In [231], THz communication was explored for future research avenue is to use THz communication to
6G and beyond from the aspects of physical, link, and aid accurate localization and sensing. For realistic link-
 28

and system-level performance evaluations, more practical and Petabit/s-level rates over multiple meters for short-
channel and simulation models need to be designed. range links [249]. In practice, commercial FSO systems
Further information on the required THz research for the are capable of transmitting data at tens of Gbit/s rates over
next decade can be found in [209]. link distances of several kilometers [249], [250]. Despite
the promising experiments and decades of research, the
RF X-RAY commercial use of terrestrial FSO systems is still rather
••• •••
limited due to their poor link reliability in practice. State-
IR VL UV
of-the-art research has been focusing on finding practical
solutions to the major challenges, ranging from atmo-
0.3 THz 400 THz 750 THz 30 PHz spheric turbulence and attenuation to beam divergence
Fig. 13. Optical wireless spectrum. and pointing errors. Further details on the latest FSO
technologies and solutions can be found in recent surveys
[249], [251], [252].
2) Optical Wireless Communications: Early research of VLC dates back to the early 2000s
• Vision: OWC is considered as a potential technology [253]. However, it was until the 2010s that the real
to complement 6G networks in special communication interest in VLC started to rise [254]. Experiments have
scenarios, such as short-range indoor access and long- shown increasing data rates and communication distances
range outdoor backhauling. over the years, e.g., 1.1 Gbit/s/0.23 m (2012), 3.22
• Introduction: OWC refers to the operation at the optical Gbit/s/0.25 m (2013), 4 Gbit/s/0.2 m (2015), 5 Gbit/s/0.75
frequency bands, i.e., infrared (IR) (0.3-400 THz), visible m (2016), 15.73 Gbit/s/1.6 m (2019), 16.6 Gbit/s/2 m
light (VL) (400-750 THz), and ultraviolet (UV) (0.75-30 (2021), 24.25 Gbit/s/1.2 m (2021) for LED-based setups
petahertz (PHz)) [242]. A schematic illustration of optical [255], [256] and 4 Gbit/s/0.15 m (2015), 6 Gbit/s/0.15
wireless spectrum is shown in Figure 13. The main types m (2017), 20 Gbit/s/1 m (2018), 40 Gbit/s/2 m (2019),
of OWC are VLC, utilizing the visible light spectrum and 46.4 Gbit/s/0.3 m (2021) for laser diode (LD)-based
[243], and free-space optical (FSO), usually operating setups [257]. By 2022, the longest transmission distances
at infrared frequencies [244]. VLC is mostly applicable for the multi-Gbit/s LED and LD VLC systems were
to short-range indoor scenarios, exploiting light-emitting 20 and 100 meters, achieving 2.12 and 6 Gbit/s data
diodes (LEDs) and laser diodes (LDs), whereas FSO rates, respectively. The latest details on LED and LD
is commonly used for short- and long-range point-to- technologies and experiments can be found in [256] and
point communications, relying on laser links. Other OWC [257], respectively.
technologies include light fidelity, light detection and In 2011, the OWC standard IEEE 802.15.7 was published,
ranging, and optical camera communications [242]. In including short-range VLC with PHY/MAC layer func-
the following, the main focus is on VLC and FSO, as tionalities. The standard was revised in 2018, expanding
they are the most promising candidates to complement the operating frequency range and including new OWC
6G networks. technologies. In 2023, the standard IEEE 802.15.13 was
• Past and Present: While fire, smoke, and other an- released for multi-Gbit/s OWC, with stationary and mo-
cient types of visible signaling methods can be seen as bile devices and link distances up to 200 m.
the ancestors of OWC, the first experiment was con- • Opportunities and Challenges: OWC has great po-
ducted in 1880, when Alexander Graham Bell transmitted tential due to its enormous unregulated spectrum, large
voice over 213 meters by modulating sunlight using his bandwidths, low implementation cost and complexity,
patented photophone device [245]. In the modern era, the high energy efficiency, ultra-low latency, robustness to
earliest demonstrations of terrestrial FSO date back to electromagnetic interference, high spatial reusability, and
the 1960s and 1970s [245]. For example, FSO LED and secure communication channels [252]. Due to massive
laser technologies were employed to transmit data over 48 bandwidths, OWC can provide ultra-high-speed com-
and 14 km long distances in 1962 and 1970, respectively munication for indoor and outdoor scenarios, with link
[245]. Multi-Gbit/s data rates were demonstrated in the distances ranging from nanometers to thousands of kilo-
late 1990s, whereas a record-breaking aggregated rate of meters [242]. License-free spectrum and low implemen-
40 Gbit/s was achieved over a distance of 4.4 km in 2000 tation costs result in economic benefits. Low energy con-
[246]. In 2008, the first Tbit/s-level FSO transmission sumption facilitates the design of green communication
was demonstrated for a link range of 212 meters [247]. systems. Immunity to RF interference allows ubiquitous
In 2018, 13.16 Tbit/s data rate was reported for a 10.45 usage and facilitates the network design. Since OWC does
km long FSO link [248]. not penetrate walls, its spatial reusability is high. The
For short-range FSO experiments, i.e., in the order PHY layer security of OWC links is inherently high due
of meters, multi-Tbit/s rates were shown in 2012. A to their locality and/or high directivity.
speed of 100 Tbit/s was achieved over a 1 meter link Given the aforementioned benefits, OWC is applicable
range in a laboratory experiment in 2014. State-of-the- to a wide range of scenarios, such as short-range cellu-
art demonstrations can support multi-Tbit/s rates over lar access, cellular backhaul links, hybrid radio-optical
multiple kilometers for long-range FSO communication networks, D2D/M2M/V2V communications, optical IoT,
 29

positioning and sensing, intra-device connections, on- Pointing errors can be mitigated by pointing the trans-
board communications, short-range indoor communica- mitter toward the receiver to obtain an LOS condition,
tions, long-range outdoor point-to-point communications, acquiring the transmitted signal at the receiving end by
space communications, underwater communications, and aligning the receiver in the direction of the beam, and
underground communications [242], [252], [258]. Dif- maintaining accurate pointing and acquisition via adap-
ferent OWC technologies have their own characteristics tive tracking with appropriate measurement and feedback
and the corresponding advantages which differ from mechanisms. Further details on pointing, acquisition, and
one to another. While VLC supports fast, low-cost, and tracking techniques can be found in [252]. Diversity
energy-efficient short-range communication in indoor en- methods aim to improve the link reliability by transmit-
vironments, FSO provides ultra-high-speed, highly di- ting multiple copies of the same information. Three main
rective, and low-cost long-range point-to-point outdoor diversity dimensions are time, frequency, and space. At
connectivity. Consequently, VLC and FSO are promising a high level, the objective of hybrid RF-FSO systems
technologies to complement 6G networks, with the main is to eliminate common disadvantages while exploiting
application scenarios being short-range indoor access and the benefits of both technologies. As discussed earlier,
long-range outdoor backhaul links, respectively. hybrid networks introduce many new challenges that must
There are many challenges to overcome before freeing the be tackled before successful deployment. Further details
potential of OWC and integrating it into future mobile regarding the challenges of hybrid RF-FSO systems are
networks as a complementary technology. Each OWC presented in [262].
technology has its own set of unique challenges. For • Literature and Future Directions: Recent survey papers
VLC, the main fundamental challenges include limited have reviewed the fundamentals, latest advances, open
communication range, easy blockage, ambient light inter- problems, and main literature of OWC [242], [259],
ference, line-of-sight (LOS) requirement, random receiver [263]–[271], VLC [243], [258], [260], [261], [272]–
orientation, uplink communication, mobility, and the non- [278], and FSO [244], [249], [251], [252], [262], [279]–
linearity of devices [243], [254], [258]. Hybrid RF-VLC [282]. The study in [242] presented a comparative
networks have been recognized as a promising solution to overview of OWC technologies by discussing classi-
tackle many of these challenges [259]–[261]. In general, fication, spectrum use, system architectures, potential
hybrid systems consist of two or more networks that can applications, and open issues. In [263], a comprehensive
be accessed in different ways based on the network and survey was conducted on OWC channel measurements
application types [259]. There are many possible access and models, focusing on indoor, outdoor, underground,
types, such as accessing the strongest network, accessing and underwater communication environments. The role of
both networks simultaneously, accessing one network for OWC for 5G/6G and IoT was discussed in [264]. In [259],
downlink and the other for uplink, access based on the the authors surveyed hybrid RF-optical networks. The pa-
quality of service (QoS) requirements, and access the per [265] presented a survey on OWC technologies, with
highest priority network and the other is backup [259]. the main focus on classification, enabling technologies,
The design of hybrid networks is highly complicated, link design, mitigation of impairments, security issues,
with many challenging tasks, such as network selection, and future challenges. The authors of [266] discussed a
network access, handover, load balancing, and resource roadmap for OWC research toward 6G deployments. The
allocation [259]. AI/ML is a promising tool to assist in work [267] provided a thorough survey of OWC for four
many of these complex tasks. For example, AI/ML can IoT domains: terrestrial, underwater, biomedical, and un-
be applied to resource management and traffic prediction derground. In [268], the security of OWC was considered.
problems. More details on the hybrid RF-VLC systems The survey [269] reviewed the latest advancements in
are available in [259]–[261]. OWC in the context of 6G and WiFi. In [270], the paper
Even though FSO is already commercially available, its focused on optical wireless and THz communications for
usage is rather limited due to poor link reliability. The 6G. The authors of [271] discussed the present and future
corresponding challenges range from atmospheric turbu- of OWC and FSO toward the 6G era.
lence and attenuation to beam divergence and pointing In [243], the authors provided a comprehensive review
errors [252]. Various weather conditions, such as rain, of VLC, covering the fundamentals, communication ar-
fog, smog, haze, dust, and snow, cause atmospheric chitectures, PHY/MAC layer designs, research platforms,
turbulence/attenuation, degrading the link performance applications, challenges, and future directions. In [258],
and reliability. Since point-to-point FSO links are based VLC was studied in the context of 6G. VLC PHY layer
on extremely narrow laser beams, beam divergence and security was discussed from the information-theoretic
pointing errors become a serious problem. Even a slight and signal processing perspectives in [272]. Vehicular
misalignment between the transmitter and receiver can VLC was explored in [273], reviewing state-of-the-art
significantly deteriorate link performance. To obtain high and identifying open problems. The article [274] sur-
link reliability, the mitigation of the aforementioned im- veyed the VLC system technology in terms of devices,
pairments is vital. Potential mitigation solutions include architectures, and applications. In [260], hybrid RF-VLC
pointing, acquisition, and tracking techniques, diversity systems were discussed from the perspectives of network
schemes, and hybrid RF-FSO systems [252]. topology, performance evaluation, potential applications,
 30

and future challenges. VLC was reviewed for IoT in optical networks were reviewed in [259]–[262].
[275]. The work [276] examined the design of federated In the category of emerging technologies, OWC is studied
learning-enabled VLC for 6G networks. In [261], the in combination with other emerging technologies, such as
authors focused on the access and applications of hybrid AI/ML and IRSs. Since AI/ML will be a key technology
VLC-RF systems. A thorough review of MIMO-VLC was in 6G, it is essential to study it for OWC systems as well,
provided in [277]. The tutorial in [278] discussed visible especially in the context of hybrid RF-optical networks.
light indoor positioning. With proper design, AI/ML can provide benefits to all
The paper [244] introduced a classification framework communication layers, from PHY to MAC and higher
for FSO links and systems. In [249], the authors dis- layers. The IRS technology is also expected to be an
cussed a research roadmap toward next-generation FSO integral part of 6G, promising diverse benefits from
from the perspective of system design. The work [279] coverage extensions and obstacle avoidance to energy-
studied FSO communication for indoor and outdoor and cost-efficient deployments. In the context of OWC,
application scenarios. In [251], FSO was reviewed in the optical IRS technology has been proposed for FSO
terms of single- and multi-beam systems, the effect of communication to relax the LOS requirement [280]. This
certain weather conditions, and the scalability of an FSO is an interesting topic for future research with practical
network. The paper [280] focused on intelligent reflect- benefits.
ing surface (IRS)-aided FSO communication systems. In the applications category, OWC research ranges from
In [252], a comprehensive survey was given on FSO nano- to space-scale communications. In particular, 6G-
communication, with the main emphasis on application relevant application scenarios for OWC include short-
scenarios, link reliability, mitigation methods, and multi- range indoor access, long-range outdoor backhauling,
user systems. The authors in [281] examined a field- D2D/V2V communications, hybrid RF-optical networks,
programmable gate array-based prototype for 6G long- optical IoT, localization/sensing, and satellite communi-
range FSO communication. The study [262] reviewed cations. The experiments category consists of demonstra-
hybrid FSO-RF systems in terms of switching methods, tions, trials, and prototyping. The results of these exper-
routing protocols, modulation schemes, research projects, iments are essential benchmarks in the evolution path of
applications, challenges, and potential solutions. In [282], OWC technologies from theory to practice, showcasing
a thorough survey of FSO systems was provided. the state-of-the-art performance usually in terms of data
In order to realize the potential of OWC, interdisciplinary rates and communication ranges. The latest experimental
research efforts and close cooperation between academia, results of VLC and FSO were reviewed in the previous
industry, and standardization bodies are needed. Based sections. In this category of research, an important future
on the review of the aforementioned survey papers, the direction is to perform more practical experiments and
future research directions of OWC can be divided into six customize them for 6G-specific application scenarios.
high-level categories, including fundamentals, channels, For VLC, a particular aim of future research is to
systems, emerging technologies, applications, and exper- tackle its fundamental problems, which range from short
iments. The primary research directions in the fundamen- communication distances and easy blockages to uplink
tals category are device technologies, transceiver designs, communication, ambient light interference, and mobil-
and PHY layer techniques. These are the core elements ity. A promising future research direction is to study
of OWC systems, thus requiring constant development. AI/ML-aided hybrid RF-VLC networks, as they can
A key direction for future research is to develop more alleviate these problems by efficiently switching be-
efficient devices, transceivers, and PHY layer designs, tween RF and VLC access. In particular, hybrid net-
especially in terms of spectrum, energy, and cost. works need to be considered for 6G-specific commu-
The research of OWC channels covers propagation char- nication and application characteristics and scenarios
acteristics, channel measurements, and channel modeling. (e.g., human/machine-centric, home/office/factory, pub-
These are the key elements in understanding OWC and lic/private, and IoT/IoV/IoU) since different environ-
providing proper tools for performance evaluation. In the ments have different opportunities and challenges. For
future, it is essential to develop realistic OWC channel example, blockages are more random and less pre-
models for 6G-specific application scenarios. Further dictable/controllable for human-centric communication in
details on the OWC channel modeling can be found in public networks than for machine-centric communication
[263], [283], [284]. In the systems category, OWC is con- in private networks. Further discussions on the future
sidered from a system-level perspective. While traditional research directions of hybrid RF-VLC networks can be
OWC research has mainly focused on individual links and found in [260], [261].
PHY layer techniques, system-level design has gained For FSO, the main aim of future research is to
increasing interest over the past decade. Since OWC improve link reliability by mitigating beam diver-
aims to complement future mobile networks, system- gence/pointing errors and fighting against atmospheric
level design with network management and higher-layer turbulence/attenuation. A particular research direction is
considerations is highly important. In this domain, a to study advanced mitigation methods, such as pointing,
particular future direction is to study hybrid RF-optical acquisition, and tracking techniques, diversity schemes,
networks, especially for VLC and FSO. Hybrid RF- and hybrid RF-FSO systems, in the 6G-relevant backhaul
 31

TABLE V
S UMMARY OF ANTENNA SYSTEM TECHNOLOGIES FOR 6G

Antenna System
Vision Description Opportunities Challenges Past Present
Technologies

Ultra-Massive 6G THz mMIMO Cost efficient mMIMO concept 5G mmWave

MIMO High BF gains
umMIMO extension design invented in 2010 mMIMO

Reconfigurable Controllable Electromagnetic Real-time control

Intelligent Energy efficient & Research since RIS prototypes
wireless metasurface & HW design &
Surfaces low-cost early 2010s and field-trials
environment reflectors ch estimation

Electromagnetic
Holographic Beyond mMIMO High spatial Practical Research since
metasurface Early experiments
MIMO technology multiplexing gains implementations late 2010s
transceivers

scenarios. The latest literature, advancements, and future larger number of antennas in practice [210]. Whereas
directions in these domains were discussed in [252], practical implementations of massive MIMO employ tens
[262]. to hundreds of antennas, ultra-massive MIMO will go
from hundreds to thousands, as illustrated in Figure 14.
Due to the huge number of antennas, very narrow beams
B. Antenna System Technologies for 6G
can be formed, leading to extreme beamforming gains.
In the 6G era, antenna systems are expected to be pushed Thus, ultra-massive MIMO is considered a promising
to their limits in the forms of ultra-massive MIMO, RISs, technology to enable THz communications with extended
and holographic MIMO (HMIMO). Ultra-massive MIMO is coverage by combating harsh propagation conditions with
a promising technology to enable THz communication in high beamforming gains [210]. In addition, increased
cellular environments by combating severe propagation losses spectral efficiency can be achieved through multi-stream
through high beamforming gains. An RIS is a revolutionary transmissions with high spatial multiplexing gains [210].
technology to control a wireless environment in a desirable Due to the miniature size of THz antennas, the physical
way. HMIMO has the potential to provide very high spatial size of antenna arrays with an ultra-massive number of
multiplexing gains due to efficient utilization of spatial di- elements remains feasible in practice [285].
mension. These three technologies are reviewed below and • Past and Present: The theoretical concept of massive
summarized in Table V. MIMO was developed in 2010 for a multi-user multiple-
input single-output (MISO) system with the number of
antennas approaching infinity [286]. Since then, massive
MIMO has been widely studied in the literature [287].
The first practical implementations of massive MIMO
were witnessed in the early phase of 5G in the late
2010s, relying on antenna arrays with 64 dual-polarized
elements and fully digital transceiver chains [287]. Since
then, the number of antennas in practical implementations
has been increasing. In the literature, the first studies on
ultra-massive MIMO were conducted in the mid-2010s
Fig. 14. From massive MIMO to ultra-massive MIMO.
[285]. Currently, ultra-massive MIMO is considered as
an extension of 5G mmWave massive MIMO to 6G
1) Ultra-Massive MIMO: THz frequencies, with potential applications in diverse
• Vision: Ultra-massive MIMO is expected to become the
scenarios, ranging from ultra-broadband cellular access
core antenna system technology in 6G, enabling THz to wireless backhauling, sensing, and localization [210].
communications with increased capacity and coverage. • Opportunities and Challenges: Ultra-massive MIMO
Moreover, very narrow beams of THz ultra-massive has great potential to become an enabling technology
MIMO may be used for high-accuracy sensing and local- for THz communications with increased data rates and
ization, while expanding the capabilities of 6G networks extended coverage in 6G networks [210]. Furthermore,
beyond communication. high spectral efficiency is enabled via spatial multiplexing
• Introduction: Ultra-massive MIMO (also known as ex-
using multi-stream transmissions, especially for multi-
tremely large-scale MIMO (XL-MIMO)) can be seen as user scenarios. To further extend the coverage and avoid
an extension of massive MIMO by employing even a blockages, THz ultra-massive MIMO beamforming can
 32

be jointly designed with the RIS technology. Due to very wideband beamforming, RIS-assisted beamforming, ex-
narrow beams, THz ultra-massive MIMO can also be used isting array technologies, and emerging applications. In
to obtain high-accuracy localization and sensing in 6G [291], the authors reviewed recent massive MIMO trends
networks [210]. toward 6G in terms of localization and sensing, AI, and
However, there are many fundamental challenges to over- non-terrestrial communications. The work [292] explored
come before THz ultra-massive MIMO systems can be near-field communications for 6G using extremely large-
realized in practice. The cost-, energy-, and spectrum- scale antenna arrays. In [293], extreme MIMO was re-
efficient design of practical ultra-massive MIMO technol- viewed, with a focus on the hardware design. The article
ogy is challenging, particularly in terms of RF, antenna, [294] provided a comprehensive survey on XL-MIMO for
and beamforming designs. As the number of antennas 6G, discussing hardware architectures, signal processing,
increases, hardware design becomes more costly, power and channel modeling. In [289], the authors explored
consuming, and complex. The choice of beamforming 6G ultra-massive MIMO in terms of spatial multiplexing,
architecture plays a major role in this picture. There are degrees of freedom, electromagnetic characteristics, and
three main beamforming architectures: digital, analog, signal processing. The authors of [295] discussed 6G XL-
and hybrid [288]. Digital beamforming is costly for large MIMO in the context of near-field communications.
antenna arrays since it requires one RF chain per antenna. At a high level, the main focus of future research needs
Analog beamforming is a significantly cheaper option. to be on THz ultra-massive MIMO for diverse 6G ap-
However, it cannot support multi-stream transmission. plications. In this domain, there are many fundamental
Hybrid beamforming provides a compromise between problems that still need to be tackled and promising
performance and cost, supporting multi-stream commu- application scenarios to be further explored. Critical open
nication with a reduced number of RF chains. Hybrid challenges toward practical THz ultra-massive MIMO
beamforming is a viable solution for such antenna settings systems include the initial access, beam misalignment,
where digital beamforming is too expensive. and mobility. Further research and development work is
As the beams become narrower, the initial access, channel needed to develop more aware, accurate, and adaptive
estimation, accurate beamforming, and mobility support beamforming systems, calling for more efficient beam
become more challenging [210]. Cell and device dis- searching, training, and tracking methods. Channel esti-
covery is particularly challenging at the cell-edge region mation is also a highly complex task, requiring more prac-
since very narrow beams are required for the distance, tical pilot designs and more efficient estimation methods,
while making it more difficult to discover the target and potentially based on AI/ML. The essential future direc-
establish a connection. Enlarged channel dimensions lead tions to further expand the capabilities and applicability
to the high complexity of channel estimation. For sharp of THz ultra-massive MIMO are RIS-assisted communi-
beams, even a slight misalignment may significantly de- cations, integrated wireless backhaul and access, cellular
grade the performance of the communication link. Beam UAV communications, vehicular connectivity, and joint
misalignment becomes more severe in mobile scenarios. communication, sensing, and localization.
Further information on the opportunities and challenges
can be found in [210], [289].
• Literature and Future Directions: While massive
MIMO theory has been well studied in the literature,
the main research focus of ultra-massive MIMO is on
practical designs/implementations at THz frequencies to
overcome fundamental challenges, provide extreme per-
formance, and expand the capabilities of 6G networks.
Recent survey papers have reviewed the latest literature,
advancements, and open problems [210], [227], [289]–
[295]. In [210], THz ultra-massive MIMO was reviewed
in terms of transceiver design, channel modeling, re-
search advancements, and future directions. In [290], Fig. 15. RIS-assisted communications.
the authors studied active dynamic metasurface antennas
for transmission and reception in 6G extreme massive
MIMO systems. The focus was on hardware architec- 2) Reconfigurable Intelligent Surfaces:
tures, transceiver design, implementation challenges, and • Vision: Energy-efficient, low-cost, and easily deployable
open research problems. Recommended future directions RISs are expected to become a mainstream 6G tech-
for metasurface-based beamforming include frequency- nology, providing diverse benefits from improved signal
selective beamforming, channel estimation, hybrid pas- quality to coverage extensions and blockage avoidance.
sive/active metasurfaces, use cases, and experiments. Ultimately, RISs have the potential to revolutionize mo-
The article [227] focused on beamforming technologies bile communication by turning an unpredictable and
for THz ultra-massive MIMO. The covered topics include destructive wireless propagation environment into a pro-
transceiver architectures, beamforming design principles, grammable smart entity that can be favorably controlled.
 33

• Introduction: The fundamental idea of RISs is to shape RIS has been studied under many different names, such as
the wireless environment in a favorable manner by re- reconfigurable reflectarrays, programmable metasurfaces,
flecting radio signals via passive beamforming toward software-controlled metasurfaces, and IRS. The term RIS
the desired receivers [63], [296]. Specifically, an RIS was introduced in the late 2010s. At present, RIS and IRS
consists of a high number of sub-wavelength size recon- are the most popular names, with RIS being dominant.
figurable electromagnetic elements that are electronically The RIS concept was extended from passive to active
controlled to adjust the phase of the incoming signal to (without RF chains) and hybrid versions in the early
direct and shape the reflected beam in a way such that the 2020s [298]. Generally, many aspects of RIS technology
signal quality is improved at the receiver [296]. RISs can have been explored, ranging from fundamentals and al-
be used to strengthen signal quality, mitigate interference, gorithmic designs to prototyping and experiments [302],
expand coverage, overcome difficult propagation condi- [303]. Recently, a special focus of research has been
tions, and even control signal polarization and channel directed toward RIS-assisted 6G networks with a wide
rank [63], [296]. A schematic illustration of RIS-assisted range of application scenarios [218], [297], [304]–[306].
communication is shown in Figure 15. RISs have also evoked enthusiasm in the industry due to
Without the need for complex decoding/encoding pro- their low cost and energy efficiency. Many major technol-
cesses and power-consuming RF operations, the passive ogy companies are currently developing various types of
type of RIS is a cost- and energy-efficient technology RIS solutions. Recently, prototypes and trials have been
[296]. Another attractive feature of passive RISs is their introduced [303]. In 2018, NTT DOCOMO demonstrated
natural support for full-duplex operation without typical a metasurface reflect-array-aided 5G communication sys-
antenna noise amplification and self-interference effects tem in the 28 GHz frequency band, obtaining a data
[296]. Typical implementations of RISs include tradi- rate of 560 Mbit/s in comparison to 60 Mbit/s with no
tional reflect-arrays, liquid-crystal surfaces, and software- reflector assistance [303]. In 2020 and 2021, NTT DO-
defined metasurfaces [296]. Metasurfaces are particularly COMO conducted further trials on transparent dynamic
promising for advanced implementations due to their metasurfaces using the same 5G frequency band [303]. In
unique electromagnetic properties. RISs are relatively 2022, LG showcased four different RIS prototypes, i.e.,
easy to deploy since they are lightweight and can be PIN diode RIS, liquid crystal RIS, transparent planar RIS,
installed on flat surfaces (e.g., walls and ceilings) [297]. and transparent flexible RIS [19]. Also in 2022, Japanese
In addition to typical passive RISs, active and hybrid Kyocera introduced a transmissive metasurface to expand
RIS concepts also exist. The concept of active RIS refers coverage and avoid obstacles in 5G/6G networks [19].
to the RIS’s capability to amplify reflected signals to Although RIS technology has received significant world-
overcome the so-called double fading effect of a typical wide attention in academia and industry, standards exist
RIS environment [298]. Compared with passive RISs, only at regional levels [303]. However, coordinated efforts
active RISs can offer improved performance at the cost toward common understanding and guidelines have been
of increased power consumption [298]. While active RISs taken in terms of large-scale projects and new inter-
do not necessarily require active RF components, there est and specification groups organized by international
exist hybrid architectures that rely on the combinations standardization bodies. For example, the EU’s Horizon
of passive RIS elements and some additional active RF 2020 program has recently funded many RIS-dedicated
chains [298]. Among these three different RIS concepts, projects [303]. Moreover, the IEEE Communications So-
there is a performance-energy/complexity/cost trade-off ciety has established two interest groups and an emerging
to be tackled to find preferable implementations for technology initiative focusing on RISs to promote mul-
different application scenarios. tidisciplinary research and international collaborations,
While the aforementioned passive, active, and hybrid including academic and industrial players [303]. In 2021,
RIS concepts operate in the relay mode, RISs can op- ETSI founded an industry specification group on RISs,
erate in the transmitter mode as well [299]. In the with a wide range of partners from vendors and operators
transmitter mode, a passive RIS is used as part of an to research institutes and universities [303]. The expected
access point (AP) by adjusting the phase and amplitude outcome consists of white papers, technical reports, and
of the incoming unmodulated carrier signal from the proof-of-concepts. Further details on the industrial and
nearby RF source to transfer information by creating standardization aspects of RISs are presented in [303].
virtual amplitude-phase modulation constellations over- • Opportunities and Challenges: The main promise of
the-air [300]. The transmitter-mode RIS allows a rather RISs is that they can turn an uncontrollable and hostile
simple RF chain-free hardware architecture, facilitating wireless propagation environment into a programmable
cost- and energy-efficient design. While the coverage of entity that can be shaped in a favorable way. This can
reflective-only RISs is limited to the front side of the be achieved with an energy-efficient, low-cost, and easily
surface, a concept called transmissive-reflective RIS aims deployable RIS technology operating in a (nearly) passive
to achieve 360 degrees coverage by allowing transmissive relay-type mode. RISs can provide diverse benefits, such
communication through the RIS to cover the backside of as high beamforming gain, improved received signal
the surface as well [301]. quality, extended coverage, and obstacle avoidance. There
• Past and Present: Since the early 2010s, the concept of are many opportunities to exploit RISs. In particular,
 34

RISs can be used to enhance a broad range of emerging [324].

6G technologies [297], [307]. Ultimately, RISs have
the potential to become a mainstream technology and
revolutionize the manner in which mobile networks are
designed in the 6G era.
There are many challenges to overcome before large-scale
deployment in mobile networks is possible. First of all,
there is a lack of comprehensive theoretical models and
performance limits, as well as realistic channel models
[296]. Furthermore, the main practical problems exist
in hardware design, real-time control, channel estima-
tion, channel state information (CSI) acquisition, mo-
bility management, and resource allocation [63], [297].
The current hardware solutions have limited controlla- Fig. 16. An active holographic MIMO surface.
bility. Since passive RISs cannot receive or send pilot
signals, channel estimation, CSI acquisition, real-time
control, and mobility management become particularly 3) Holographic MIMO:
problematic [297], [308]. Adding an RIS to a wireless • Vision: HMIMO is seen as a promising beyond massive
environment further complicates the resource allocation MIMO technology for 6G networks to obtain very high
problems. spatial multiplexing gains via transceiver-based active
• Literature and Future Directions: Since the late 2010s, HMIMO or controllable wireless environments via low-
RIS technology has been one of the major 6G topics power/cost passive HMIMO reflectors (i.e., RISs).
in the literature. Over the years, a vast variety of re- • Introduction: HMIMO aims to go beyond massive
search and development work has been conducted, from MIMO by transmitting, receiving, or reflecting commu-
theory to practice. However, there still exist unresolved nication signals using electromagnetically-driven surfaces
issues remain to be addressed. Further efforts are needed [287], [325], known as HMIMO surfaces (HMIMOS)
to find practical solutions for hardware design, real- [325]. HMIMOS can be classified into active/passive
time control, channel estimation, CSI acquisition, and and contiguous/discrete categories [325]. The difference
mobility management. Another vital future direction is between active and passive is that an active HMIMOS
to study RISs in the context of 6G, considering its is used as a transceiver with sophisticated RF and signal
special characteristics and potential application scenarios. processing capabilities, whereas a passive HMIMOS acts
In particular, RISs can be used to enhance emerging as a reflector with low-cost and low-power passive el-
6G technologies, such as THz communications, massive ements. An active HMIMOS is also known as a large
MIMO, cell-free massive MIMO, UAV communications, intelligent surface (LIS), whereas a passive HMIMOS
NOMA, D2D, backscattering, wireless power transfer is widely known as an RIS or IRS [325]. A schematic
(WPT), PHY layer security, sensing, and localization. illustration of an active HMIMOS is presented in Figure
Recently, numerous survey articles on RISs have been 16.
published [218], [296], [297], [302]–[319]. These can be The idea behind a contiguous HMIMOS is to create
divided into three high-level categories: generic [296], a contiguous aperture by incorporating an (virtually)
[302], [307], [309], [310], [312], [314], [316], specific uncountable number of elements into a two-dimensional
[303], [308], [311], [315], [317]–[319], and 6G-oriented surface of a finite size [325]. A discrete HMIMOS
[218], [297], [304]–[306], [313]. While the generic sur- relies on a discrete aperture that typically consists of a
veys reviewed RISs from a wide perspective, the spe- large number of software-controllable unit cells made of
cific surveys focused on a particular narrow aspect of metamaterials [325]. Based on the aforementioned cate-
RISs. The generic papers covered operating principles, gorization, the four operation modes of HMIMOS are de-
state-of-the-art technologies, recent research advances, fined as contiguous active transceiver HMIMOS, discrete
opportunities, applications, and open challenges [296], active transceiver HMIMOS, discrete passive reflector
[302], [307], [309], [310], [312], [314], [316]. The spe- HMIMOS, and contiguous passive reflector HMIMOS
cific surveys explored prototyping and experiments [311], [325].
myths and critical questions [308], industrial perspective Among these modes, the typical ones are contiguous
[303], ML approaches [315], sensing/localization [317], active transceiver HMIMOS and discrete passive reflector
hardware [318], air-to-ground communications [320], and HMIMOS [325]. Since the former mode approximates
security/privacy [319]. The 6G-oriented survey papers a virtually infinite number of elements, it implies that
examined RISs for 6G from the perspective of generic it could potentially achieve the fundamental limits of
overviews [297], [305], performance optimization [313], massive MIMO and enable extremely high spatial mul-
THz communications [218], [321], vehicular communi- tiplexing gains. Furthermore, the implementations of ac-
cations [304], positioning in IoT [306], near-field com- tive HMIMOS are more energy- and cost-efficient than
munications [322], PHY layer security [323], and NTNs massive MIMO technology. The most attractive features
 35

of the latter mode are software-controlled reflections, The fundamental theory of active HMIMOS is largely
energy/cost-efficient implementation, and flexible deploy- lacking, requiring a comprehensive characterization of the
ment. In this section, the main focus is on the active theoretical performance limits. Efficient algorithms need
HMIMOS since the passive ones (i.e., RISs) were already to be designed to approach these limits in practice. Since
reviewed in the previous section. contiguous HMIMOS is considered as a whole, conven-
• Past and Present: In the literature, the first works on tional far-field channel models may not be valid in certain
active HMIMOS were published in 2017, under the cases [328]. Specifically, the size of the surface is much
names of holographic RF systems, holographic beam- larger than the wavelength and is somewhat comparable
forming, and LISs [325]. Active HMIMOS began to gain to the link distances. Thus, near-field models must be
more interest at the beginning of the 2020s. The main carefully studied. Radio waves behave very differently in
focus of HMIMO research is on passive HMIMOS (i.e., the near-field than in the far-field. Although this brings
RISs) due to its energy/cost-efficient implementation and new challenges for the design of HMIMOS systems,
relatively easy deployment. In current mobile networks, it also opens up novel opportunities. For example, the
5G supports codebook-based massive MIMO with lim- directive nature of the near-field propagation environment
ited resolution in the azimuth and elevation angles [1], may lead to improved spatial multiplexing gains through
[326]. This beam-space approach is highly sub-optimal, efficient beam focusing methods. Near-field HMIMOS
obtaining a performance far from the theoretical limits operation may also open new possibilities for WET.
of massive MIMO [63]. Active HMIMOS is gaining an In particular, important future directions include practi-
increasing amount of interest toward 6G, as it is seen as cal implementations, prototyping, experiments, and field-
a potential solution to this need. trials. This work is ongoing in academia and industry.
• Opportunities and Challenges: The main opportunity However, further efforts are needed to prove the fea-
that active HMIMOS offers is to potentially obtain ex- sibility of HMIMOS in practice. Moreover, the special
tremely high spatial multiplexing gain and performance characteristics of 6G networks must be considered, such
close to the theoretical limits of massive MIMO in as mmWave/THz operation, stringent performance re-
practice, while being more energy- and cost-efficient than quirements, and a heterogeneous network architecture.
massive MIMO technology. On this road, diverse issues Recently, a handful of survey papers have been published
must be addressed. These open challenges are primarily on HMIMOS [325], [327]–[333]. In [325], HMIMOS
related to theoretical limits, channel modeling, algorithm was reviewed from the 6G perspective. A broad range
design, practical implementations, and experiments [327]. of topics was covered, such as hardware architectures,
A comprehensive characterization of the theoretical limits fabrication methodologies, operation modes, functionality
with a proper electromagnetic domain analysis is still types, characteristics, communication applications, design
to be defined, providing performance upper bounds for challenges/opportunities, and case studies.
practical algorithms. Channel models must be updated The survey [328] explored LIS technology in terms
by considering the special properties of HMIMOS, such of information-theoretical limits, communication modes,
as LOS and non-line-of-sight (NLOS) near-field propa- power-scaling law, and future research directions. In
gation. Channel estimation becomes difficult due to the [327], a comprehensive survey was given on HMIMOS,
extremely high number of antenna elements. HMIMOS reviewing physical aspects, theoretical foundations, en-
also sets major challenges for beamforming and beam abling technologies, extensions, and open problems. In
focusing designs, calling for efficient low-complexity [329]–[331], the authors provided a three-part tutorial on
algorithms to enable practical systems. In practical imple- HMIMO, covering channel modeling and estimation in
mentations, many challenges arise, e.g., identification and part 1, performance analysis and beamforming aspects
compensation of hardware impairments, handling of mu- in part 2, and opportunities and challenges in part 3.
tual coupling between densely located antenna elements, The paper [332] discussed channel modeling for HMIMO
and the support of numerous beams for high spatial communications in the near-field domain. In [333], the
multiplexing gains. In order to verify the performance authors introduced electromagnetic information theory
of practical implementations, experiments need to be for HMIMO communications.
executed in realistic mobile network scenarios and setups.
Further details of the main challenges can be found in
[327]. C. Transmission Scheme Technologies for 6G
• Literature and Future Directions: Since the late 2010s, The role of a well-designed transmission scheme is crucial
many aspects of active HMIMOS have been researched. for 6G since it determines how efficiently the available spectral
The main topics include fundamental theory, channel resources can be used. In other words, the 6G transmission
modeling, algorithm design, practical implementation, scheme plays a key role in turning a massive spectrum range
experiments, and sensing/localization. Since HMIMOS is into extreme performance to support stringent requirements
a new research area, all the aforementioned directions and a wide range of demanding usage scenarios. To this end,
need major research and development efforts in the near 6G requires an ultra-flexible transmission scheme with novel
future to attain an adequate level of maturity for practical technological elements. Some potential technologies include
implementation. highly tunable multi-waveform scheme, advanced modulation
 36

TABLE VI
S UMMARY OF TRANSMISSION SCHEME TECHNOLOGIES FOR 6G

Transmission
Scheme Vision Description Opportunities Challenges Past Present
Technologies

Multi-Waveform Ultra-flexible More than one Supports massive Finding suitable 4G CP-OFDM 5G CP-OFDM
Scheme waveform scheme waveform spectrum range waveforms and DFT-s-OFDM and DFT-s-OFDM

Advanced High-order mod

Modulation and High-performance Bits into symbols High throughput 4G Turbo/conv & 5G LDPC/polar &
& coding for
Coding Methods modulaton/coding & error correction & high reliability up to 256-QAM up to 1024-QAM
URLLC

Non-Orthogonal Next-generation User separation in More efficient Receiver Under study for
Multiple Access 5G study item
multiple access power or code than orthogonal complexity 6G

Grant-Free Network access Fast/efficient Preamble 4G four-step 5G two-step

Medium Access Massive access
wo grant from BS network access collisions random access random access

and coding methods, efficient NOMA, and fast grant-free induced by a high peak-to-average-power ratio (PAPR),
medium access, as summarized in Table VI. In the following, and sensitivity to hardware impairments and mobility.
we provide a detailed discussion on each of these technologies. Due to the shortcomings of CP-OFDM, many other wave-
1) Multi-Waveform Scheme: forms were studied for 5G in the literature [335], [336].
• Vision: A flexible multi-waveform scheme is expected to The main ones included filter bank multi-carrier (FBMC),
play a crucial role in the 6G air interface by supporting universal filtered multi-carrier (UFMC), and generalized
efficient operation in a massive spectrum range from sub- frequency-division multiplexing (GFDM) [335]. In addi-
6 GHz to THz frequencies. tion, different types of OFDM variants were proposed,
• Introduction: At a high level, the purpose of a waveform such as filtered (F)-OFDM and windowing (W)-OFDM
is to define a transmission framework to carry modulated [336]. Nevertheless, a tunable version of CP-OFDM
information symbols from the transmitter to the receiver technology was chosen for 5G, with flexible multi-
over a wireless communication channel. A flexible multi- numerology as a key feature [2]. The main elements of
waveform scheme refers to an approach in which more multi-numerology are scalable SCSs and CP lengths. The
than one waveform, with flexible features, is employed in former provides robustness against hardware impairments
a communication system. Multi-numerology is a key ele- and lower latency at higher frequencies, whereas the latter
ment to achieve flexibility for a given waveform by using aims to eliminate the effects of multipath propagation
multiple sets of parameters to choose from, depending and inter-symbol interference in all channel conditions.
on the prevailing conditions. Specifically, different sets While CP-OFDM is used for both downlink and uplink
of parameters are used for different transmission settings directions in 5G, there are certain uplink setups, i.e.,
and channel conditions, leading to improved performance single-layer transmissions, where a single-carrier-based
and enabling efficient communication in diverse wireless DFT-s-OFDM technology is an alternative option, en-
environments. abling extended coverage. Flexible CP-OFDM plays a
• Past and Present: The earliest realization of a multi- key role in 5G for supporting diverse use cases, such as
waveform scheme is from 4G LTE, where different eMBB, URLLC, and mMTC. Currently, different types
waveforms are used for downlink (cyclic prefix (CP)- of waveforms are being studied in academia and industry
OFDM) and uplink (discrete Fourier transform-spread- to support a wide range of demanding 6G application
OFDM (DFT-s-OFDM)), and two CP lengths exist (i.e., scenarios. 4G and 5G waveforms are summarized in
normal and extended) [334]. Spectral efficiency is pre- Figure 17.
ferred in downlink, whereas power efficiency in uplink. • Opportunities and Challenges: The potential of a multi-
An extended CP is used for worse channel conditions, waveform design, with highly tunable numerology, is to
with the aim of eliminating inter-symbol interference. CP- provide an efficient core to an ultra-flexible transmission
OFDM was adopted in 4G due to its robust nature toward structure to support a vast range of possible 6G frequen-
multipath fading as well as straightforward support for cies, requirements, use cases, and application scenarios.
low-complexity receivers and MIMO communications. Due to 6G’s massive spectrum range, relying solely on
While CP-OFDM has many advantages, there are also a single waveform may not be a feasible solution. A
apparent disadvantages, such as reduced spectral effi- preferable approach is to select a set of waveforms to
ciency due to CP and orthogonality, poor power efficiency support all types of 6G scenarios. To this end, the main
 37

and cons, but there is no single method that fits well to

WAVE- all 6G scenarios. Consequently, multiple waveforms must
FORMS be utilized in ultra-heterogeneous 6G networks.
In the context of multi-waveform schemes, there are two
main future research directions, i.e., developing a com-
prehensive set of waveforms to support different types
4G 5G of 6G scenarios and finding a flexible set of parameters
for each of these waveforms. As mentioned earlier, a
logical starting point for this category of research is to
CP-OFDM CP-OFDM study an enhanced OFDM-based scheme as a primary
(DL) (DL/UL) technology, complemented by one or more waveform
technologies. Single-carrier waveforms, such as DFT-s-
OFDM and its variants, seem potential candidates for
complementary technologies, as they fit well for THz
DFT-s-OFDM DFT-s-OFDM
frequencies due to their low PAPR and robustness toward
(UL) (UL Rank 1)
hardware impairments [216], [337], [345]. The paper
[337] provided a survey on the waveform design for 6G
Fig. 17. 4G and 5G waveforms. THz communications. As 6G is expected to expand its
capabilities beyond communication, an important future
challenge is to develop a proper set of waveforms to topic is the study of waveform design for a joint com-
support a massive spectrum range from sub-6 GHz to munication and sensing paradigm [344], [346]–[349].
THz frequencies, and also to find a comprehensive set of
parameters for those waveforms and the associated frame
CODING
structure. GAIN
At a high level, a possible solution for the multi-
waveform problem is to choose one primary waveform CHAN- CODING
NEL RATE
technology to handle most of the scenarios and one
or many complementary technologies for special cases.
For example, an ultra-tunable OFDM-based waveform
strategy could be chosen as the main technology due to
its proven performance and flexibility in 5G. The flexible
QoS
MODULATION CODING
OFDM scheme can then be complemented by a single AND CODING DELAY
carrier-type waveform technology, such as DFT-s-OFDM
or its variant, for higher-frequency operation in the THz
band since this type of waveform has a low PAPR and
is more robust against severe hardware impairments at
very high frequencies [216], [337]. It is worth noting COM- ERROR
PLEXITY RATE
that if an OFDM-based multi-waveform scheme will be
selected, the first version of 6G could be designed to DATA
interact closely with 5G, enabling a faster and smoother RATE
launch. Such a design could exploit the lessons learned
from the transition from 4G to 5G. Fig. 18. Factors to consider in the design of modulation and coding schemes
[350].
• Literature and Future Directions: In the literature, a
vast variety of single-carrier, multi-carrier, and OFDM-
based waveforms have been studied for 5G and beyond 2) Advanced Modulation and Coding Methods:
[337]–[340]. Typical single-carrier waveform candidates • Vision: Advanced modulation and channel coding meth-
include different variations of DFT-s-OFDM [216], [337], ods will play key roles in the 6G PHY layer, especially
[341]. In the multi-carrier domain, popular waveforms in terms of high-throughput and extremely reliable com-
include FBMC, UFMC, GFDM, and orthogonal time munications.
frequency space modulation [339], [342]–[344]. Numer- • Introduction: A modulation method is in charge of
ous OFDM variants have been developed, such as F- mapping the bits into symbols. The order of the mod-
OFDM, block-filtered OFDM, W-OFDM, cyclic post- ulation is defined by the number of bits per symbol.
fix windowing-OFDM, time-interleaved block-windowed Higher-order modulations are used to achieve higher data
burst OFDM, and weighted overlap and add OFDM rates, whereas lower-order modulations are meant for
[338]. Since CP-OFDM has established its status in better reliability. Channel coding fights against errors
mobile networks, competing technologies aim to over- occurring in a wireless medium by adding redundancy
come its shortcomings. However, considering individual to the transmitted data sequence. Higher coding rates are
waveforms, each of these technologies has its own pros employed for reliability, whereas lower code rates are
 38

used for better throughput. vanced channel coding will play a key role in pro-
Modulation and channel coding are tight together in a viding extremely reliable communication for many 6G
concept known as adaptive modulation and coding, in application scenarios, such as smart factory and smart
which modulation orders and coding rates are bundled healthcare environments. Enhanced polar codes seem
into modulation and coding schemes (MCSs), each of promising for 6G due to their favorable properties for
which has different spectral efficiency and reliability highly reliable communication, particularly with stringent
properties [351]. Adaptive modulation and coding is latency requirements [63], [356], [357].
used to adapt MCSs to the prevailing channel conditions At a high level, there are two main challenges in mod-
by relying on the signal quality information fed back ulation and coding designs toward 6G, i.e., developing
from the receiver [351]. Adaptive modulation and coding efficient methods for ultra-high throughput and extremely
plays an important role in the link-level performance of reliable communication links. The former design problem
current mobile networks, particularly in terms of data rate calls for efficient high-order modulation and low coding
and reliability [351]. Enhanced modulation and coding rate methods with decent error-correcting properties. A
methods are needed for every new mobile generation to straightforward solution is to increase the modulation
meet the ever-growing performance demands. Figure 18 order beyond 5G’s 1024-QAM, requiring a thorough
summarizes the main factors that need to be considered performance comparison between different variations of
in the design of modulation and coding schemes. QAM. However, increasing the order of QAM may not
• Past and Present: Each mobile generation has adopted provide the needed performance gains at higher 6G
a novel or enhanced channel coding concept, i.e., 2G: frequencies due to the inefficiency of power amplifiers
convolutional coding (data and control), 3G: Turbo cod- [63]. To alleviate this problem, coded modulation with
ing (data) and convolutional coding (control), 4G: Turbo signal shaping is a promising concept [358], especially
coding (data) and convolutional coding (control), 5G: in combination with polar codes [359]–[362]. Polar codes
low-density parity check (LDPC) coding (data), and polar have favorable features to efficiently support lower cod-
coding (control) [352]. Currently, LDPC codes are used ing rates in combination with higher-order modulations
for data channels and polar codes for control channels [359], [363], [364]. Coded modulation with probabilistic
in 5G [353]. Turbo coding was the first channel coding shaping is already in use in optical fiber communications
method approaching theoretical channel capacity. Linear [63].
LDPC coding also belongs to the class of capacity- In the latter design problem, a major challenge is to
approaching codes while outperforming Turbo coding, develop channel codes that fit well with 6G-level reli-
particularly in the higher coding rate region and in terms ability and latency requirements. A challenging trade-off
of the error floor [354]. Polar coding is a linear block- exists between reliability and latency in the design of
error correction code with low-complexity encoding and channel coding in the URLLC-type scenarios [357]. In
decoding designs, and the first channel code that achieves other words, long block-length codes are required for
theoretical channel capacity [354]. LDPC and polar codes reliability, whereas short ones are required for latency.
have been reviewed for 5G NR in [353], [354]. Polar coding has been shown to strike a good balance
The most commonly used modulation methods in mobile between reliability and latency, making it a promising
communication are phase shift keying (PSK) and quadra- candidate for the 6G-level URLLC scenarios [356], [357].
ture amplitude modulation (QAM) [355]. PSK is a digital In general, polar codes have favorable properties for
modulation technique in which the phase of the carrier highly reliable communications, such as the lack of error-
wave is altered. Digital QAM adjusts the amplitudes of floor and efficient error-correction capabilities [63], [356].
the two orthogonal carriers according to a digital mod- Further discussions of the latest enhancements for polar
ulation process. The used modulation methods and their codes can be found in [63], [357], [364].
constellation sizes for different mobile generations are as • Literature and Future Directions: In the 2010s, LDPC
follows [355]: Gaussian minimum shift keying (GMSK) and polar codes were studied for 5G [353]. Research be-
in 2G; binary PSK (BPSK), quadrature PSK (QPSK), yond 5G is ongoing, with a special emphasis on enhanced
16-QAM, and 64-QAM in 3G; BPSK, QPSK, 16-QAM, polar codes [357], [364], [365]. Many different variations
64-QAM, and 256-QAM in 4G; π/2-BPSK, QPSK, 16- of polar codes have been proposed in the literature [366]–
QAM, 64-QAM, 256-QAM, and 1024-QAM in 5G. Each [369]. In particular, polar codes have been examined for
new generation has raised the highest constellation size 6G-level scenarios, such as ultra-high throughput and
a step further. This trend suggests that 6G could adopt extremely reliable low-latency communications [356],
4096-QAM, provided that it will be proven beneficial in [357], [363], [364], [370], [371]. Shaped polar-coded
practice. modulation is another active and particularly interesting
• Opportunities and Challenges: The main advantage of topic for 6G [63], [360]–[362], [372], [373]. The past,
advanced modulation and coding methods is improved present, and future of channel coding were discussed in
link-level performance in terms of reliability and data recent surveys [352], [365], [374]. Further research is
rates. Higher modulation orders and lower coding rates needed in these directions to achieve a required level of
provide better throughput, whereas lower orders and maturity for practical implementation in the 6G era.
higher code rates provide reliability. In particular, ad- In the modulation domain, QAM is the most widely
 39

used and studied modulation method in mobile networks but are left for possible future usage in beyond 5G
[355]. Currently, 5G supports QAM with modulation networks. According to [376], the main reason behind
orders of 16, 64, 256, and 1024 [355]. 6G calls for even this decision was that there were no clear gains shown
higher-order modulations. Recent studies have shown in the evaluation process of different NOMA schemes
special interest in hexagonal QAM due to its promising compared to the existing Release 15 technologies (e.g.,
performance properties [355]. A comprehensive survey of multi-user MIMO), and given that the implementation
QAM and its diverse variants was provided in [355]. complexity of NOMA receivers is rather high. A de-
tailed discussion of the proposed NOMA candidates and
OMA NOMA the corresponding evaluation and decision process are
UE3
provided in [376]. Nevertheless, the research focus of
UE1 UE6 NOMA has shifted from 5G to beyond 5G, as it is still
UE9
Power

Power
UE1 UE2 UE3 UE4 UE5 UE4 considered a promising technology candidate for many
UE2 UE7 UE8
communication scenarios in the future.
UE
UE5
10 • Opportunities and Challenges: The main benefit of
NOMA technology is that it provides improved spectral
Frequency Frequency
efficiency and fairness by serving multiple devices per
Fig. 19. Orthogonal versus non-orthogonal multiple access [375]. each time-frequency resource unit. The most promis-
ing 6G application scenario for NOMA is ultra-massive
IoT communications with grant-free access [377]. For
3) Non-Orthogonal Multiple Access: a typical overloaded massive connectivity scenario, it
• Vision: NOMA is considered a potential technology is assumed that there are two defining features present
candidate for improving the spectral efficiency and sys- [377]. First, there are much more devices requesting
tem capacity of 6G. A particularly promising 6G usage service than the number of available orthogonal resource
scenario for NOMA is to facilitate massive IoT commu- units. Second, it is assumed that narrowband IoT sensors
nications in combination with fast grant-free access. will send only a small amount of uplink data every now
• Introduction: NOMA is based on the principle that and then.
multiple users/devices can be served simultaneously by In this type of scenario, conventional orthogonal multiple
utilizing the same transmission resource element (e.g., access schemes may be inadequate to provide service for
a time-frequency resource block) [376]. At the cost of all the devices in need, and waste too much resources for
increased interference levels and receiver complexity, each narrowband IoT sensor, as the smallest orthogonal
NOMA can improve spectral efficiency, system through- resource unit may significantly exceed the need of an
put, and user-fairness compared to orthogonal multiple individual IoT device. NOMA, instead, is seen as a more
access (OMA) [376]. The difference between OMA and efficient method to serve all devices in need due to its
NOMA is illustrated in Figure 19. Furthermore, latency ability to serve multiple devices in a single resource unit
properties can be improved by combining NOMA with a and better match the needs of each individual device,
grant-free access scheme [377]. and not waste the scarce spectral resources. Moreover,
Typically, NOMA schemes are categorized into two main combining NOMA with fast grant-free medium access
classes [378]: power-domain NOMA (PD-NOMA) and will further improve the system performance, especially
code-domain NOMA (CD-NOMA). In the former strat- in terms of decreased latency and reduced signaling [377].
egy, the users are separated in the power domain. For For the aforementioned reasons, grant-free NOMA is an
example, using superposition coding at the transmitter attractive technology for 6G ultra-massive IoT scenarios.
and successive interference cancellation (SIC) at the re- There are also numerous other application scenarios for
ceiver. The latter approach exploits code-level separation NOMA in the context of 6G networks [378]. Combining
by relying on, for example, spreading codes, interleaving, NOMA with other emerging 6G technologies (e.g., RIS,
scrambling, or other types of user-specific re-modification D2D, V2X, VLC, etc.) may provide further benefits in
of data sequences. CD-NOMA can be further categorized terms of spectral efficiency, system throughput, service
into dense and sparse coding classes [378]. There are also balancing/fairness, and energy efficiency [379]. A com-
hybrid NOMA schemes that combine the PD-NOMA and prehensive review of the combination of NOMA and
CD-NOMA strategies. A comprehensive categorization of many other emerging technologies has been presented in
the numerous NOMA variants can be found in [378]. [379], [380].
• Past and Present: In the past decade, there has been As mentioned earlier, NOMA was studied for 5G NR as
great interest in studying the NOMA technology for a study item, but 3GPP decided not to include it in the
5G and beyond [378]. Consequently, NOMA was added official 5G standards [376]. This 3GPP process showed
as a study item to the 3GPP 5G NR standardization that a critical challenge of NOMA is the development
process [376]. Many different types of NOMA schemes of schemes that provide a sufficient balance between
were proposed and evaluated using link- and system- performance and complexity. In particular, a typical prob-
level simulations. However, it was decided in 3GPP that lem of PD-NOMA is the implementation complexity
NOMA studies do not proceed to the work item phase, of the required multi-user detection-based receiver (e.g.,
 40

the SIC-receiver). Consequently, reducing the receiver been combined with many other emerging technologies.
complexity is an essential challenge, as discussed in Currently, the most promising research direction is grant-
[376]. Another key challenge is to find suitable 6G usage free NOMA for massive IoT communications [377]. Due
scenarios in which the NOMA technology is beneficial, to its promising nature, it is advisable to direct an extra
and to develop customized NOMA methods for each of focus to that research area. Other potential topics, with
these usage scenarios. disruptive nature, include NOMA-D2D, NOMA-V2X,
• Literature and Future Directions: Since the early NOMA-UAV, NOMA-RIS, NOMA-massive MIMO, and
2010s, NOMA has been widely studied for 5G and NOMA-VLC [379], [380]. Applying AI/ML methods to
beyond [376]. Both domains, power and code, have been assist in NOMA solutions is also an important research
considered, with the main focus on the former. As dis- direction.
cussed in [376], many NOMA methods were developed
GRANT-FREE GRANT-BASED
and evaluated for 5G NR as a study item. In 3GPP, further
study on NOMA was left for beyond 5G scenarios, as its
development work was not continued for the work item
Instant access
phase in the 5G NR design process. Since then, a plethora Permission
of NOMA schemes have been proposed for promising process

beyond 5G usage scenarios. Comprehensive surveys on a

Fig. 20. Grant-free versus grand-based medium access.
wide range of future NOMA methods were presented in
[378], [381]–[383]. In particular, combinations of NOMA
with many other emerging 6G technologies have been 4) Grant-Free Medium Access:
studied [379]. • Vision: Fast grant-free medium access is considered a
In the literature, numerous survey papers have reviewed key technology to enable efficient network access in the
different aspects of NOMA and captured its evolutionary 6G era, especially for ultra-massive IoT scenarios.
path from the preliminary 5G studies to promising 6G • Introduction: Grant-free medium access refers to an
candidate technology, with numerous potential applica- access scheme where devices can instantly access the
tion scenarios. At a high level, NOMA surveys can be network without a time-consuming permission process,
classified into several categories, i.e., 5G and beyond as illustrated in Figure 20. Grant-free access aims to
[378], [384]–[386], generic [376], [380], [387], [388], offer a fast and efficient network access procedure. Its
specific [377], [379], [380], [389]–[397], and 6G [381]– main benefits are decreased latency, reduced signaling
[383], [398], [399]. In the 5G and beyond domain, the overhead, and improved energy efficiency [400]. Typical
main focus was on the applicability of NOMA to 5G and drawbacks include the collisions of transmissions and a
expanding the possible NOMA application scenarios to lack of priority among service-needing devices [400]. All
better fit the needs of beyond 5G networks. The generic these features make grant-free access applicable to IoT
surveys reviewed NOMA from a wider perspective, scenarios, with many devices sending small amounts of
covering current status, recent advances, state-of-the-art, data every now and then.
application scenarios, and open problems. The specific • Past and Present: In the literature, grant-free access
surveys examined various narrow topics, including the for mobile communications started to gain considerable
combination of NOMA and other emerging technologies interest in the mid-2010s due to the recognized relevance
[379], [380], NOMA myths and critical questions [389], of diverse IoT scenarios in future mobile networks. A
grant-free NOMA for IoT [377], RIS-assisted NOMA particular focus of the corresponding studies was on
[390], [393], [396], DL-assisted NOMA [391], NOMA- mMTC for 5G. Recent research on grant-free access looks
based VLC [392], NOMA for ISAC [394], [397], and beyond 5G to enable ultra-massive connectivity in 6G
cache-aided NOMA [395]. The 6G-oriented surveys ex- [400], [401]. In standardization, 4G LTE supports a four-
plored NOMA as the next-generation multiple access step random access procedure, while 5G NR updated
technology. its random access to a grant-free two-step procedure in
To include the NOMA technology in the 6G standards, Release 16 [402].
there are many open issues to be addressed. For instance, Whereas 4G’s four-step process requires a response from
the implementation complexity of NOMA schemes, espe- the base station (BS) before sending its payload data,
cially at the receiver side, must be reduced for practical 5G’s two-step access allows devices to transmit data with-
usage. Hence, complexity reduction is an essential target out a particular response [400]. This grant-free random
for future research. Another research avenue is to study access provides benefits in lowering latency and reducing
what are the most suitable 6G scenarios for different control signaling overhead, particularly for MTC scenar-
types of NOMA schemes. For each potential scenario, ios with many burst transmissions of small data packets
tailored NOMA solutions need to be developed and from a massive number of devices [400]. However, the
thoroughly evaluated. This category of research is widely performance of the two-step access is limited by the
conducted worldwide. Recently, different types of NOMA preamble collision problem when multiple devices send
solutions have been proposed for various future appli- the same preamble to the BS simultaneously, causing a
cation scenarios. In particular, the NOMA concept has collision of the transmissions. In [402], a survey was
 41

provided on the two-step random access procedure in active devices. A comprehensive survey was provided on
5G NR, reviewing also the latest literature and potential grant-free NOMA for IoT in [377]. In [403], grant-free
solutions to the preamble collision problem. URLLC was studied, with a special focus on the potential
• Opportunities and Challenges: The potential of ad- enhancements provided by massive and cell-free massive
vanced grant-free access is to serve as a key enabler for MIMO technologies. The paper [400] discussed grant-
ultra-massive IoT and its numerous application scenarios free random access for MTC. In this context, massive
in the 6G era by providing a fast and efficient network ac- MIMO and NOMA concepts were reviewed, as well
cess procedure. As grant-free access offers many benefits as future challenges toward 6G. In [405], the authors
by reducing latency, releasing communication resources explored grant-free access for massive satellite-based IoT
from excess signaling, and facilitating energy-efficient in the 6G era. The work [401] discussed grant-free
designs, it is naturally applicable to IoT scenarios with network access based on compressive sensing for 6G
massive numbers of devices occasionally sending small massive communications.
data packets. On the road to this vision, there are still Although 5G has already adopted a grant-free access
many challenges to overcome. The main ones are related process, it needs to be upgraded to match the unique char-
to the special characteristics of 6G, such as massive acteristics of 6G, such as massive access, extremely tight
connectivity, stringent performance requirements, and performance requirements, novel network architectures,
network heterogeneity [400]. and versatile application scenarios. In this respect, it is
First, the greater the number of access-needing devices vital to study and design grant-free access mechanisms
is, the higher is the probability of preamble collisions. that consider emerging 6G technologies, such as AI/ML,
This requires advanced collision avoidance strategies NOMA, RIS, cell-free massive MIMO, and space-air-
[400], [402]. Grant-free access becomes more challenging ground network architecture. AI/ML is a versatile tool
when massive connectivity is combined with the stringent for making grant-free access more efficient and robust
latency requirements of devices [400]. Since transmis- [400], [402]. NOMA allows more devices to be served
sion collisions increase latency, novel solutions must be simultaneously by allocating multiple devices to a single
adopted. For example, a contention-free access strategy resource unit and separating them into power or code
with reserved preambles can be used to achieve collision- domains. Thus, grant-free NOMA is a potential candidate
free transmissions within the target delay time [400]. for ultra-massive IoT connectivity in 6G [377].
However, when the number of devices increases, reserved Recently, grant-free NOMA has been extended to RIS-
preambles may run short. Adding stringent reliability assisted scenarios to further improve the network access
constraints to this scenario, that is, massive URLLC, performance by providing potential benefits in terms of
further complicates the problem [400], [403]. In this spectral efficiency or reliability [406]. Cell-free massive
case, there is a compromise between connection density, MIMO with grant-free access is a promising concept to
latency, and reliability. To alleviate the problem of finding provide massive connectivity with stable coverage and
a proper balance between these conflicting requirements, decreased latency for low-power devices in IoT scenarios
AI/ML-aided traffic prediction methods can be exploited [403]. Grant-free access can exploit the distributed nature
[400]. Accurate traffic prediction facilitates preamble of cell-free networks, but needs to address the corre-
management and collision avoidance. sponding synchronization issues [400], [403]. Although
Integrated space-air-ground networks also bring new 3D networks offer great opportunities for 6G, they also
challenges to grant-free access due to unconventional set new challenges for grant-free access [400], [405].
3D channel and interference characteristics with non-
terrestrial APs (UAVs and satellites) and end-devices
(UAVs). Cell-free network design with distributed D. Network Architectural Technologies for 6G
lightweight APs, another architectural evolution expected The design of mobile networks is becoming increasingly
to be employed in 6G, will also change the traditional complex for each new generation. From the network design
network topology, creating new opportunities and chal- perspective, 6G is expected to support 3D network architec-
lenges. While spatial sparsity can be exploited to sup- tures, UDNs, flexible cell deployments, and cell-free opera-
port massive access, synchronization becomes trickier. tions. A 3D network architecture will be enabled by integrating
In general, AI/ML is a promising tool to tackle diverse terrestrial and non-terrestrial access, including space, air, and
issues in grant-free access by utilizing device activity and ground layers. Satellite communication is a key technology
traffic patterns for efficient design and management. More for global coverage on the land, in the air, and at the sea.
information regarding the aforementioned challenges of Due to THz communications, 6G will rely on an ultra-dense
grant-free access in 6G networks can be found in [400]. cell design to provide sufficient coverage for extreme-capacity
• Literature and Future Directions: In the literature, there scenarios. Flexible cell deployments will be facilitated by
are a handful of survey papers on grant-free access that integrating wireless backhaul and access. In addition to the tra-
cover different aspects and review the latest advancements ditional cell-based design, 6G is expected to be complemented
[377], [400], [401], [403]–[405]. In [404], compressed by a cell-free network architecture to provide stable QoS in
sensing techniques were reviewed for grant-free massive the coverage area. This section provides a detailed discussion
IoT connectivity, focusing on the efficient detection of on the aforementioned network architectural technologies, i.e.,
 42

TABLE VII
S UMMARY OF NETWORK ARCHITECTURAL TECHNOLOGIES FOR 6G

Network
Architectural Vision Description Opportunities Challenges Past Present
Technologies

Integrated
Non-Terrestrial Space-air-ground Space-air-ground Cost efficiency & Satellite commun
and Terrestrial Global coverage 5G NTNs
network access network layers industry incentive since 1960s
Networks

Ultra-Dense Highly densified Interference Denser networks 5G mmWave

Networks THz UDNs Extreme capacity
networks management from 1G to 5G small cells

Cell-Free Massive Complementary Lots of distributed Stable QoS over Scalability & Concept invented Under study for
MIMO 6G architecture low-cost APs network coverage clustering in 2015 6G

Integrated Access Same resources Faster/cheaper to Resource alloc

and Backhaul THz IAB Separated A&B 5G IAB
for A&B install than fiber between A&B

INTNs, UDNs, IAB, and cell-free massive MIMO. These receivers. Since satellites are high in space, each one
technologies are summarized in Table VII. of them can cover large geographical areas on Earth.
1) Integrated Non-Terrestrial and Terrestrial Networks: Consequently, satellites can provide global coverage,
including land, sea, and air. There are three primary
• Vision: INTNs are expected to play a key role in 6G, orbits for communication satellites: geostationary orbit
potentially providing global coverage and enabling a (GEO) (35786 km), medium Earth orbit (MEO) (7000-
myriad of novel applications, ranging from high-speed 25000 km), and low Earth orbit (LEO) (300-1500 km)
remote area connectivity to global IoT and worldwide [409]. Each orbit has its advantages and disadvantages.
environmental/industrial monitoring. In general, wider coverage is obtained using satellites in
• Introduction: INTNs are communication systems that higher orbits, while the propagation characteristics are
typically consist of ground, air, and space layers. This better and satellites cheaper in lower orbits.
architecture is also known as a space-air-ground inte- • Past and Present: Different layers of the INTNs have
grated network (SAGIN) [407], as illustrated in Figure evolved over different timescales. Although the history
21 [23], [63]. For this network architecture, the corre- of satellite communications dates back to the 1960s
sponding layers are called ground-based, airborne, and and the first terrestrial cellular networks were opened
spaceborne [63]. The main elements of the ground-based in the 1980s, UAV-assisted communication is still in its
layer include mobile networks, satellite ground stations, infancy. The era of satellite communication began in the
and mobile/satellite devices [63]. early 1960s when the first communication satellite was
The airborne layer consists of high- and low-altitude launched. Since then, satellites have been an important
aerial platforms. HAPSs are aerial network nodes, such part of worldwide communications, currently providing
as aircrafts, airships, and balloons, operating as relay-type a vast range of services from television broadcasts and
entities at the stratospheric altitudes of up to 20 km [63]. satellite phones to high-speed Internet access and global
Due to their relatively high altitudes, HAPSs can provide navigation systems. The next major step is to integrate
wide area coverage from urban to rural environments. satellite communication into mobile networks, thereby
In the lower airborne layer, UAVs can be used as aerial opening up a broad range of novel application scenarios.
BSs or relays to improve the performance of mobile The earliest research on HAPSs was conducted in the
networks, especially in terms of capacity and coverage 1990s. However, HAPSs have gained more interest only
[408]. UAVs are considered as the low-altitude platform recently, as they are seen as part of the next genera-
stations (LAPSs), serving as agile and flexible network tion space-air-ground network architecture. UAV-assisted
nodes [63]. UAVs can provide temporal or long-term communications have been extensively studied over the
performance enhancements, depending on the application past decade, with the main focus on 5G networks. In the
scenario. late 2010s, the focus of research started to shift toward
The spaceborne layer is based on satellite communica- 6G networks [408].
tion. Satellite communication refers to communication 5G is already taking the first steps toward the inte-
between widely separated locations on the globe by gration of terrestrial and non-terrestrial networks. Cur-
sending radio signals from the ground-based transmitters rently, NTNs, especially satellite access (with implicit
by relaying and amplifying satellites to the ground-based
 43

Fig. 21. Integrated space-air-ground network [23], [63].

support for HAPS and air-ground networks), are under the capabilities of traditional mobile networks. Other
standardization in 3GPP 5G NR [410], [411]. The work benefits include robustness against security attacks and
toward supporting NTNs started in 2017 as a Release 15 natural disasters. For mobile networks, satellite-assisted
study item on deployment scenarios and channel models, communication enables a wide range of new application
followed by Release 16 studies identifying necessary scenarios, such as high-speed remote area connectivity,
physical/higher-layer features and key use cases with global IoT, worldwide environmental/industrial monitor-
the associated requirements [410]. NTNs were formally ing, high-quality maritime and aeronautical communica-
incorporated into the 5G NR standards in Release 17. tions, and remote area emergency/safety/disaster commu-
The corresponding work items specified the necessary nications.
enhancements to support LEO/GEO satellites (also im- In the airborne layer, HAPSs can provide wide area
plicitly HAPS and air-ground scenarios), stage 1 ser- coverage and high-speed connectivity for diverse types
vice requirements, and produced normative specifications of environments, from urban and rural to remote and
based on the previous studies [410], [412]. Release 17 disaster areas. Compared to satellites, HAPSs offer much
also studied non-terrestrial IoT, satellite access/backhaul, smaller coverage. However, they are cheaper and faster to
business roles, service management, and public land deploy, which makes them more flexible network nodes.
mobile network (PLMN) selection (in international areas) In the lower airborne layer, UAVs can provide dynamic
[410], [412]. Release 18 studied NR NTN enhancements improvements to system-level performance, particularly
in terms of coverage, access beyond 10 GHz, mobility, in terms of capacity and coverage. Potential application
and service continuity [411], [412]. Detailed reviews on scenarios include flexible support for temporal hotspots
the standardization efforts of 5G NR NTNs are presented and mass events, communication for disaster areas, and
in [410]–[412]. It is worth noting that in 3GPP, UAVs coverage for outage/remote areas. Due to their numerous
are studied in a separate track than other non-terrestrial benefits and potential applications, NTNs are expected to
components, focusing only on cellular-enabled UAV com- become an integral part of 6G networks.
munications [410]. Integrating non-terrestrial communications into mobile
• Opportunities and Challenges: Incorporating non- networks brings many challenges, such as satellite in-
terrestrial components as part of terrestrial networks tegration at a reasonable cost and QoS, network man-
provides many opportunities for expanding capabilities agement in a heterogeneous 3D network architecture,
and introducing novel application scenarios. In a ground- realistic channel modeling, and regulatory aspects. In
air-space network, each layer offers its own set of ben- terms of satellite integration, LEO and mini-satellites
efits and challenges. The main advantage of the space- are promising candidates for 6G due to their reasonable
borne layer is global-scale coverage, vastly expanding balance between cost and performance. Satellites in the
 44

lower orbits have better propagation features, shorter offloading, resource allocation, multi-connectivity, mo-
delays, and cheaper prices than those in the higher orbits. bility management, distribution of computation/caching
A heterogeneous 3D network architecture with space-air- resources across layers, realistic channel modeling, and
ground layers makes network and resource management practical experiments [407], [411]. Further details on
challenging, calling for advanced cooperation mecha- these research aspects can be found in [407], [411].
nisms between different layers. AI/ML is a promising
tool for addressing diverse network management issues.
Realistic channel models are needed for appropriate
performance evaluation in the 6G-specific application
scenarios. Regulatory challenges arise when aiming at
global coverage. Regulations in different countries and
international waters must be considered when designing
INTNs. The main challenges of INTNs are further dis-
cussed in [407], [411].
• Literature and Future Directions: In the literature,
INTNs have received a considerable amount of attention
since the mid-2010s, becoming one of the key topics in
6G research. Numerous survey articles have recently been
published [409]–[424]. They explored a broad variety of
INTN aspects. The work in [410] reviewed 5G NTNs in
3GPP, covering radio access, systems, services, protocols, Fig. 22. A heterogeneous ultra-dense network.
and IoT. In [409], the authors surveyed the evolution of
NTNs from 5G to 6G networks. NTNs were discussed
from the perspectives of 5G, mmWave, IoT, multi-access 2) Ultra-Dense Networks:
edge computing (MEC), AL/ML, higher layers, field • Vision: UDNs are considered a key element in meeting
trials, industry progress, and 6G. NTNs were explored the extreme capacity needs of 6G networks, especially
toward 6G in [413]. In [414], a survey was conducted via dense THz cell deployments.
on NTNs in the 6G era. The focus was on enabling • Introduction: UDNs refer to extremely densified wireless
technologies, open issues, and a case study. 6G SAGIN networks, where there are a massive number of het-
was studied in [415]. The topics covered include space erogeneous access nodes and end-devices. The typical
and mobile networking, key enablers, UAV-as-a-service, access nodes of next-generation heterogeneous UDNs
design aspects, applications, challenges, and future re- range from macro and small/tiny BSs to roadside units
search avenues. and aerial/satellite relay nodes [425]. End-devices can
In [416], 6G service-oriented SAGIN was reviewed in vary from mobile devices and IoT sensors to vehicles,
terms of applications, requirements, resource manage- drones, and robots [425]. A schematic illustration of a
ment, cloud-edge synergy, and future research. The study heterogeneous UDN is shown in Figure 22. Network
in [411] focused on INTNs, discussing standardization, densification is a means to correspond to the exponential
architecture, use cases, opportunities, challenges, and growth of mobile data traffic and the constant need for
future directions. In [417], [418], [422], AI for NTNs was more capacity. Higher-frequency communication, with
reviewed. The authors in [419] provided a 6G connected larger bandwidths and shorter link distances, naturally
sky vision on the integration of terrestrial and non- lends itself to the network densification paradigm, pro-
terrestrial components, discussing use cases, architecture, viding extreme capacities and data rates in ultra-dense
and network design. The work [420] examined satellite- deployments. Network densification brings access nodes
terrestrial convergence from 5G to 6G. In [412], the and end-devices closer to each other, leading to lower
authors reviewed recent advances of NTNs in 5G, fo- propagation losses, reduced transmission powers, and
cusing on 3GPP Release 17 and 18. Multi-connectivity improved received signal qualities. In general, network
was explored for beyond 5G NTNs in [421]. The paper densification aims to improve capacity, data rates, spectral
[423] studied AI/ML, network slicing, and O-RAN tech- efficiency, coverage, and energy efficiency [425], [426].
nologies to facilitate the design of 6G NTNs from the On the other hand, densification makes the management
academia and industry perspectives. In [424], the authors of the network more challenging, especially in terms of
discussed the challenges of radio access technologies for resource, interference, and mobility management [426].
6G NTNs, focusing on the waveform design, spectrum • Past and Present: In the history of mobile communi-
coexistence, and radio resource management. cation, network densification has always been one of the
To free the potential of INTNs, major efforts are still key ways to satisfy the ever-increasing demand for higher
required in the interdisciplinary research and develop- network capacity [425]. Each generation, from 1G to
ment work. Important future research directions include 5G, has developed denser and denser networks with a
3D network management, cooperation between layers, more heterogeneous nature. In 5G networks, the main
performance-cost trade-offs, network selection, traffic types of access nodes include macro and small cell BSs
 45

[427]. High-power macro BSs typically operate at sub-6 still needed to address these fundamental challenges.
GHz frequencies, and provide a relatively large coverage, Recently, the research focus has shifted to beyond 5G
with efficient mobility support. Lower-power small BSs, UDNs [428], [431]. Consequently, the variety of studied
with limited coverage and mobility support, offer a higher topics has widened while taking the special characteristics
capacity, primarily relying on mmWave communications. of 6G networks into account. Accordingly, interesting
5G also supports a heterogeneous network architecture, future topics include the exploration of UDNs from the
with the emerging rise of IoT, vehicular, and non- perspective of AI/ML assistance, THz operation, optical
terrestrial communications. 6G will continue the trend of wireless, ultra-massive IoT, vehicular networks, ultra-
developing denser and more heterogeneous networks by dense IAB, and cell-free network design. In particular,
expanding to higher operating frequencies with denser AI/ML is applicable to solve many complex network
deployments and aiming to fully integrate space, air, management problems in the design of UDNs [425],
mobile, vehicular, and IoT components into the network [426], [428]. Further details on UDNs can be found in
architecture. recent surveys that have reviewed the latest literature,
• Opportunities and Challenges: The potential of UDNs research achievements, open issues, and future directions
is to fulfill the extreme network capacity demands of [425]–[428], [432].
the 6G era. In particular, ultra-dense THz cell deploy-
ments enable novel data-hungry multimedia applications
in densely populated areas. Although UDNs hold great
potential, they also pose major challenges. A major limit-
ing factor of the network capacity in UDNs is interference
[428]. Hence, it is of the utmost importance to develop
efficient interference management methods to free the
potential of UDNs and achieve the desired capacity gains.
There are three main types of interference in UDNs: F
I
B
inter-tier, inter-cell (inter-tier), and intra-cell interference E
R
(intra-tier) [428]. The key to managing interference is
cooperation among neighboring/interfering cells. Coop-
eration requires computation power, information sharing, Fig. 23. Integrated access and backhaul.
and additional signaling, increasing the demands of com-
putation hardware and backhaul/fronthaul links.
Another challenge is the mobility management [428]. 3) Integrated Access and Backhaul:
Due to smaller cells, handovers are more frequent for • Vision: While IAB is already part of 5G standards, its
mobile end-devices. Handovers require network control, role in 6G will grow due to continuing cell densification.
end-device assistance, and communication resources from Since IAB is a cheaper and faster alternative to fiber links,
the source and target cells. Thus, more frequent handovers it is expected to become an integral element in ultra-dense
consume more computational and communication re- 6G networks.
sources, leading to a decrease in capacity and an increase • Introduction: IAB is a concept in which the same radio
in latency, energy consumption, and computational com- resources of a BS are used for both wireless access and
plexity. Resource management is also more challenging backhaul [433], as illustrated in Figure 23. IAB is a flex-
for UDNs [426]. For example, efficient load-balancing ible, agile, and low-cost method to provide backhauling,
mechanisms are required to prevent service imbalances being a promising alternative to fiber links, especially
and user fairness issues. Backhauling may also become a in dense networks due to faster and cheaper installation
bottleneck in an ultra-dense deployment [427]. Because [433].
conventional fiber links are costly and time-consuming to • Past and Present: IAB was first standardized in 4G
install, the deployment of a large number of access nodes under the name LTE relaying [434]. However, this ap-
is very expensive and slow. In this respect, the ultra- proach has not achieved much success owing to scarce
dense integrated wireless access and backhaul concept is spectral resources [434]. IAB started to gain considerable
a promising solution due to its flexibility, low cost, and interest in the mid-2010s, with a special focus on 5G
fast installation. mmWave networks. Compared to 4G, 5G is more suitable
• Literature and Future Directions: In the literature, for the widespread use of IAB due to dense small-cell
UDNs have been extensively explored during the past deployments, mmWave spectrum, and massive MIMO
decade [425], [426], [429]. The original driver behind technology [63]. IAB was first standardized in 5G NR
the increased research interest was 5G mmWave com- Release 16 and further enhanced in Release 17 [433].
munications with dense small-cell deployments [430]. Overviews of NR IAB can be found in [433]–[435].
Popular research directions for UDNs have been re- • Opportunities and Challenges: Commonly used optical
source allocation, interference management, user associ- fiber backhaul links are very fast and reliable, but they
ation, energy efficiency, mobility/handover management, are also costly and time-consuming to install [63]. In this
and backhauling [425]–[427], [429]. Further research is context, IAB is a promising alternative to fiber links due
 46

to its lower cost, higher flexibility, and faster deployment aided IAB, RIS-aided IAB, UAV IAB, cache-enabled
[433]. The role of IAB will become more important in IAB, and optical IAB [433]. Since 6G is expected to enter
the future since mobile networks will become denser in the THz spectrum, a special research focus needs to be
the 6G era. Thus, IAB is expected to play a key role directed toward ultra-dense 6G IAB networks, operating
in ultra-dense 6G networks operating at mmWave/THz at THz frequencies.
frequencies [63], [433]. Other possible application sce-
narios for IAB include UAV-assisted networks, RIS-
empowered networks, optical wireless networks, cache-
enabled networks, and NTNs [433].
The main challenges in IAB are related to resource and
interference management [433]. For example, resource
allocation between access and backhaul is not a trivial
task depending on the traffic loads at the source and
CPU
destination BSs. If too much resources are allocated to
either side, system performance degrades. AI/ML is a
promising tool to facilitate such resource allocation prob-
lems by predicting traffic loads and capacity demands.
Another fundamental challenge is the mitigation of inter-
ference. In IAB, two types of interference exist [433]:
interference between access and backhaul (i.e., inter-
technology interference) and interference within access
and backhaul (i.e., intra-technology interference). The Fig. 24. Cell-free massive MIMO [443].
former is a (rather) new type of interference in mobile
networks, which makes interference management more
challenging. This calls for novel interference mitigation 4) Cell-free Massive MIMO:
mechanisms, possibly AI/ML-assisted. Integrating IAB • Vision: Cell-free massive MIMO is a promising technol-
with other emerging 6G technologies, such as NTNs, ogy to complement the traditional cell-based network de-
RISs, OWC, and caching, opens up new opportunities for sign in the 6G era. It is applicable to scenarios that require
IAB, but also introduces a new set of challenges [433]. stable QoS levels over the entire network coverage.
• Literature and Future Directions: In recent years, IAB • Introduction: Cell-free massive MIMO aims at providing
has been extensively studied [433], considering diverse stable performance across the network coverage area,
topics from resource and interference management to thus alleviating the traditional problem of large perfor-
network topology optimization and end-to-end perfor- mance discrepancies between the cell-center and cell-
mance evaluations. A comprehensive overview of the IAB edge regions [63], [444]. The main idea is to use lots
literature was provided in [433]. As the standardization of distributed low-cost APs with a few antennas each
work on NR IAB started in the late 2010s, a special instead of having a lower number of traditional APs with
research focus has been directed toward 5G mmWave a large number of co-located antennas [63], [444]. Each
networks [436]. Further information on NR IAB and the device in the network area is jointly served by its nearby
related literature can be found in [223], [434]. Recent APs. Cooperation between APs is enabled by the central
IAB topics on 5G evolution and beyond include UAV- processing units (CPUs) and fronthaul links.
aided IAB [437], AI/ML-aided IAB [438], cache-aided Compared with the traditional cell-based network design,
IAB [439], RIS-aided IAB [440], mmWave IAB [441], cell-free massive MIMO provides shorter link distances,
and cell-free IAB [442]. Further discussion of the latest lower propagation losses, reduced transmission powers,
research areas is provided in [433]. alleviated interference profiles, and improved signal qual-
Future IAB research can be divided into two main areas: ities [63], [444]. Consequently, cell-free operation leads
practical enhancements to 5G NR IAB and IAB solutions to improved stability of the user-experienced performance
beyond 5G. In the former category, essential research across the network coverage area and increased system-
directions include enhancements to beamforming, inter- level energy efficiency. Cell-free design is applicable to
ference management, resource allocation, routing, and scenarios in which there is a need for steady QoS within
topology optimization. For instance, massive MIMO is the entire network. Scalability is a typical problem in cell-
a potential technology to enhance NR IAB such that free network architectures [445]. A schematic example of
the same frequency-time units can be used for access a cell-free massive MIMO network is illustrated in Figure
and backhaul links, leading to improved spectral effi- 24.
ciency. Hybrid beamforming is a particularly promising • Past and Present: The concept of cell-free massive
method due to its good balance between performance and MIMO was introduced in 2015 [446], [447]. The pro-
implementation complexity. In the latter category, it is posed idea, that is, a large number of distributed APs
important to study the synergy between IAB and other jointly serving users in the network area [448], [449],
emerging 6G technologies, such as THz IAB, AI/ML- has flavors from three different concepts, namely massive
 47

over the network, such as industrial environments. Cell-

M- free massive MIMO is expected to serve as a complemen-
MIMO tary technology to conventional cellular network topology
in the 6G era [432], [453]. However, this vision is still
far from reality, as the research and development work of
cell-free massive MIMO has mainly been theoretically-
Cell-Free oriented. Hence, there is a lack of practical performance
validations, experiments, and field-trials. Before practi-
CoMP Massive cal large-scale realizations are possible, the fundamental
MIMO problems must be resolved.
The basic issue in cell-free operation is scalability [445],
as discussed earlier. This problem can be solved by
dynamic user-centric clustering, which limits the com-
putational burden in the processing units and signaling
UDNs overhead in the fronthaul/backhaul links [445]. Therefore,
clustering plays a critical role. The number of APs
in a cooperative cluster cannot be too large since the
Fig. 25. Three technologies behind cell-free massive MIMO [444]. complexity increases significantly. Cluster sizes cannot be
too small either due to the increased interference levels,
MIMO, network MIMO, and UDNs [444], as shown in degrading network performance. Another fundamental
Figure 25. Since the total number of antennas serving issue in cell-free massive MIMO is synchronization. A
each user is large, the PHY layer technologies of massive synchronized network is required because each user is
MIMO are applicable. The foundation of a cell-free jointly served by multiple APs via coherent transmis-
operation that jointly serves each user via many APs is sion. Inaccurate synchronization leads to degraded per-
based on the principles of network MIMO (i.e., joint formance. Therefore, proper synchronization mechanisms
processing CoMP). A large number of geographically are pivotal.
distributed APs in a relatively small area reflects the Since cell-free architecture is a new way to construct
nature of UDNs. The challenge lies in the co-design of a network, resource allocation strategies must be re-
these three elements to obtain a cell-free operation with designed accordingly. Mobility is also problematic since
sufficient scalability for practical implementations [444]. it leads to rapid chances in clustering. Theoretical channel
In the original concept, all distributed APs are assumed models are commonly used in the performance evaluation
to jointly serve each user in the network area, leading of the proposed cell-free solutions, leading to unrealistic
to scalability issues due to the increasing computational results. Practical channel models based on the dedicated
complexity and signaling overhead as the number of channel measurements are required to achieve more re-
APs and users grows, making the concept infeasible for alistic results and more useful performance analyses.
practical large-scale implementations. To solve scalability Prototyping and field trials are required to shift cell-
issues, a refined version of the cell-free operation was de- free massive MIMO from a theoretical concept to a
veloped, known as user-centric cell-free massive MIMO practical network architecture. More detailed discussions
[450], in which each user is served by a limited set of of the fundamental challenges of cell-free networks are
nearby APs. Clustering APs for individual users makes presented in [432], [444], [451]–[453].
the network more scalable, leading to better suitability • Literature and Future Directions: In the literature,
for large-scale deployments. In [445], the user-centric cell-free massive MIMO has been actively researched
approach was further enhanced by applying a clustering since the mid-2010s. The concept has been thoroughly
framework from the network MIMO literature, known as reviewed in recent surveys [432], [444], [451]–[459]. A
dynamic cooperation clustering. This clustering concept broad range of aspects was discussed, including theo-
has been proven scalable for any network size [445]. The retical foundations, network scalability, dynamic user-
latest details of cell-free massive MIMO research are centric clustering, synchronization, resource allocation,
covered in [432], [444], [451]–[453]. Cell-free massive uplink/downlink operations, AP selection, receive com-
MIMO is expected to be utilized in 6G to complement the bining, transmit precoding, power optimization, channel
traditional cell-based network architecture in scenarios hardening, channel estimation, pilot assignment, hard-
that require stable QoS in the network coverage area ware impairments, mobility issues, mmWave/THz oper-
[432], [453], [454]. ation, fronthauling, deployment challenges, and future
• Opportunities and Challenges: The key advantages of research toward 6G. Although substantial research efforts
cell-free massive MIMO are stable QoS across the entire have been made to date, further work is still needed to
network coverage area, energy- and cost-efficient deploy- overcome the fundamental challenges discussed earlier.
ment, macro diversity, and favorable propagation. Cell- Moreover, promising 6G-related future topics include
free network design is particularly applicable to scenarios AI/ML for cell-free, cell-free with RISs, cell-free for
where there is a need for robust and steady performance IoT, cell-free in O-RAN, practical implementations, and
 48

TABLE VIII
S UMMARY OF NETWORK INTELLIGENCE TECHNOLOGIES FOR 6G

Network
Intelligence Vision Description Opportunities Challenges Past Present
Technologies

Enhanced network E2E optim & AI/ML in

Intelligent Core AI-native core AI-enhanced core Cloud-native 5G
management cloud-edge coop 5G-Advanced

Enhanced edge Infra & AI algs & Edge computing AI/ML in

Intelligent Edge AI-native edge AI-enhanced edge management data acquisition in 5G 5G-Advanced

Intelligent Air AI-native air AI-enhanced air Enhanced Fast changing ch Flexible air AI/ML in
Interface interface interface PHY/MAC conditions interface in 5G 5G-Advanced

experiments [432], [453], [454], [458], [459]. 1) Intelligent Core:

• Vision: In the core network, 6G will go beyond 5G’s soft-

warization by adopting intelligence via pervasive AI/ML.
CORE This can be seen as an evolution from cloud to cloud
intelligence.
• Introduction: Mobile networks consist of three main
components: core network, RAN, and mobile devices,
6G as illustrated in Figure 27. The core and RAN operate
INTELLIGENCE cooperatively between the Internet and mobile devices.
The core network is responsible for the overall network
AIR operation, management, and security, whereas the RAN
EDGE
INTERFACE handles wireless access to serve mobile devices. For
example, one of the key tasks of the core network is
to guarantee secure and reliable end-to-end communi-
Fig. 26. The cornerstones of 6G network intelligence. cation between source and destination nodes. Today’s
core networks are software-based and cloud-native. The
next major step in the evolution of core networks is
E. Network Intelligence Technologies for 6G the adoption of intelligence via AI/ML in the 6G era.
The ultimate goal of AI/ML is to revolutionize the design, The intelligent network core is based on the pervasive
operation, and management of mobile networks by making utilization of AI/ML in order to improve the design,
them more intelligent, efficient, flexible, scalable, automated, operation, management, maintenance, and security of the
proactive, economical, ecological, and secure. While this network. DL is an attractive technology for the core
vision is currently far from reality, the first concrete steps since it achieves excellent performance when the training
toward it have been taken. AI/ML has been adopted in the datasets are large. Data acquisition is a crucial component
5G standards from Release 18 onward (i.e., 5G-Advanced). In of the intelligent core.
6G, pervasive AI/ML is expected to be a major leap toward • Past and Present: Each mobile network generation has
the grand vision. This section discusses how AI/ML can be its own core network that responds to the demands
exploited at different levels of the network, i.e., the core, edge, and expectations of that particular generation. Since the
and air interface. These are the cornerstone of 6G network requirements of mobile networks are constantly growing,
intelligence, as illustrated in Figure 26 and summarized in the capabilities of the core networks evolve generation
Table VIII. by generation. In short, the core networks have evolved
from 2G’s circuit-switched network through 3G’s and
BACKHAUL ACCESS 4G’s packet cores to the latest software/service-based ar-
chitecture of 5G. Specifically, a new cloud-native service-
oriented core network was developed for 5G, as defined
by 3GPP in Release 15 [1]. The main features of the
5G Core include SBA, SDN, NFV, and network slicing.
CORE RAN UEs
SBA relies on a vast variety of interconnected network
Fig. 27. Three main elements of mobile networks. functions, each of which provides one or more services
that are accessible by other network functions. This archi-
 49

tecture allows the agile addition of novel functionalities. latent knowledge exploration. The surveys [460], [461],
SDN enables cloud-native and flexible network manage- [464] explored ML from a wider perspective in wireless
ment. NFV and network slicing enable the division of the networks. In [464], ML was discussed in the context of
network resources into independent virtual slices, each SDN, surveying traffic classification, routing optimiza-
of which can be dedicated to a specific service. Virtual tion, QoS prediction, resource management, and network
slicing facilitates the introduction of new services and security. The article [460] focused on ML applications
tailored customer solutions. for resource management, networking, mobility manage-
• Opportunities and Challenges: While softwarization ment, and localization. In [461], ML was reviewed for the
made 5G’s core network cloud native, AI/ML is expected PHY, MAC, and network layers, edge computing, SDN,
to make 6G’s core intelligent and take mobile networks and network security.
to the era of intelligence. AI/ML can potentially im- In [462], [463], [466]–[471], AI/ML was reviewed in
prove the operation, management, and security of the the context of 6G networks. In [462], ML was con-
network. Although much research has been conducted, sidered for intelligent end-to-end network optimization
there are many issues to be resolved in harnessing the in various layers toward 6G. The focus was on MAC
synergy of AI/ML and mobile networks. In [178], [179], layer network access, network layer routing, network
[460]–[463], many challenges and future directions were layer traffic control, and application layer streaming
discussed. These can be divided into several categories: adaptation. The paper [466] studied network intelligence
infrastructure, AI/ML algorithms, network optimization, in 6G, discussing its role, challenges, architecture, and
core-edge cooperation, and security. First of all, network orchestration possibilities. In [467], the authors explored
infrastructure needs to be highly capable from the core intelligent network slicing for 6G networks, introducing
to the edge (in terms of communication, computation, an AI-native slicing architecture as well as discussing AI
and information exchange) to enable the pervasive and for slicing and slicing for AI.
efficient use of AI/ML throughout the network. There is The tutorial in [468] presented an architectural framework
a challenging trade-off between the cost and performance for 6G holistic network virtualization and pervasive net-
in the update of the infrastructure. work intelligence, reviewing also topics like the interplay
In mobile networks, the used AI/ML algorithms need between network slicing and digital twins, AI for net-
to be efficient, fast, reliable, and data-protected. This working, and networking for AI. In [469], the work intro-
makes the design of algorithms challenging and calls duced a concept of intelligence-endogenous networks for
for advanced AI/ML methods, inference/training ap- 6G, utilizing AI and knowledge graph technologies. The
proaches, and data acquisition mechanisms. There are article [463] surveyed ML-based resource management
many challenging network optimization problems that for 6G networks. The covered aspects include resource
can be enhanced by AI/ML, e.g., routing, traffic control, allocation, task offloading, mobility management, energy
and network slicing, to mention a few. A close core- efficiency maximization, and latency minimization. In
edge cooperation and cross-layer design are required to [470], the authors provided a comprehensive survey on AI
obtain the proper end-to-end performance of the network. for 6G networks, focusing on AI-aided technologies and
AI/ML-based security solutions are vital to cope with a applications. The work [471] discussed generative AI for
changing threat landscape and to tackle outside attacks. 6G wireless intelligence. Future research directions were
Further discussion on open problems and future research discussed earlier in the opportunities and challenges part
opportunities can be found in [178], [179], [460]–[463]. of this section.
• Literature and Future Directions: In the literature,
mobile network intelligence has been extensively studied
since the late 2010s, with a focus on 6G networks. Recent
ALL ON-
research progress and open issues regarding intelligent DEVICE
networking have been reviewed in numerous survey ar-
ticles [178], [179], [181], [460]–[471]. In [178], [179], ALL IN-EDGE
[181], [465], the works focused on DL, discussing its CLOUD-EDGE CO-
applications in wireless networks to achieve network in- TRAINING
telligence. The paper [179] surveyed DL applications for ON-DEVICE INFERENCE
PHY, data link, and routing layers. In [178], a thorough CLOUD
TRAINING
IN-EDGE CO-INFERENCE
overview was provided of DL in mobile and wireless
networking, with the main focus on the technological en- CLOUD-EDGE CO-INFERENCE
ablers of DL in networking, DL-driven network aspects,
and customizing DL for networks.
Fig. 28. Six levels of edge intelligence [472].
The authors of [465] provided a tutorial on the applica-
tions of artificial neural networks to solve diverse issues
in wireless networking. The work [181] reviewed DL 2) Intelligent Edge:
for wireless network optimization, discussing universal • Vision: Intelligent edge is anticipated to become an
modeling, complexity mitigation, algorithm design, and integral part of 6G networks, enabling novel services
 50

and applications with reduced latency and communication 17 [17], and 18 [18]. 3GPP is continuing its work on edge
overhead. computing toward EI. The term EI was first introduced
• Introduction: Intelligent edge, commonly known as edge in the white paper of the Gartner Hype Cycle in 2018
intelligence (EI), refers to a combination of edge com- [472]. Since then, EI has been one of the key 6G topics
puting and AI, benefiting from the synergy of both in academia and industry, spurring a broad range of
technologies [472]. Edge computing drives computational publications, projects, collaborations, and development
capabilities, tasks, and applications from the core to efforts.
the network edge [472]. The network edge consists of • Opportunities and Challenges: Combining edge com-
different types of edge nodes, typical ones being edge puting and AI/ML is a natural step in the evolution of
servers and end-devices (e.g., mobile and IoT devices) mobile networks toward pervasive network intelligence.
[472]. The edge computing paradigm shift, which moves Edge computing offers a computation- and data-intensive
computation resources closer to the edge information platform, with the beneficial features of low latency,
sources, naturally leads to reduced latency and commu- reduced communication overhead, high energy efficiency,
nication overhead. protected privacy, and context awareness. AI has the
AI, the other part of EI, is typically based on ML ability to free the potential offered by edge computing
methods, which consist of two main phases, including by optimizing the network edge (e.g., performance, effi-
model training and inference [472]. In the training phase, ciency, adaptability, automation, and security/privacy) and
the AI/ML model is optimized for the given objective enabling a vast range of disruptive applications. Due to
using training datasets that aim to represent a compre- its versatile benefits, EI is expected to play a major role
hensive set of practical data realizations. In the inference in the 6G network intelligence.
phase, the trained AI/ML model is executed by feeding it To realize large-scale EI in practice, fundamental chal-
the real-world input data, acquired from the information lenges must be addressed and resolved. At a high level,
sources, and obtaining an output, optimized according to the main challenges are related to the computation in-
the target objective through the knowledge learned in the frastructure, AI/ML models/algorithms, data availability,
training process. DL, the most popular AI/ML method, network management, network security, and privacy pro-
has been recognized as a natural fit for edge computing, tection. First, large-scale EI requires a ubiquitous com-
achieving excellent performance with large datasets. FL is putation infrastructure, with powerful computation and
another promising AI/ML method for the network edge, storage capabilities at the edge servers, which is a highly
particularly targeted for distributed optimization at the non-trivial trade-off between cost and performance. For
end-devices. each EI purpose/task, an efficient AI/ML approach, with
As shown in Figure 28, there are six levels of EI based practical data acquisition mechanisms, must be devel-
on where AI/ML training and inference are performed oped. Since EI will change the threat landscape, novel
in the cloud-edge-device hierarchy [472]: cloud-edge co- security approaches are required. Due to massive amounts
inference and cloud training, in-edge co-inference and of generated data, EI will be vulnerable to privacy threats,
cloud training, on-device inference and cloud training, calling for advanced privacy protection techniques. For
cloud-edge co-training and inference, all in-edge, and the success of EI, all the aforementioned issues must be
all on-device. As the levels increase, less computation properly addressed. Comprehensive discussions of open
offloading and information exchange are required. The challenges and future directions can be found in [182],
protection of data privacy is also facilitated. However, the [472]–[475].
network is disposed to increased computation latency and • Literature and Future Directions: While edge comput-
energy consumption issues due to the limited computation ing has been a well-studied subject, its combination with
and energy resources of the edge devices. It is dependent AI introduced a new paradigm. In the literature, the ear-
on the application which level is the best fit for it. liest studies on EI are from the late 2010s. The research
• Past and Present: While EI is a new concept, its boomed at the beginning of the 2020s. Over the years,
components, AI and edge computing, have been studied EI has been explored from diverse perspectives, such as
separately in the past. AI research started already in the AI models and algorithms, end-to-end architectures and
1950s, with ups and downs on the road, until it reached a performance, security and privacy approaches, resource
level of constant progress through the introduction of DL management techniques, and application requirements
in the 2000s. Due to advances in other key technologies, with technical enablers. The latest progress in these
AI boomed in the 2010s, reaching also mobile networks. directions and the corresponding literature have been
AI was introduced for 5G in 3GPP’s Release 18 [18]. reviewed in numerous surveys [152], [182], [196], [472]–
The history of AI was discussed in more detail in [486]. These surveys can be divided into generic, 6G-
Section VII. Although it took decades for AI to mature, oriented, and specialized categories. The generic and
edge computing has evolved rapidly. Specifically, edge specialized surveys considered EI from broad and nar-
computing became a popular topic in the 2010s, attracting row perspectives, respectively, whereas the 6G-oriented
wide interest in academia and industry. Consequently, surveys focused on EI in 6G.
edge computing has been supported by 5G since Release The generic EI surveys discussed the basics, key en-
15 [1], with constant enhancements in Release 16 [13], ablers, potential applications, open challenges, and future
 51

• Introduction: An intelligent air interface refers to an

PHASE 1 advanced radio interface where the PHY and MAC layers
are enhanced by AI/ML [487]. In this evolution path,
AI ENHANCES INDIVIDUAL BLOCKS there exist three main phases, as defined in [487] and
summarized in Figure 29. In the first phase, AI/ML
is used to enhance or replace individual air interface
PHASE 2 processing blocks, such as channel estimation or symbol
demapping in the PHY layer. In the second phase, AI/ML
AI REPLACES MANY BLOCKS JOINTLY replaces many blocks by jointly designing them. An
example of this is the joint design of channel estimation,
equalization, and symbol demapping. In the third phase,
AI/ML is expected to design parts of the air interface in
PHASE 3
the PHY and MAC layers, relying on end-to-end learning
AI DESIGNS PARTS OF AIR INTERFACE processes. The third phase would be a revolutionizing
paradigm shift in the design of mobile networks, lead-
Fig. 29. Three evolution phases toward AI-native air interface [487].
ing to substantial performance benefits and significantly
reduced standardization [487].
Traditionally, the PHY layer consists of individual pro-
research opportunities. In the earliest and most popular cessing blocks, which are designed separately. Conven-
survey on EI [472], the authors focused on DL model tional model-based mathematical approaches are gener-
training and inference at the network edge. In [473], AI ally efficient for individually designed PHY layer mod-
was discussed for edge and on edge. The paper [474] ules. However, the overall performance tends to be sub-
provided a thorough overview of the combination of edge optimal when the PHY layer is considered as a whole
computing and DL, covering a vast variety of topics. [63]. The joint design of different PHY layer blocks
In [475], an intelligent edge was rigorously surveyed is mathematically extremely complex [63]. Conventional
in terms of caching, training, inference, and offloading. mathematical tools are incapable of optimally solving
The authors of [182] reviewed all in-edge DL, with the such problems. Due to this algorithm deficit, the use of
main focus on computation architectures, technological AI/ML is justified in the joint design problems [63].
enablers, model adaption, and key performance metrics. The MAC layer is responsible for the network access
The 6G-oriented surveys envisioned EI as a key element process of the service-needing devices and the corre-
of 6G networks. In [476], self-learning EI was discussed sponding radio resource allocations. Efficient allocation
for 6G, also introducing a self-learning architecture, with of resources in diverse dimensions, such as frequency,
a case study to confirm its effectiveness. The paper [477] time, space, power, and/or code, is one of the most
surveyed trustworthy and scalable edge AI for 6G in essential and challenging tasks of the air interface. Due
terms of communication efficient training and inference, to their mathematical complexity, resource allocation
resource allocation techniques, end-to-end architecture, problems are well suited for AI/ML. Generally, resource
standardization (computing and learning), hardware and optimizations are inherently non-convex combinatorial
software platforms, and applications (IoT, healthcare, and problems, being too complex to be solved using conven-
vehicles). In [485], the authors explored split learning tional mathematical methods [63]. Due to this algorithm
for 6G edge networks. Each specialized survey focused deficit, AI/ML solutions may be beneficial for many types
on exploring EI from a narrow perspective, including of resource allocation problems. In this respect, DRL has
IoV [478], IoT in healthcare [479], vehicular systems in been recognized as a promising tool to efficiently solve
6G [480], autonomous driving in 6G [152], on-device different types of MAC layer problems, particularly those
learning systems [481], UAVs [482], metaverse [483], related to resource allocation and network access [488].
security/privacy [484], federated learning [196], and re- The reason for this is that DRL naturally lends itself
inforcement learning [486]. to solving sequential decision making and optimization
Further studies and development efforts are needed to problems [488].
reach the required level of maturity for the standardiza- • Past and Present: In the literature, AI/ML research on
tion and commercialization of EI in mobile networks. the air interface began around the mid-2010s, with a
The previously discussed challenges need to be properly special focus on the PHY layer design. AI/ML-aided
solved in the near future. Future research topics have been MAC layer design also became an interesting topic. In
discussed in [182], [472]–[475]. the past few years, an AI/ML-enhanced 6G air interface
has gained increasing interest in the wireless community
3) Intelligent Air Interface:
and is currently a widely studied topic in academia and
• Vision: The air interface of 6G networks is expected to industry. In practice, 5G was the first mobile generation
be enhanced by AI/ML, potentially revolutionizing the to adopt AI/ML. Specifically, AI/ML was introduced in
design, standardization, and implementation of mobile Release 18, which is the first realization of 5G-Advanced
networks. [7], [18]. However, the use of AI/ML is somewhat limited
 52

since 5G was not originally optimized for pervasive • Literature and Future Directions: In the literature,
AI/ML. 6G will be the first generation designed for AI/ML-enhanced air interface has been studied since the
pervasive AI/ML, including intelligent core, edge, and mid-2010s. The main focus has been on DL-aided PHY
air interface. layer designs, ranging from enhancing/replacing single
• Opportunities and Challenges: Exploiting AI/ML in the or multiple processing blocks (such as channel coding,
design of the air interface provides many potential bene- symbol mapping, channel estimation, equalization, de-
fits, ranging from improved performance to easier design tection, decoding, and symbol demapping) to replacing
and reduced standardization [487]. Possible performance the entire PHY layer with an end-to-end learning process
enhancements include reduced complexity, decreased la- [487]. Furthermore, AI/ML-assisted MAC layer design
tency, and increased spectral/energy/cost efficiency. The has been widely examined, often related to resource
design of the PHY/MAC layers also becomes easier allocation problems with DRL approaches [488]. Due to
since there is less algorithm/protocol design needed. the immaturity of this field of research, major efforts are
Moreover, less standardization is required mainly due needed in all of these directions in the future, including
to the reduction in the PHY/MAC layer options and AI/ML assistance from smaller to larger entities.
parameters. Ultimately, the pervasive use of AI/ML for The AI/ML-assisted air interface has been reviewed in
the air interface would be a major paradigm shift and the recent literature [183], [186], [487], [489]–[500]. In
revolutionize the way how mobile networks are designed, general, these surveys cover the main literature, recent
standardized, operated, and deployed [487]. To this end, advances, and open challenges. Most studies considered
there are major challenges ahead. PHY layer design using DL [183], [186], [490]–[497],
In general, 6G presents many challenges for the design of [499], [500]. These DL works can be further divided
the air interface due to the significantly increased network into the 6G-specific [183], [186], [499], B5G/5G-specific
complexity and tightened requirements. Specifically, there [495], [497], and generic surveys [490]–[494], [496],
will be a massive number of diverse types of devices with [500]. Additionally, federated learning was reviewed for
numerous service classes, extremely high QoS require- the PHY layer in [498]. The design of the MAC layer
ments, integrated terrestrial and non-terrestrial networks, functions was discussed in [487], [489], [494]. The work
converged communication and beyond-communication [487] provided a vision toward an AI/ML-native 6G
technologies, and a wide range of application scenarios. air interface, ideally enabling optimized communication
Even though AI/ML is seen as one of the key enablers schemes for any hardware, wireless environment, and
corresponding to these 6G challenges, it will be highly application. The paper described the main transition
challenging to practically implement pervasive AI/ML for phases on the road to achieving AI/ML-nativeness and
every level of the network, including the air interface. discussed the needed PHY/MAC layer learning proce-
The main challenges of implementing an AI/ML- dures. In [489], the authors introduced a framework for
enhanced air interface are related to rapidly varying chan- an AI/ML-enabled 6G air interface, covering PHY/MAC
nel conditions, a vast variety of wireless environments, layer designs and interactions with the higher layers.
stringent and diverse QoS requirements, data collection, Major research efforts are required in the near future to
heterogeneous network architecture, multiple resource realize the vision of an intelligent 6G air interface. The
dimensions, and massive network access. Hybrid offline- corresponding challenges were discussed earlier. In par-
online learning is a vital element to tackle the challenge ticular, the 6G-specific characteristics and requirements
of providing accurate training that matches well with the must be properly addressed in the design of AI/ML-
real-world channel conditions and environments. Extreme enhanced air interface.
latency and reliability targets also set high requirements
for the AI/ML-based solutions, calling for parallel com-
puting and accurate training. F. Beyond-Communication Technologies for 6G
Adequate data collection is a critical element for the The integration of beyond-communication technologies will
practical implementation of AI/ML-based approaches, be a major paradigm shift in the evolution of mobile networks,
particularly for the resource allocation and network ac- significantly extending the way how mobile networks can
cess problems of the MAC layer. However, this re- be exploited. The main beyond-communication technologies
quires plenty of (over-the-air) signaling between dif- include computation, sensing, and energy, as shown in Fig-
ferent network nodes. Integrated satellite-air-ground ac- ure 30. Currently, 5G networks have adopted edge comput-
cess and communication-computation-sensing-energy re- ing capabilities and enhanced positioning in its palette of
sources further complicate the design of AI/ML-based technologies. This paves the way for the broader usage of
MAC and higher layer functions and interactions between beyond-communication technologies in the 6G era. Beyond-
them. Overall, efficient AI/ML-aided air interface solu- communication technologies are expected to enable a broad
tions are needed, which take the special characteristics range of novel capabilities and applications for 6G. In the
of 6G into account, in cooperation with higher layers. following, we discuss integrated communication, computation,
Further discussions on the specific PHY and MAC layer and caching (i3C), ISAC, and WET. These technologies are
challenges and future guidelines can be found in [487], summarized in Table IX.
[489].
 53

TABLE IX
S UMMARY OF BEYOND - COMMUNICATION TECHNOLOGIES FOR 6G

Beyond-
Communication Vision Description Opportunities Challenges Past Present
Technologies

Integrated
Communication, Freeing synergy Expanded 3C resource Research since 5G edge
Computation, and Joint design of 3C
between 3C capabilities management mid-2010s computing
Caching

Integrated Sensing
and Perceptive 6G Joint radio Ubiquitous Trade-off between Research since Under study for
Communication networks sensing and comm network sensing S&C performance late 2010s 6G

Wireless Energy Powering IoT Electrical energy Efficiency & Decades of Under study for
Transfer Sustainable IoT
sensors/devices over-the-air distance research mobile networks

• Opportunities and Challenges: The potential benefits

which i3C offers to future mobile networks include
COMPUTING extended capabilities, enhanced performance, and novel
applications [501], [502]. Caching enables bringing popu-
lar content to the network edge and closer to end-devices,
reducing latency and communication overhead. Advanced
6G BEYOND computing and processing enable bringing more intelli-
COMMUNICATION gence to the edge, enhancing network management. The
main performance enhancements of i3C are lower latency,
higher data rates, and better energy efficiency. i3C can
ENERGY SENSING play a key role in diverse future applications, such as
immersive XR, smart city/factory, and intelligent vehicle
systems. Due to its potential, i3C is expected to become
an integral part of 6G networks [502].
Fig. 30. Beyond-communication technologies for 6G. Before the practical implementation of i3C is possible,
diverse challenges must be resolved. Key challenges are
1) Integrated Communication, Computation, and Caching: related to heterogeneity, resource management, latency
requirements, real-time analytics, mobility, security, and
privacy [501], [502]. In the 6G era, the heterogeneity
• Vision: Communication, computation, and caching (3C) of networks, devices, and applications makes the joint
integration is considered as one of the key technologies design of 3C challenging, calling for novel solutions. In
for 6G networks, exploiting the synergy between 3C particular, resource management and allocation become
capabilities at the network edge. more complicated due to multiple resource types and
• Introduction: i3C refers to the joint design of 3C tech- their diverse performance requirements. A major chal-
nologies at the edge of the network [501]. Through joint lenge is to satisfy the stringent performance requirements
design, 3C technologies can be used to benefit each other, of future services and applications, especially minimal
enhancing the performance and extending the capabilities latency. Due to the complexity of i3C networks, real-
of mobile networks. Consequently, i3C enables novel time analytics and processing are difficult in practice.
services and applications. i3C is considered a major Mobility management also becomes trickier since neigh-
paradigm shift in the design of mobile networks [502]. boring BSs may have different 3C capabilities, affecting
• Past and Present: In the literature, i3C started to gain service quality. Since the introduction of i3C exposes
increasing interest after the mid-2010s. Early studies mobile networks to the new types of threats and attacks,
focused on applying i3C to 5G networks. Back then, the novel security and privacy solutions need to be developed.
novel concepts of softwarization, virtualization, and edge AI/ML has been recognized as a promising tool for
computing played key roles in i3C research [501]. At the addressing many of the aforementioned issues [502]. The
end of the 2010s, research started to shift toward 6G, with fundamental challenges and future topics of i3C have
a focus on AI/ML-assisted i3C. Although 5G networks been discussed in [501]–[503].
support SDN, NFV, and edge computing technologies, • Literature and Future Directions: In the literature, i3C
i3C is still too immature for large-scale usage in practice.
 54

has been actively studied since the mid-2010s. Recent [507], [508]. There are three types of ISAC design:
survey papers have reviewed the latest achievements and communication-centric, radar-centric, and joint optimiza-
related literature [501]–[506]. In [501], a survey was pro- tion [508], as shown in Figure 32. The communication-
vided on mobile edge networks from the perspective of centric design refers to merging radio sensing functions
the 3C convergence. Computing and caching at the edge into wireless communication systems, whereas the radar-
were first reviewed individually, and then the synergy centric design merges communication functions into radar
between the 3C technologies was discussed. The work systems. In the joint optimization design, there is no
[504] discussed FL-assisted MEC, communication, and bias toward the underlying systems, but the system can
caching to provide more intelligence to the network edge. be jointly optimized to meet the needs of the desired
In [505], 3C resource sharing was explored for D2D IoT applications.
scenarios. The authors in [506] presented a review of the In the context of mobile networks, ISAC refers to joint
3C convergence in IoT. In [502], a comprehensive survey radio sensing and communications using the same cel-
was provided on the integration of 3C and control (i4C) lular spectrum and network infrastructure, sharing the
for beyond 5G networks. The study [503] gave a thorough majority of hardware and signal processing modules
discussion on i3C in terms of cloud-edge cooperation, [509]. This concept is also known as the perceptive
resource management, and intelligence. mobile networks [509]. In the perceptive networks, radio
Further research is needed in the near future before large- sensing is profoundly fused into mobile networks, greatly
scale usage is possible. In addition to solving the chal- expanding network capabilities and enabling ubiquitous
lenges discussed earlier, the main future directions are sensing services and applications. Radio sensing refers to
related to AI/ML-aided i3C/i4C, for example, DL/FL as- the retrieval of information from the surrounding environ-
sistance, big/small data analytics, and real-time decision- ment through the received radio signals and the measure-
making. Further details on the future research directions ments of sensing parameters (such as angle of arrival,
can be found in [502]. angle of departure, time delay, and Doppler frequency)
and feature parameters (such as the pattern signals of
objects, activities, and events) [508], [509]. There are
three types of cellular radio sensing, i.e., downlink active
sensing, downlink passive sensing, and uplink sensing
[509]. While downlink sensing signals are from the BSs,
uplink sensing signals originate from the UEs. Active and
passive sensing refer to the signals transmitted from the
BS and other nearby BSs, respectively.
Radio sensing enables a broad range of novel capabilities
for mobile networks, including the detection (size, shape,
material, flaw), recognition (gesture, activity, event), lo-
calization (indoor/outdoor), mapping (2D/3D), tracking
(industrial, environmental, consumer), imaging (biomed-
ical, security), and monitoring (health, medical, security,
Fig. 31. Joint sensing and communication in a cellular environment. environmental, industrial, agricultural) of objects and
entities [507], [508], [510]. As there are many similarities
between sensing and communication, they can be inte-
2) Integrated Sensing and Communication: grated into mobile networks, sharing the same wireless
• Vision: ISAC is considered a revolutionary technology resources [507], [508]. The integration is becoming more
for 6G, expanding the services and applications of mo- natural since radars and communications have evolved in
bile networks beyond traditional communication toward the same direction, i.e., toward higher frequencies with
ubiquitous sensing. larger bandwidths and larger-scale antenna arrays with
• Introduction: ISAC refers to the integration of radio higher array gains. This development path has provided
sensing and communication capabilities into the same more resources in the spectral and spatial dimensions,
wireless system [507], as illustrated in Figure 31. Al- leading to increased capacity and connection density in
though radio sensing and communications are different communication systems and improved range and accu-
technologies with distinct objectives, they have similar- racy in radar sensing systems. Moreover, the development
ities in hardware and signal processing designs, making of mobile networks toward denser cell deployment and
it possible to integrate them into one system in a cost- pervasive AI/ML will further enhance the integration of
, energy-, and spectrum-efficient manner [507], [508]. sensing and communication.
ISAC is also known by different names, such as radar- Due to the sharing of wireless resources and mutual assis-
communication, joint radar and communication, joint tance between sensing and communication, cellular ISAC
communication and radar, dual-functional radar com- provides diverse benefits compared to the separated sens-
munication, joint (radar/radio) sensing and communica- ing and communication systems. In other words, these
tion, and joint communication and (radar/radio) sensing benefits originate from the integration and coordination
 55

• Opportunities and Challenges: Ultimately, the potential

ISAC of ISAC is to realize the concept of perceptive network by
DESIGN
turning mobile networks into a ubiquitous sensing entity
(i.e., ”network as a sensor” [509]), with a vast variety of
innovative services and applications. As this grand vision
COMMUNICATION- RADAR- JOINT significantly extends the capabilities of mobile networks,
CENTRIC CENTRIC OPTIMIZATION
it opens new business opportunities for mobile network
operators and vertical industries. Due to the synergy be-
tween sensing and communication, cellular ISAC is seen
BIAS TO BIAS
NO BIAS as a key technology to be exploited in many future appli-
COMMUNICATION TO RADAR
cation scenarios, ranging from immersive context-aware
human-machine interactions and smart factory/city/home
Fig. 32. Main types of ISAC design. environments to intelligent vehicle/transportation systems
and e-health/energy/agriculture [507], [508].
gains, defined in [507]. The integration gain originates In addition to expanding the capabilities of mobile net-
from the sharing of the same wireless network resources works, ISAC also offers other benefits. Compared to
between sensing and communication, providing improved two separated systems, integrating communication and
spectrum, energy, size, and cost efficiency. The coordina- sensing into the same system provides direct benefits
tion gain is achievable through mutual assistance between in terms of spectrum, energy, and cost efficiency [507].
sensing and communication, that is, communication- Additional benefits are achievable through mutual assis-
assisted sensing and sensing-assisted communication. For tance between communication and sensing, potentially
example, the coordination gain may appear in terms of leading to performance improvements in beamforming,
improved beamforming and sensing efficiency/accuracy. resource allocation, PHY layer security, and sensing
Due to the different nature of sensing and communica- efficiency/accuracy [507]. Due to its potential, ISAC is
tion, cellular ISAC has certain shortcomings in practice expected to become a revolutionary element for 6G,
[509]. First, ISAC requires a full-duplex operation or providing sensing capabilities in mobile networks [507],
equivalent. Second, the sensing distance may be limited [512].
due to the limited transmission power of the cellular Due to the infancy of the cellular ISAC concept, diverse
BS. Third, performance trade-offs exist between sensing unresolved issues and design challenges exist on the way
and communication due to their conflicting targets and toward the commercialization of perceptive networks with
requirements. Typical trade-offs are defined as the PHY ubiquitous sensing capabilities [507], [508], [510]. First,
layer, spatial degrees of freedom, and cross-layer trade- the previously mentioned drawbacks of ISAC need to
offs, which are further discussed in [507]. be properly addressed, i.e., developing practical solutions
• Past and Present: Although ISAC is a new topic in the for full-duplex or equivalent operation, compensating for
context of mobile networks, integrating communication limited sensing ranges when needed (e.g., by cooperat-
into radar sensing systems has been studied since the ing among neighboring BSs), and thoroughly studying
1960s [507]. Since then, ISAC research was dominated fundamental performance trade-offs between sensing and
by the radar community for a long time. In the 2010s, the communication to fully understand their nature and find
integration of radar/radio sensing into wireless commu- a suitable balance between the performances in potential
nication systems started to gain considerable interest in cellular application scenarios. As communication is the
the wireless community. It was until the introduction of primary function, it has the highest priority in the design
the perceptive mobile network concept in the late 2010s of cellular ISAC networks. In this regard, a critical
[509] that the wireless community noticed the game- challenge is to integrate sensing without compromising
changing potential of ISAC for future mobile networks. communication performance.
Recent advances in mobile networks and radar systems Other essential challenges are related to the fundamental
have made the vision of a perceptive network possible. performance bounds, joint waveform/array optimization,
In particular, the development toward larger-scale antenna clutter suppression, and sensing parameter estimation
arrays, higher frequencies with wider bandwidths, denser [507]–[509], [513]. The characterization of information-
cell deployments, and pervasive AI/ML are the key ele- theoretical limits on cellular ISAC is largely unknown,
ments to enable the beneficial integration of radar/radio which limits the understanding of the theoretical foun-
sensing into mobile infrastructure. dations of perceptive networks. Deriving performance
Currently, ISAC is one of the key 6G topics in bounds is far from trivial due to the special characteristics
academia, industry, and standardization. For example, of mobile ISAC. For example, significant differences
ITU-R considers ISAC as one of the emerging technology between sensing and communication signals lead to fun-
trends/enablers for IMT-2030 [35], [36]. Recent survey damental performance trade-offs, which have a critical
papers provide further details on the history and present impact on the system design. While the research work
of ISAC, from the perspectives of academia, industry, and is in progress with some existing studies [507]–[509],
standardization bodies [507], [511]. [513], it is still a widely open challenge to develop
 56

practical signaling methods that adequately satisfy the holographic ISAC [520], UAV-assisted ISAC [524], ISAC
(more or less) conflicting requirements of both functions for vehicular communication networks [518], and AI/ML-
with given priority weights (usually higher on commu- assisted ISAC [519], [527]. The 6G-oriented surveys
nication). The center of this development work is the provided comprehensive explorations of ISAC in the
joint waveform optimization and antenna array design context of 6G [507], [510]–[512], [530]–[535].
since they have quite different requirements for sensing Since the development of cellular ISAC networks is
and communication, notably affecting the performance of in a rather early phase, further research is needed in
both functions. the coming years. Some important future topics toward
In cellular ISAC networks, rich multipath environments 6G include a thorough characterization of the funda-
are challenging for sensing due to the presence of harmful mental performance limits/trade-offs, sensing-integrated
clutter [508]. Clutter refers to the unwanted multipath sig- channel models, joint waveform/signaling/array optimiza-
nals that contain only a small amount of new information. tion, compressed sensing-based clutter suppression, net-
It is vital to remove clutter signals at the receiver since worked sensing, cooperative distributed sensing, sensing-
they can significantly degrade the performance of sensing assisted mmWave/THz beamforming, pervasive AI/ML
algorithms by increasing the number of estimated sensing assistance, and sensor fusion [507], [510]–[512], [528].
parameters. Although clutter suppression has been well
studied for radar networks, it is still mostly an unresolved
issue in the context of cellular ISAC [508]. In general, WET
sensing parameter estimation is a challenging task due
to the complex signal structures in mobile networks.
Since most of the existing techniques from radar sys-
tems cannot be directly applied, many novel methods NEAR- FAR-
have recently been studied. For example, compressed- FIELD FIELD
sensing-based parameter estimation methods have shown
emerging promise, but they still have major limitations in
practice [508]. To summarize, all of the aforementioned INDUCTIVE ENERGY
topics require major advances to find proper solutions for COUPLING BEAMFORMING
their corresponding problems. Detailed reviews on these
topics and the related literature can be found in [507]–
[510], [513]. CAPACITIVE
• Literature and Future Directions: Since the late 2010s, COUPLING
ISAC has been one of the main 6G topics in the lit-
erature. Over the years, a vast range of aspects has
Fig. 33. Main categories of WET.
been studied, such as information theoretical limits,
performance trade-offs, communication-assisted sensing,
sensing-assisted communication (beamforming, resource 3) Wireless Energy Transfer:
allocation, PHY layer security), signal processing (wave- • Vision: WET is considered a revolutionary technology to
form optimization, MIMO design, receiver processing), potentially energize lightweight IoT networks in the 6G
network management (resource allocation, higher layer era.
designs), integration with other emerging technologies • Introduction: WET (also known as WPT) is a technology
(AI/ML, THz, RISs, V2X, UAVs, satellites), and potential that transmits electrical energy over the air through a
applications (smart home/factory/city/healthcare, digital wireless medium [536], [537]. WET aims to power and
twins, XR, vehicular systems, remote sensing, environ- charge wireless devices to promote autonomy, mobility,
mental monitoring, etc.). long life-time, and novel applications [536], [537]. There
The aforementioned topics and the related literature have are two main categories of WET: near-field and far-
been thoroughly reviewed in numerous surveys [228], field [538], as summarized in Figure 33. Near and far
[234], [238], [240], [507]–[535]. At a high level, these fields refer to the different regions of the electromagnetic
survey papers can be classified into three categories: field around a radiating source. In the near-field region,
generic, specific, and 6G-oriented. In [508], [509], [513], the behavior of the electromagnetic field is far different
[514], [516], [525], [528], the generic surveys discussed from that in the far-field region. While the near-field
ISAC from a wide perspective, covering topics such as behavior dominates in the close proximity of the source,
fundamentals, state-of-the-art designs, recent advance- far-field characteristics, i.e., typical electromagnetic ra-
ments, potential applications, open problems, and fu- diation, dominate at longer ranges. Due to the different
ture research guidelines. The specific surveys reviewed radiation characteristics, different types of technologies
narrower aspects of ISAC, including fundamental limits are required for WET in the near and far fields.
[513], channel modeling [529], waveform design [517], In the near-field category, energy is transferred by in-
ISAC signals [526], THz ISAC [228], [234], [238], [240], ductive coupling via magnetic fields or capacitive cou-
ISAC for IoT [515], RIS-assisted ISAC [521]–[523], pling via electric fields [538], [539]. In the near-field
 57

device called the Tesla Tower [540]. However, the exper-

iment failed. After Tesla’s experiment, it took a long time
before anything significant occurred in the field of WET.
In the late 1940s, the concept of backscatter communica-
tion was introduced [541]. Backscatter communication is
currently considered a form of the WIPT concept [536].
The most popular commercial application of backscatter
communications is radio frequency identification (RFID)
[542]. Active research on WET via microwaves began
in the 1960s, when William Brown conducted his first
Fig. 34. Simultaneous wireless information and power transfer. experiments [543]. Brown achieved a remarkable 54 %
overall efficiency in one of his laboratory experiments
technologies, the distances over which the energy can be in 1975 [540]. In the 1990s, phased arrays began to
efficiently transferred are short. Typical commercial ap- gain popularity, leading to the rise of beamforming-based
plications of the near-field WET include wireless charg- WET [540].
ing of mobile phones, tablets, smart watches, electric Over the years, WET with microwave energy beamform-
toothbrushes, electronic medical implants, and electric ing has been extensively studied. Traditional research has
vehicles, to mention a few. mainly focused on the RF aspects, while recent studies
In the far-field category, energy is typically transferred by have expanded to signal and system designs as well, with
focusing electromagnetic radiation, such as microwaves, a special focus on integrating WET into future wireless
toward the dedicated receivers via directive transmissions networks [536]. In this respect, the concept of SWIPT
[537], [540]. This technology is known as energy beam- started to gain interest in the 2010s [544]. Currently,
forming (power beamforming) [537]. Energy beamform- WET is being studied for 6G networks, with a special
ing aims to provide efficient energy transfer over rela- emphasis on energizing low-power IoT devices [537].
tively long ranges, much greater than that of the near-field While there exist no large-scale commercial applications
technologies. However, the operating efficiency, i.e., the of the far-field WET, there are some in the near-field
portion of the transmitted energy received, decreases with domain, such as wireless chargers for wireless/mobile
the radiation distance. Thus, achieving efficient energy devices, electronic medical implants, and electric vehi-
transfer over long ranges is a fundamental challenge in cles. Although WET has been extensively studied over
the far-field technologies. A typical application proposed the decades, with some commercialized products, it is
for the far-field WET is the powering of lightweight IoT far from maturity. From a regulatory perspective, ITU-
devices [537]. More details on the energy beamforming R published its first report on radio-frequency WET
can be found in [537]. in 2016, with an updated version in 2021 [543]. This
While the traditional concept of WET is considered sepa- report focuses on the possible applications of WET via
rately from wireless communication systems, a relatively radio waves, corresponding technologies, and candidate
new idea is to transfer both energy and information simul- spectrum bands.
taneously using the same network [536], as illustrated in • Opportunities and Challenges: WET has great potential
Figure 34. This concept is known as wireless information to revolutionize wireless ecosystems and expand the
and power transfer (WIPT), which can be divided into capabilities of wireless networks beyond communications
three categories: simultaneous WIPT (SWIPT), wireless by wireless charging and powering electric devices, par-
powered communication networks, and wireless powered ticularly low-power IoT sensors. In particular, WET is
backscatter communication [536]. In the first category, considered a key enabler for sustainable IoT in the 6G era
information and energy are simultaneously transferred by promoting the long life-time, mobility, and autonomy
from one or many transmitters to one or many receivers. of devices [537]. There are many design challenges in
There are two types of receivers: information receivers the path toward efficient and ubiquitous WET as an
and energy receivers [536]. Information and energy re- integral part of future wireless networks. The fundamen-
ceivers can be co-located in the same device or separated tal challenges are mainly related to efficiency, distance,
into different devices. In the second category, downlink availability, mobility, and safety [536]. These elements
transmissions are used for energizing devices, whereas are crucial for integrating WET into mobile networks.
devices use this energy to transmit information in the The seamless integration of wireless energy with commu-
uplink. In the third category, the downlink is for energy nication, computation, sensing, and positioning is a major
and uplink for information, while the devices are low- challenge that requires multidisciplinary research efforts
power, low-complexity tags that directly modulate the [536]. Further challenges arise from the trends toward 6G,
downlink signals by their own information without the such as higher frequencies, larger number of antennas,
need to generate carrier signals by themselves. denser networks, greater number of devices, and a higher
• Past and Present: The earliest studies on WET date back level of intelligence. On the other hand, by overcoming
to the end of the 19th century, when Nicola Tesla con- the aforementioned design challenges, integrated WET
ducted a wireless high-power experiment using a massive may enable many novel applications, such as the wire-
 58

less powering of low-power IoT, lightweight autonomous reasonable for 6G purposes, i.e., from meters to tens of
systems, crowd sensing, and distributed EI [536]. meters. More experiments are needed in the context of 6G
• Literature and Future Directions: WET has been stud- technological trends, such as higher frequencies, a larger
ied for decades in the literature. Traditional research has number of antennas, and a greater number of low-power
mainly focused on the RF design aspects, with a special devices.
emphasis on the energy receiver [545]. Since the early In the system design, special research efforts need to
2010s, signal and system designs have gained more inter- focus on a paradigm shift in which wireless networks
est [545], particularly in the context of integrating WET integrate energy, communication, computation, sensing,
into future wireless networks [536]. In the literature, there and positioning. There are some emerging technologies
are lots of survey articles which cover a wide range which can be used to aid WET and expand its capabilities,
of aspects on WET [531], [536]–[538], [544]–[553]. An such as RISs [548] and UAVs [547]. RISs can be used
overview of wireless powered communication networks to improve efficiency and increase range, whereas UAVs
was presented in [546]. The focus was on basic architec- can provide flexibility and availability. Further research
tures, key technologies, and future extensions. The con- is needed in these promising directions. Other interesting
cept of SWIPT was meticulously reviewed in [544]. The future directions include wireless powered 6G systems,
studied aspects include basics, interference exploitation, such as massive lightweight IoT networks [537].
emerging technologies, and future challenges. The work While most of the future research directions are focused
[545] reviewed WIPT from the perspectives of RF, signal, on the far-field studies, also the radiating near-field WET
and system designs. In [538], a survey was provided is an active research area for 6G purposes [551]. As
on non-radiative near-field WET, covering fundamentals, the far-field energy transfer suffers from relatively low
challenges, metamaterials, and applications. In [537], the efficiency, radiative near-field technologies may provide
authors studied massive WET for sustainable IoT in the some benefits in certain scenarios, especially with higher
6G era. A detailed discussion was given on the system frequencies and a larger number of antennas. In this direc-
architecture, applications, technological enablers, energy tion, far-field studies may no longer be valid, thus many
beamforming schemes, and future directions. aspects of energy beamforming need further research,
In [536], WPT was studied for future networks from the such as channel estimation, beam design, and waveform
perspectives of signal processing, ML, computation, and design [551]. In addition, a rethinking of SWIPT is
sensing. This comprehensive review covered challenges, needed, as radiating near-field characteristics may provide
key technologies, rate-energy trade-off, system design benefits in some scenarios [551]. Additionally, the use of
methodologies, and wireless-powered IoT. In [547], a tu- metasurfaces to aid near-field energy beamforming is an
torial overview was provided on UAV-enabled WET. The interesting topic for future research [550].
main topics included single- and multi-UAV scenarios as
well as UAV-enabled wireless powered communication
G. Energy-Aware Technologies for 6G
networks and mobile edge computing. In [548], the
authors presented an overview of the RIS-aided WIPT. As the absolute energy consumption is constantly growing,
In [549], the work reviewed the theory, prototypes, and it is of utmost importance to further improve the energy
experiments on WPT, with and without simultaneous efficiency of mobile networks. In this respect, developing more
information transfer. Metamaterials and -surfaces were efficient energy management technologies is one of the main
explored for WPT and energy harvesting in [550]. In goals and challenges of 6G. In this section, we focus on three
[551], the near-field WPT was considered in the context energy-aware technologies: green networks, energy harvesting
of IoE for 6G. The paper [552] discussed simultaneous (EH), and backscatter communications. These technologies are
lightwave information and power transfer for 6G in terms summarized in Table X.
of transceiver architectures, optical beam propagation, 1) Green Networks:
design trade-offs, synergy with other emerging technolo- • Vision: 6G networks are anticipated to be highly energy
gies, and application scenarios. In [531], the authors efficient at all levels of the network, providing ecological
discussed a multi-functional 6G, with the integration of and economic benefits.
sensing, communication, and energy. The study [553] • Introduction: Green mobile networks aim to alleviate
reviewed the design of WIPT and its fusion into 6G energy overhead and reduce the negative environmental
networks. impact caused by mobile networks [554]. Green com-
Although WET has been studied for decades, it is far munication and networking focus on reducing energy
from its true potential. Further research is needed in all consumption through energy-efficient design at different
areas from the fundamentals and experiments to system levels of the system, including the network, communi-
design and emerging technologies. In particular, 6G with cation, and device levels, as summarized in Figure 35.
its novel technologies and application scenarios brings At the network level, the main trends include temporally
new opportunities and challenges that need to be widely powering down underutilized parts of the BSs (e.g., parts
addressed. In the fundamentals category, more studies of the transmission equipment), virtual resource sharing
are needed in the RF design to further improve energy among operators, and energy-aware network management
transfer efficiency and increase distances to be practically approaches. At the communication level, the focus is
 59

TABLE X
S UMMARY OF ENERGY- AWARE TECHNOLOGIES FOR 6G

Energy-Aware
Vision Description Opportunities Challenges Past Present
Technologies

Sustainable 6G Energy-efficient Ecological and High energy Research since Energy-efficient

Green Networks
networks design at all levels economic benefits consumption early 2010s design in 5G

Energy Harvesting Sustainable External energy Lightweight IoT Efficiency & RF-EH research Under study for
lightweight IoT collection devices consumption since 2000s mobile networks

Backscatter Autonomous External energy to Battery-free low Low rates & short Concept invented Under study for
Communications low-power IoT transmit data power IoT devices distances in 1940s mobile networks

and practice. Consequently, 5G supports many energy-

EE DESIGN efficient approaches, such as massive MIMO, ultra-lean
carrier design, and sleep modes [556]. More information
on the energy-efficient technologies used in 5G RAN is
given in [556]. In the late 2010s, the focus of research
NETWORK COMMUNICATION DEVICE started to shift toward green 6G networks [562].
LEVEL LEVEL LEVEL
• Opportunities and Challenges: In the big picture, the in-
formation and communication technology (ICT) industry
is a major electricity consumer, causing massive usage
POWERING ENERGY-AWARE
DOWN PARTS RESOURCE
SLEEP TIME of fossil fuels and high energy costs [554], [557]. The
OPTIMIZATION
OF BSs ALLOCATION total energy consumption of the ICT industry is exponen-
tially growing since the volume of network infrastructure,
number of devices, and amount of data and comput-
LIGHTER ENERGY-AWARE
MANAGEMENT TECHNOLOGIES
TX POWER ing are constantly increasing [554], [557]. Since mobile
OPTIMIZATION
PROTOCOLS (RIS-GFMA-EH) networks comprise a major part of the ICT industry,
green communication and networking technologies are
Fig. 35. Energy-efficient design at different levels of green mobile networks. vital for alleviating this problem [554], [557]. Diverse
opportunities and challenges exist in the design of green
mobile networks. The potential of green design in the 6G
on enhancing resource allocation in frequency, time, era is to significantly reduce the annual growth rate of
space, power, and code dimensions, utilizing energy- the total energy consumption of mobile networks. Thus,
efficient technologies (e.g., RISs, grant-free access, EH, green 6G networks are expected to provide ecological
and backscatter communications), and designing energy- and economic benefits by reducing fossil fuel usage and
aware PHY layer techniques. energy costs [554].
At the device level, greener approaches are particularly Diverse challenges must be resolved to obtain the po-
needed for transmission power and sleep time optimiza- tential benefits of green networks in practice. Mobile
tion. The aforementioned green design aspects have been networks are becoming more complex and heterogeneous,
discussed in detail in [554]–[558]. In addition to the with more resources, leading to more energy consuming
environmental impact, there is also an economic incentive networks. 6G is expected to utilize macro, small, and tiny
since decreasing the energy overhead reduces energy BSs, as well as aerial/space APs. Moreover, the main
costs as well. As the overall energy consumption of 6G resources are expected to be communication, compu-
mobile networks is constantly growing, it is of utmost tation, caching, sensing, and energy. This heterogeneity
importance to develop novel energy-aware approaches for makes the design and management of green networks
6G networks. AI/ML is expected to play a key role in challenging. AI/ML is seen as a key tool to alleviate
green 6G networks [554]. the design of green 6G networks [554]. Possible energy
• Past and Present: Due to increasing energy costs and savings can be attained via AI/ML-optimized energy-
environmental impact, energy efficiency has been one of aware network/resource management, network node co-
the key design principles in modern mobile networks. The operation/signaling, relaying, traffic/routing control, user
concept of green networks dates back to the early 2010s scheduling, resource allocation, and mobility manage-
[559]. This research boomed during the 2010s, with the ment [554]. Pervasive AI/ML itself is energy-aggressive
main focus on green 5G networks [560], [561]. Green since it requires lots of computation power. Thus, it is an-
5G networks have been intensively studied in theory
 60

other challenge to design energy-efficient and lightweight

AI/ML approaches [554]. Further details on the opportu- RADIO
FREQ
nities and challenges of green mobile networks can be
found in [554], [557].
• Literature and Future Directions: Recently, several PRESSURE SOLAR
surveys have been published on green communication and
networking for 6G, reviewing the latest research progress
and related literature [554], [555], [557], [558], [562]–
[565]. In [562], a survey was provided on green 6G EH
networks. The focus is on network architectures (space- SOURCES
air-ground-sea, intelligence network, new network pro- VIBRATION KINETIC
tocol stack) and promising technologies (THz/VLC, EH,
molecular/quantum communication, blockchain-based se-
curity, intelligent materials). In [555], the authors dis-
cussed greener PHY layer technologies for 6G, analyzing
the joint energy-spectral efficiency design in NOMA and
WIND THERMAL
waveform overlapping multiple access frameworks. The
work [563] reviewed green-UAV communications for 6G
in terms of power consumption models, trends, enabling Fig. 36. Typical energy sources for energy harvesting.
techniques, applications, and open research problems.
In [554], a comprehensive review was presented of AI
models for green communication toward 6G networks. In while the drawback is the possible availability and energy
this framework, the work considered the existing litera- level issues. In the dedicated RF-EH, dedicated energy
ture, 6G paradigms, AI models, mobile network commu- transmitters are used to transfer energy to the EH de-
nications, MTC, computation-oriented communications, vices. This enables guaranteed availability and energy
and open research challenges. The authors of [557] levels. Typical application scenarios of RF-EH include
explored greener 5G/B5G access networks, focusing on low-power IoT networks, wireless sensor networks, and
energy consumption modeling, energy-efficient network wireless-powered communication networks.
architectures, technological evolution, and network shar- RF-EH networks can be divided into centralized
ing. The paper [564] provided a thorough discussion (infrastructure-based) and decentralized (infrastructure-
on sustainable 6G toward greener networks. In [558], less) architectures, as introduced in [539]. A typical
[565], the surveys discussed 6G green communication in centralized architecture consists of three main elements:
terms of zero-energy devices, focusing on technological information gateways (BSs), energy sources (dedicated or
enablers. Although AI/ML has been widely studied for ambient), and network nodes (devices) [539], as shown
green 6G networks since the late 2010s, major efforts are in Figure 37. The key components of an RF-EH device
still needed for practical realizations in the near future. include an RF energy harvester, power management mod-
As discussed earlier, at the center of future research is ule, energy storage, application, lightweight microcon-
AI/ML-optimized green designs at all levels of the 6G troller, and lightweight RF transceiver [539]. Typically,
networks [554]. an RF energy harvester comprises an antenna, impedance
matching module, voltage multiplier, and capacitor [539].
2) Energy Harvesting:
The aforementioned EH architecture is known as harvest-
• Vision: EH has been recognized as a promising tech- store-use. Another main class is a harvest-use architecture
nology for promoting energy-constrained, low-power, and that lacks the capability of storage. This leads to a
sustainable IoT networks in the 6G era. reduced cost of EH devices.
• Introduction: EH is defined as a process in which energy • Past and Present: RF-EH has been actively researched
is collected from external sources in order to promote the since the 2000s, with the main focus on wireless sensor
autonomy, mobility, and sustainability of wireless devices networks. In the 2010s, RF-EH for cellular network
and networks [554]. Typical external energy sources are applications (e.g., IoT) began to receive more attention in
RF, solar, kinetic, thermal, wind, vibration, and pressure the wireless community. Currently, the focus of cellular
[554], as illustrated in Figure 36. Due to its properties, RF-EH research is on 6G, with special interest in energy-
RF energy is well-suited for mobile network applications, limited IoT networks. Although commercialized RF-EH
such as low-power IoT. Thus, the focus is on RF-EH solutions exist, RF-EH is still too immature for large-
from now on. RF-EH can be divided into two types: scale use in cellular networks.
ambient and dedicated [539]. In the ambient RF-EH, • Opportunities and Challenges: RF-EH offers many new
energy is harvested from existing radio signals, such as opportunities for mobile networks to advance sustainabil-
cellular communications, television broadcasts, and WiFi ity, autonomy, and mobility. Ultimately, RF-EH acts as
connections. The benefit of ambient RF-EH is that no a key enabler for the large-scale usage of lightweight
dedicated infrastructure is needed for energy sources, communication networks in the 6G era, such as different
 61

for advanced antenna and circuit designs. Further studies

RF-EH are required to obtain and maintain an appropriate level
ARCHITECTURE of harvested power density in the devices, especially in
mobile environments. Moreover, the locations of dedi-
cated energy transmitters need to be properly determined
INFORMATION ENERGY NETWORK to ensure fairness among EH devices. More experiments
GATEWAYS SOURCES NODES are also required in realistic environments to validate the
performance of RF-EH systems. Further details of the
aforementioned issues and future directions can be found
BASE in [539], [566].
DEDICATED DEVICES
STATIONS

BACKSCATTER
AMBIENT

Fig. 37. Three main elements of a centralized RF-EH architecture. MONOSTATIC BISTATIC AMBIENT

types of energy-limited IoT and sensor networks. There

DEDICATED DEDICATED
are still many technological obstacles to overcome before AMBIENT RF
SOURCES SOURCES
RF-EH can become a mainstream technology in mobile SOURCES
(COLOCATED) (SEPARATED)
networks. The main challenges of RF-EH are related to
the optimization of energy conversion efficiency, energy Fig. 38. Three main types of backscatter communication systems.
consumption, distance between energy sources and har-
vesters, operating frequency, locations of the dedicated
energy sources, and operational/capital expenses [539], 3) Backscatter Communications:
[566]. • Vision: Backscatter communication is seen as a promis-
• Literature and Future Directions: In recent years, a ing technology to provide low-power, low-complexity,
handful of survey papers have been published, discussing and low-cost communication systems for 6G, enabling
different aspects of RF-EH and reviewing recent ad- lightweight IoT networks.
vances [566]–[572]. RF-EH-based metasurface structures • Introduction: A typical backscatter system consists of
were reviewed in [567]. RF-EH and metasurfaces were three main elements, including an RF signal source
first considered separately, and then RF-EH antenna and (i.e., an emitter carrier), a backscatter transmitter, and
rectenna designs based on metasurfaces were discussed. a backscatter receiver [542]. The basic principle of
The work [568] reviewed security in EH networks from backscatter communications is that the backscatter trans-
the perspective of threats/attacks, PHY layer secrecy, mitter absorbs RF signals from an external source, mod-
lightweight cryptography, and additional PHY layer coun- ulates the signals with its own encoded data, and reflects
termeasures. In [566], the authors provided a comprehen- the modified signals toward the backscatter receiver,
sive review of RF-EH, discussing applications, evaluation which decodes and extracts the desired information from
metrics, energy propagation models, rectenna architec- the received signals [542]. A key feature of backscatter
tures, MAC layer protocols, open challenges, and future communication is that the backscatter transmitter does not
directions. Another comprehensive survey of RF-EH was need to generate RF signals by itself [542]. As a result,
presented in [569]. This study reviewed many topics, the low-complexity backscatter transmitters can operate
including RF-EH systems, techniques, principles, eval- with minimal power and be implemented at low cost.
uation metrics, environments, circuits, and applications. The goal of backscatter communications is to provide
In [570], RF-EH was briefly discussed in the context of low-power, low-complexity, and low-cost communication
next-generation IoT devices. The paper [571] studied RF- systems for different types of application scenarios, typ-
EH techniques for low-energy devices in the context of ical ones ranging from RFID systems to sensor and IoT
IoT, industry 4.0, and wireless sensing. The authors in networks.
[572] examined multi-directional rectennas in RF-EH. In There are three main types of backscatter communication
[573]–[576], the generic surveys explored EH in terms of systems: monostatic, bistatic, and ambient [542], as sum-
different energy sources. marized in Figure 38. The monostatic system consists
Since RF-EH is still far from its potential, significant of two main components, i.e., a backscatter transmitter
research efforts are needed in the future. Therefore, and a reader device that contains an RF source and
it is vital to address the main challenges mentioned a backscatter receiver [542]. Since the receiver is in
earlier. For instance, improvements in the conversion the same device as the RF source, monostatic systems
efficiency and energy consumption of EH devices call suffer from a round-trip pathloss and the doubly near-far
 62

problem, limiting communication ranges and data rates. found in [542], [577], [578], [582]–[584]. For example,
Typical usage scenarios of the monostatic systems are performance comparisons were provided among a set
short-range RFIDs applications. In the bistatic system, the of backscatter systems in [582], [584]. In particular,
dedicated RF sources are separated from the backscatter the transmission powers, data rates, and communication
receivers, avoiding the round-trip pathloss and doubly ranges were compared.
near-far problems. This leads to improved system per- • Opportunities and Challenges: There are many benefits
formance, coverage, and flexibility. in backscatter communications, offering lots of opportu-
The ambient backscatter systems exploit existing wireless nities for future wireless systems. However, backscatter
systems, such as cellular networks, WiFi, and television communication has some shortcomings, placing many
broadcasts as the RF sources [542]. In contrast to the obstacles on the road toward large-scale practical deploy-
bistatic approach, ambient systems do not require any ments. Due to its inherent nature, backscatter communica-
dedicated spectrum or RF sources for communication, tions support energy-constrained lightweight wireless sys-
leading to improved spectral, power, and cost efficiency. tems [542]. As a result, the backscatter concept is seen as
However, ambient RF signals are uncontrollable and a promising approach to realize sustainable IoT applica-
unpredictable, leading to more complicated system de- tions in the 6G era [578]. Potential application scenarios
sign and unstable performance. Nevertheless, the am- include smart environments, healthcare, logistics, retail,
bient backscatter communication concept is the most health monitoring, and sport innovations, to mention a
evolved and promising one to be utilized in 6G for low- few. For example, backscatter-based sensor networks can
power, low-complexity, and low-cost communication sce- be used to detect toxic gases, carbon dioxide, smoke,
narios, enabling applications such as energy-constrained and movement in smart homes, offices, and buildings.
battery-free IoT networks [577], [578]. A comprehensive Backscatter communication is also applicable to logistics,
overview of the backscatter communications systems is warehousing, and retailing for tracking, identification, and
presented in [542]. monitoring. In health and sport monitoring, backscatter
• Past and Present: The concept of backscatter commu- approaches can enable in-body, on-body, and wearable
nication was first introduced in the late 1940s [541]. sensor networks. Further details on the aforementioned
Later on, this innovation has contributed to many practical application scenarios can be found in [542], [578], [584],
applications, such as RFID, remote switches, tracking [585].
devices, and medical telemetry [542]. Currently, RFID is The main shortcomings of backscatter communications
the most popular commercial application of backscatter include low data rates, short communication distances,
communications, typically used for commodity identifica- lack of strict QoS guarantees, and security issues [542].
tion in retailing and logistics. However, the applicability Since the backscatter transmitters rely on the external RF
of traditional (monostatic) backscattering is rather limited sources, their transmission powers are low, leading to low
due to its inherent constraints [542]. First, the receivers data rates and short link ranges. Due to the unpredictabil-
and RF sources are in the same device. Second, the trans- ity of ambient RF signals, QoS cannot be guaranteed.
mitters must be located near their dedicated RF sources. Since the backscatter transmitters and receivers are low-
Third, the backscatter transmitters can communicate only complex devices, they are prone to security attacks,
when requested by their dedicated receivers. To over- such as eavesdropping and jamming. The corresponding
come these limitations, enhanced backscatter systems, challenges are to maximize rate and range, increase ro-
i.e., bistatic [579] and ambient [580], were developed bustness, and provide secure communication. In addition,
in the early 2010s, receiving a considerable amount of other fundamental challenges include minimizing energy
research interest. consumption and cost. Since most of these objectives
The bistatic approach separates the RF sources and conflict with each other, there need to be priorities set
receivers, enabling a more flexible system design, im- and trade-offs made, depending on the purpose of the
proved performance, and extended coverage [581]. Am- system. Recent backscatter systems, aiming to tackle
bient backscatter systems go a step further by exploiting these challenges with different types of trade-offs, have
existing RF sources, such as cellular and WiFi signals. been reviewed in [542], [577], [578], [582], [584].
Consequently, their applicability is much wider than • Literature and Future Directions: Modern backscatter
that of the monostatic systems. In particular, advanced research began to gain notable attention after the introduc-
backscatter communication is seen as an enabler for tion of the bistatic [579] and ambient [580] backscatter
future low-power, low-complexity, and low-cost com- concepts in the early 2010s. Since then, backscatter com-
munication systems. Consequently, practical bistatic and munication has been studied from various perspectives
ambient backscatter systems are currently under active in the literature. This research can be divided into three
study, particularly for 6G IoT scenarios [578]. Recently, main categories: fundamentals, emerging systems, and
different types of modified backscatter concepts, with applications. The main topics in fundamental research
their own pros and cons, have been introduced, such include channel coding, modulation, channel modeling,
as multi-antenna, full-duplex, NOMA-aided, UAV-aided, channel estimation, detection, resource allocation, multi-
and RIS-aided backscatter systems. Detailed reviews ple access, performance analysis, and PHY layer security.
of the state-of-the-art backscatter approaches can be Literature reviews of these topics can be found in [542],
 63

TABLE XI
S UMMARY OF END - DEVICE - ORIENTED TECHNOLOGIES FOR 6G

End-Device-
Oriented Vision Description Opportunities Challenges Past Present
Technologies

D2D Direct comm Data off-loading Interference

Communications Ubiquitous D2D 4G sidelink 5G sidelink
between devices & power savings management

V2X Intelligent Comm bw vehicle Ubiquitous vehicle Management &

Communications 4G V2X 5G V2X
vehicular systems and any entity connectivity cooperation

Cellular UAV Freeing potential Mobile network New usages for 3D coverage & Research since
Communications 5G UAS
of UAVs support for UAVs UAVs mobility early 2010s

[578], [585], [586]. ing perspective and reviewing state-of-the-art backscatter

The research on emerging systems can be divided into systems and their performance. The authors in [586]
two main categories, i.e., new system concepts and com- reviewed backscatter communications as a solution to
binations with other emerging technologies. Several novel the limited battery life problem. The next-generation
backscatter systems have recently been proposed [582]– backscatter communication systems, techniques, and ap-
[584]. Typically, they aim to provide (relatively) high plications were surveyed in [585]. The ambient backscat-
throughput or long range with low transmission power ter concept was explored as an enabler for energizing IoT
and implementation costs. For example, the passive WiFi devices in [588]. In [583], the latest backscatter systems
and Interscatter systems achieved 11 Mbit/s data rates, were discussed in the context of IoT.
while the LoRea and LoRa backscatter concepts obtained The ambient backscatter technologies were examined
3.4 km and 2.8 km communication distances, respectively for ultra-low-energy MTC in [577]. The work in [578]
[582]. Recently, backscatter communications have been reviewed backscatter communications to enable ultra-
studied in combination with other emerging technologies massive connectivity in 6G. A comprehensive survey
[578], [587], such as MIMO, NOMA, UAVs, RISs, of the ambient backscatter technologies was presented
VLC, and AI/ML. These combinations can potentially in [584], focusing on the latest concepts proposed in
provide different types of benefits, ranging from improved the literature and providing a taxonomy for ambient
throughput or range to increased reliability. systems. The paper [587] discussed AI/ML-empowered
In the application domain, backscatter communications backscatter communications for 6G. In [589], the authors
have been studied for various scenarios, such as green explored NOMA-based backscatter systems, focusing on
IoT, ultra-low power sensor networks, smart homes, technological principles, performance optimization, and
healthcare, biomedical applications, environmental mon- potential applications. Moreover, backscatter communi-
itoring, logistics, transportation, smart cities, agriculture, cation was briefly discussed in terms of next-generation
and body-area networks. In general, backscatter systems IoT and zero-energy devices in [570] and [558], [565],
can assist in many important functions in those appli- respectively. Further work is needed in all of the afore-
cation scenarios, such as sensing, localization, tracking, mentioned areas, especially in the context of 6G and its
identification, and monitoring. Backscatter-assisted appli- unique characteristics, requirements, and applications. In
cations have been reviewed in [542], [578], [584], [585]. addition, the fundamental challenges, discussed earlier,
Since backscatter communication is a relatively immature must be properly addressed toward the 6G era.
technology in the context of mobile networks, further
research is needed on the aforementioned aspects. A
H. End-Device-Oriented Communication Technologies for 6G
special focus should be directed on the 6G applications.
Insightful surveys on backscatter communications can 6G is expected to support massive amounts of wireless
be found in [542], [577], [578], [582]–[589], from devices, vehicles, and drones, thereby setting diverse require-
which [542], [577], [584], [588] focused on the ambient ments for mobile networks. In this picture, D2D, V2X, and
backscatter systems. These papers covered a broad range cellular-connected UAV communications will play key roles.
of aspects, including fundamentals, state-of-the-art, op- Each of these end-device-related technologies is discussed
portunities, applications, challenges, possible solutions, below and summarized in Table XI.
open problems, and future topics. In [542], a generic 1) D2D Communications:
survey was presented, with the main focus on the ambient • Vision: 6G is expected to provide wide support for
and bistatic backscatter systems. A practical tutorial was D2D communications in cellular, industrial, vehicular,
provided in [582], concentrating on the signal process- and aerial environments.
 64

Cellular
communication
D2D

IN-BAND OUT-BAND

UNDERLAY CONTROLLED
D2D
communication

Fig. 39. Cellular versus D2D communications.

OVERLAY AUTONOMOUS
• Introduction: D2D communication refers to direct com-
munication between close-proximity devices without BS
Fig. 40. Different types of D2D communication [591].
involvement [590], as illustrated in Figure 39. D2D com-
munications can be classified into two main categories:
in-band and out-band [590], [591], as summarized in sible D2D node, providing connectivity, content, and
Figure 40. In the in-band case, there are two modes, assistance to nearby devices, systems, and applications.
i.e., underlay, using the same spectrum as the cellular Depending on their capabilities, D2D nodes can potential
communication, and overlay, using a dedicated part of the offer assistance beyond communication as well, such as
cellular spectrum. Out-band communication is either au- computation, caching, positioning, sensing, and energy.
tonomous between devices or controlled by the BS. D2D Furthermore, D2D nodes can form clusters to be more
communications can provide diverse benefits, such as data powerful as a group. Although this vision is hypothetical,
traffic off-loading, improved spectral efficiency, decreased it shows the way forward.
latency, increased throughput, better reliability, and im- 6G provides a major opportunity to take D2D commu-
proved energy efficiency [591]. Common drawbacks in- nication to the next level and make it a mainstream
clude challenging interference and resource management cellular technology. In this picture, the synergy with
[590], [591]. Typical application scenarios include mobile other emerging 6G technologies plays a key role by
traffic off-loading, relaying, content sharing/distribution, providing joint benefits and broadening their combined
proximity-aware services, and broadcasting road safety applicability and capabilities [591]. For instance, D2D
messages [590]. communications at THz and VL frequencies enable ultra-
• Past and Present: The concept of D2D communications high data rates. For IoT scenarios, D2D communication
was first proposed in the context of cellular multi-hop can improve connectivity and robustness. Extending D2D
relays in 2000 [592]. However, it was until the late 2000s communications and relaying to aerial scenarios enables
when D2D research started to boom, with a special focus novel applications for UAVs and provides benefits, such
on LTE scenarios [593]. Since then, D2D communication as improved coverage, efficiency, and safety. The po-
has been an active research topic for practical use in cellu- tential benefits of RIS-aided D2D communications are
lar networks. In the early 2010s, D2D communication, or coverage extensions and obstacle avoidance. AI/ML is a
sidelink communication, as it is known in the 3GPP spec- promising technology to enhance resource management
ifications, was adopted for 4G LTE-A evolution [594]. and mode selection mechanisms in D2D communications.
Specifically, sidelink communication was first specified As the devices and networks become more powerful
in Release 12, followed by sidelink relaying in Release and intelligent toward 6G, devices could also offer more
13. Releases 14 and 15 provided further enhancements than connectivity to each other, e.g., computation power,
for LTE sidelink, for example, in the context of V2X caching, positioning/sensing assistance, and useful inter-
communications. Recently, sidelink communication has actions as a part of smart applications. The formation of
been further enhanced in the 5G NR standards [594]. NR D2D clusters can make these interactions more powerful.
sidelink was first introduced in Release 16, with the main These clusters can be autonomous or network-controlled,
focus on V2X scenarios. Release 17 defined further en- being also part of the network-driven EI.
hancements, such as reliability/latency improvements and In general, D2D communications can provide perfor-
UE power savings [17]. Release 18 introduced sidelink mance improvements in terms of spectral efficiency,
positioning, NR sidelink evolution, and NR sidelink relay throughput, latency, energy efficiency, reliability, and
enhancements [7], [18]. coverage [590], [591]. System-level spectral efficiency
• Opportunities and Challenges: The ultimate potential can be improved by using underlay in-band D2D com-
of D2D communications is that any device is a pos- munication, which uses the same spectral resources as the
 65

cellular network. The potential throughput improvements communications, different security and privacy threats
are due to short communication ranges. Latency reduction need to be properly addressed and efficient solutions
is possible due to fast connection establishments and short developed. More information on the opportunities and
link and content distances. The reduced energy consump- challenges of D2D communications can be found in
tion is due to the low transmission powers and light [590], [591].
signaling. D2D relaying can provide coverage extensions • Literature and Future Directions: In the literature, the
and increased reliability for cell-edge and out-of-cell early research of D2D communications dates back to the
scenarios. Numerous applications can benefit from D2D late 2000s [595]. The special focus was first on 4G LTE
communications [590], such as location-aware services, use cases [593] but it shifted to 5G [596] around the mid-
online gaming, social networking, interactive advertis- 2010s and has recently turned toward 6G [591]. Over the
ing, content sharing, public safety broadcasting, road years, a broad range of D2D topics has been examined,
safety/efficiency messages, interactive entertainment, etc. such as device discovery, mode selection, interference
In contrast to the numerous opportunities, there are many management, power control, resource allocation, relay-
challenges in D2D communications. Typical ones are ing, mobility management, and security/privacy [590],
related to interference management, device discovery, [597]. Recent survey articles have reviewed the latest
mobility management, and security/privacy [590], [591]. literature, state-of-the-art solutions, recent advances, and
The integration of underlay D2D communications into open challenges of D2D communications [591], [597]–
cellular networks makes interference management more [603]. These surveys discussed D2D in terms of 5G [597],
challenging since a new tier is added to the network archi- 6G [591], [598], [599], cognitive D2D [600], resource
tecture, leading to the new types of interference scenarios. management [601], state-of-the-art solutions [602], and
In a such network, there exist two tiers, i.e., a cell-tier AI-based resource allocation [603].
and a D2D-tier [590], which cause interference to each Since 6G provides diverse opportunities and challenges
other. In addition to inter-tier interference, there exists for D2D communications [591], future research needs
also intra-tier interference within both tiers. More com- to be adapted accordingly. Many emerging 6G tech-
plicated interference scenarios call for novel interference nologies can benefit D2D communications if combined
management solutions without overwhelming signaling properly [591]. In addition, the capabilities of D2D
overhead and computational complexity. can be broadened from communication to computation,
Another fundamental challenge in D2D communications caching, sensing, and positioning. In general, 6G aims
is the discovery of other D2D users in the network. De- to provide broad support for D2D communications in
vice discovery can be classified into two categories, cen- diverse scenarios, including cellular, industrial, vehicular,
tralized and distributed [590]. In the centralized case, de- and aerial environments. Future research directions can be
vice discovery is handled completely or partially through divided into two main categories, i.e., extending standards
the BS. The complete involvement of the BS is more and studying novel topics. 5G supports D2D mainly in
controlled, requiring more signaling and time to establish V2X, public safety, and specific application scenarios.
a connection between D2D users. In the case of partial Release 18 extended the support for higher frequencies
involvement, device discovery is faster with reduced (i.e., FR2), unlicensed spectrum, carrier aggregation, and
signaling overhead, but less controlled and may cause positioning [7], [18]. For 6G, important future studies
interference issues in the network. In the distributed case, include extensions to the THz spectrum, IoT scenarios,
device discovery is handled by the D2D users, without UDNs, and UAV environments [590], [591]. Promising
any involvement of the BS, through periodic beacon future topics worth studying include AI/ML-aided D2D,
signaling. Compared to the centralized discovery, dis- RIS-aided D2D, D2D-aided EI, VLC D2D, and D2D
tributed discovery is less time- and resource-consuming sensing. In addition, D2D security and privacy concepts
at the cost of possible interference issues. Generally, need a major update for the 6G era.
distributed discovery is preferable in delay-constrained
2) V2X Communications:
application scenarios. Typical challenges in distributed
discovery are related to the design (structure/frequency), • Vision: V2X communication is expected to act as a key
synchronization, and interference of beacon messages enabler for future intelligent vehicular and transportation
[590]. systems in the 6G era.
D2D communication can be interrupted when D2D users • Introduction: V2X communication is generally defined
are mobile and moving away from one another. Thus, de- as the wireless connectivity between a vehicle and any
veloping appropriate mobility management mechanisms type of an object or entity that is under the influence
for D2D communications is highly important. Due to its of the vehicle, or vice versa. V2X communication com-
direct nature, D2D communication exposes the network prises various connectivity types, the main ones being
and users to diverse security and privacy threats. Typical V2V, vehicle-to-infrastructure (V2I), vehicle-to-network
threats include, among others, malicious attacks, eaves- (V2N), and vehicle-to-pedestrian (V2P) communications,
dropping, modified messages, and node impersonation as defined in 3GPP [604] and illustrated in Figure 41.
[590]. Also the anonymity, confidentiality, and integrity V2V refers to the D2D-type direct communication among
of data may be threatened [590]. To ensure safe D2D nearby vehicles. The V2I technology provides communi-
 66

sors, and remote driving. In Release 16, 5G-V2X was

officially included in the 3GPP standards [605]. The
Technical Specification (TS) 22.186 defined the service
requirements for the aforementioned 5G-V2X use cases
[607]. Compared to 4G-V2X, 5G-V2X supports more
advanced use cases with more stringent requirements,
V2V
reducing latency and enhancing reliability, throughput,
and flexibility [605]. Releases 17 and 18 provided further
enhancements for 5G-V2X. The key aspects of Release
17 included sidelink enhancements for resource alloca-
tion, beamforming, and UE relaying [605], [608]. Release
18 focused on architectural AI/ML integration and further
Fig. 41. Four main types of V2X communications. enhancements for sidelink resource allocation, beamform-
ing management, UE relaying, UE power savings, and the
cation between vehicles and road infrastructure (e.g., road introduction of Uu multicasting services for wide-area
site units, traffic lights, traffic signs, etc.). V2N connects V2N communications [608].
vehicles and cellular networks, extending the capabilities • Opportunities and Challenges: The potential of next-
of V2X. Vehicles and pedestrians are connected via V2P generation V2X communications is to advance the con-
communication. The goal of V2X communications is to nectivity, intelligence, autonomy, and automation of
promote road safety, traffic efficiency/management, vehi- large-scale vehicular systems and individual vehicles;
cle cooperation, driver assistance, connected autonomous traffic tracking, monitoring, management, cooperation,
driving, and intelligent vehicle/transportation systems. and efficiency; cooperation between different objects and
In the standardization-wise, there are two types of V2X entities in the framework of vehicular systems; and
communication technologies, i.e., IEEE’s WiFi-based ubiquitous road safety. From a broader perspective, V2X
V2X, known as Dedicated Short-Range Communication communication is seen as a key technology to enable
(DSRC), and 3GPP’s cellular-based V2X (C-V2X) [155]. intelligent vehicular and transportation systems in the
WiFi-based DSRC, which supports V2V and V2I tech- 6G era. To realize this vision in practice, V2X must
nologies, does not require any communication network rely on a wide range of emerging technologies. Some
infrastructure to form ad hoc-type connections among potential enablers include a flexible utilization of a broad
vehicles and between vehicles and traffic infrastructure. spectrum range (from sub-6 GHz to THz frequencies),
The shortcoming of WiFi-based V2X communications pervasive use of AI/ML (from system architecture to air
is that strict service requirements cannot be guaranteed interface), coordinated utilization of 3D network archi-
due to unlicensed spectrum operation. In addition to tecture (ground-air-space), and broad usage of beyond-
V2V and V2I, C-V2X supports V2N connectivity, which communication technologies (computing, sensing, local-
is particularly important for enabling future intelligent ization, and control) [155]. While these technologies
vehicular and transportation systems. offer novel opportunities for V2X communications, they
• Past and Present: The concept of V2X communications also introduce diverse challenges for the corresponding
was originally standardized by IEEE in 802.11p in 2010 network design. The survey [155] provides a detailed
[155]. The first generation of this WiFi-based concept was discussion of the key enabling technologies for 6G-V2X,
named DSRC, which covers the V2V and V2I technolo- discussing their opportunities and challenges.
gies. The second-generation DSRC was released in IEEE The benefit of a wide spectrum range is that different
802.11bd in 2019 [155]. In 2017, 3GPP standardized frequency bands can be used for different V2X purposes,
4G LTE V2X (i.e., 4G-V2X or LTE-V2X) in Release based on their favorable features. For example, THz
14 [605]. Two communication modes were introduced: frequencies, with massive bandwidths, can be used for
LTE-Uu for long-range network connectivity via V2N high-throughput V2V communications and other close-
and LTE sidelink for short-range direct connectivity via proximity V2X applications. In contrast, lower frequen-
V2V and V2I [155]. Release 15 updated 4G-V2X di- cies, with better coverage and mobility support, can be
rect communication parts (named LTE-eV2X) to support utilized for long-range V2N communications and other
transmit diversity for better reliability as well as higher- wide-area V2X applications. The utilization of broad
order modulation and carrier aggregation for improved spectrum requires dynamic network architecture, with
throughput [155]. In general, 4G-V2X supports basic road numerous configurations and QoS requirements. Each
safety and traffic management use cases. spectrum band has unique challenges that need to be
The first 3GPP studies on 5G NR V2X (i.e., 5G-V2X addressed. Typical ones are related to transceiver design,
or NR-V2X) were introduced in Technical Report (TR) transmission schemes/parameters, and interference man-
22.886 (Release 15/16), examining the enhancement of agement. For example, propagation losses are high and
3GPP support for 5G-V2X services [606]. The report hardware impairments severe at THz frequencies, calling
identified advanced V2X use cases in four main groups, for highly directional beamforming and careful hardware
i.e., vehicle platooning, advanced driving, extended sen- design, with efficient compensation mechanisms.
 67

AI/ML is a promising technology to improve V2X net- [611], the authors explored AI/ML technology to enable
work and communication optimization, efficiency, flexi- advanced V2X features. Security and privacy challenges
bility, and predictability. For example, DL is well-suited in V2X communications were discussed in [612]. The
for prediction and management problems, DRL for re- article [613] reviewed V2X technology in the context of
source allocation, and FL for distributed optimization. intelligent transportation systems. The authors in [155]
However, practical AI/ML implementations are partic- provided a detailed discussion of 6G for V2X commu-
ularly challenging in the V2X framework due to the nications, focusing on the revolutionary and evolutionary
fast-varying channel conditions (highly mobile scenarios), technologies. In [614], V2X cyber-security was consid-
heterogeneous and dynamic wireless environments (IoV), ered, discussing reactive and proactive security solutions.
and stringent latency requirements (real-time processing). The work [615] provided a comprehensive study on re-
This calls for efficient online learning approaches and fast source allocation for 6G-V2X sidelink. Sustainable V2X
AI/ML algorithms. communication was explored in [616], with the focus on
Non-terrestrial communication is recognized as a means relevant use cases and technology trends. In [617], task-
to enhance the coverage, reliability, and capacity of V2X oriented V2X was studied from the perspective of digital
scenarios. While satellites are the key for wide and remote twins and edge computing. The survey [618] provided
area coverage, UAVs enable flexible capacity boosts in a thorough discussion of the V2X cyber-security threat
the needed areas. The integration of non-terrestrial com- landscape.
ponents requires advanced (AI/ML-based) cooperation
mechanisms between different layers. New channel and
interference characteristics arise from the 3D network
architecture, calling for enhanced resource allocation and
interference management approaches, as well as novel
3D channel models for V2X environments. Furthermore,
satellite communication is problematic for time-sensitive
V2X applications due to its long delays.
Integrated beyond-communication technologies can po-
tentially advance intelligence, efficiency, awareness, and
autonomy in vehicular systems. Powerful computation,
storage, and caching capabilities are vital for pervasive
AI/ML, whereas network sensing and positioning im-
prove the situational awareness of V2X systems. The inte-
gration of beyond-communication technologies into cellu- Fig. 42. Cellular-operated UAV communications.
lar and V2X networks requires significant enhancements
to the system architecture, network resource management
procedures, cooperation and information exchange mech- 3) Cellular-Connected UAV Communications:
anisms, and data collection and analytics, among others. • Vision: Cellular-connected UAV communication is seen
• Literature and Future Directions: In the literature, as a means to enable novel aerial applications, and
cellular V2X communication has been widely exam- ultimately free the potential of UAVs by providing ubiq-
ined for 4G and 5G. 4G-V2X research has mainly uitous, seamless, and high-quality mobile connectivity for
focused on developing technological enablers to sup- UAVs in the 6G era.
port road safety and traffic management applications. • Introduction: Cellular-connected UAV communication
In the context of 5G, V2X has been extended to sup- refers to the support of UAVs by mobile networks through
port more advanced features related to remote driving, cellular connectivity, as illustrated in Figure 42. The
driver assistance, vehicle platooning, and extended sen- promise of cellular involvement is the networks’ potential
sors. For 6G, V2X research is currently ongoing. Major ability to provide high-quality and reliable mobile con-
enhancements are under study, e.g., related to the use nectivity everywhere, expanding the opportunities to ex-
of AI/ML, broad spectrum range, non-terrestrial connec- ploit UAVs for versatile purposes. However, this requires
tivity, beyond-communication technologies, and security. fundamental architectural changes to the network struc-
Further research efforts are needed in these directions in ture since current mobile networks have been designed
the near future. The status, recent advances, and future to serve ground users. Currently, the cellular support of
research areas of V2X communications have been thor- UAVs is under 5G standardization, while academia and
oughly discussed in recent survey articles [155], [604], industry are seeking novel ways to enhance it further.
[605], [608]–[618]. From a communication perspective, the new concept of
The paper [605] presented an in-depth overview of 5G- UAV-to-everything (U2X) communications, introduced in
V2X in Release 16. Release 17 and 18 enhancements [619], is at the center of future cellular UAV connectivity.
were surveyed in [608]. 5G-V2X was also discussed A generic definition of U2X communications is the
in [604] and [609]. The work [610] studied large-scale connectivity between UAVs and other nodes in a cellular
V2X deployments, presenting also a vision toward 6G. In network, such as BSs, ground-devices, and other UAVs
 68

[619]. The main connectivity modes of U2X include arise from the cellular support of UAVs since mobile net-
UAV-to-network, UAV-to-UAV, and UAV-to-device com- works have unique capabilities to provide reliable, high-
munications [619]. Other potential modes are UAV-to- performance, and ubiquitous mobile connectivity. Ulti-
satellite and UAV-to-vehicle communications. Ultimately, mately, cellular-connected UAV communications aim to
U2X communications aim to take advantage of all layers free the potential of UAVs. Cellular UAVs can potentially
of the network, from ground to space and from cellular enhance or enable many types of applications, including
to vehicular. In particular, U2X communication is seen monitoring (e.g., industrial, environmental, and traffic),
as an enabler for IoU [619]. surveillance (e.g., public safety), logistics (e.g., air cargo
• Past and Present: In the research-wise, the interest and delivery), transportation (e.g., air taxis), entertain-
toward cellular UAV connectivity boomed in the 2010s. ment (e.g., immersive VR experiences), search/rescue
Due to advances in electronics, AI/ML, wireless commu- operations (e.g., difficult terrain and large areas), disaster
nications, and other related fields, UAVs were becoming management (e.g., humanitarian and medical aid), and
smaller, cheaper, more capable, and easier to control. agriculture (e.g., precision monitoring), among others
Consequently, the use of UAVs for civilian purposes [162], [620], [622]–[625]. It is expected that 6G will
was spreading around the world. Academia and indus- provide a fruitful platform for cellular-connected UAV
try saw the potential of combining UAVs and cellular communication to grow toward its potential.
communications, and started to take actions to make the Many challenges exist on the way toward comprehensive
visions real. Lots of research and development work has cellular support for UAVs. The UAV communication
been conducted, including theoretical studies, channel scenario differs significantly from that of the traditional
measurements/modeling, algorithm/protocol/architectural cellular environment on the ground. The main differences
design, technology development, performance evalua- include the high altitude of end-devices, unique 3D chan-
tions, experiments, and field trials. Strong collaboration nel characteristics, air-ground interference, dynamic 3D
between academia and industry has also been involved. network topology, 3D mobility, and emphasized uplink
In the 2010s, the research on UAVs mainly focused on communications [622], [623]. To manage these pecu-
5G networks. On the verge of the 2020s, the focus began liarities, novel solutions are needed. As UAVs have a
to gradually shift toward 6G. relatively high altitude compared to the ground-users,
In standardization, 3GPP has been exploring cellular- conventional cellular networks, based on down-tilted BS
connected UAV communications from Release 15 onward antennas, lack the ability to provide a broad coverage for
[620]. In 3GPP, UAVs are studied under the concept of UAVs up in the air. For successful UAV communications,
UAS, which consists of two main elements: a UAV and cellular networks need to adopt a large-scale 3D network
a UAV controller [621]. A UAV can be controlled using architecture, where the airspace is also ubiquitously cov-
a remote controller via a 3GPP cellular network or non- ered. This calls for a 3D cell planning/design, up-tilted
3GPP control mechanisms [621]. The main cellular-based BS antennas, and 3D beamforming. In particular, massive
communication services for the UAS ecosystem can be MIMO is seen as one of the potential transmission
classified into two categories, i.e., command/control data technologies to facilitate 3D coverage by forming beams
and payload data services [621]. UAS also interacts with toward UAVs in the sky [625]. However, massive MIMO
UAS traffic management (UTM), which provides many has its own challenges and limitations, such as pilot
important services for the safe operation of UAS [621], contamination and CSI acquisition [625].
such as identification, tracking, authorization, regulatory Due to the unique nature of a 3D radio channel environ-
information, and storage of operational data. ment, novel channel models are of great importance to
In Release 15, the work on cellular-operated UAVs started evaluate the performance of the proposed communication
with a study item on the required enhancements of LTE algorithms. If UAVs are served using the same spectral
networks to support UAVs, resulting in TR 36.777 [620]. resources as the ground-users, a new type of interference
In Release 16, the work continued with TR 22.829, is present [623], i.e., air-ground interference. This calls
which identified UAV use cases and the required en- for new interference management and power control
hancements for 3GPP networks, calling for 5G support techniques. For example, the massive MIMO technology
[620]. Moreover, TS 22.125 defined the requirements for has the potential ability to efficiently suppress air-ground
UAS operation over 3GPP networks [620]. In Release interference by accurate 3D beamforming [625]. Since
17, TR 23.754 and TR 23.755 studied mechanisms to UAVs are mobile in 3D space, possibly with relatively
support connectivity, identification, and tracking in UAS, high velocity, 3D handovers become frequent, leading
as well as the architectural requirements and solutions to challenging cell design and mobility management
to support UAS applications, respectively [620]. Release [625]. AI/ML is seen as an efficient tool to assist in the
18 provided further enhancements for the NR support 3D network design and mobility management problems.
of UAVs, especially in terms of identification, reporting, Recent surveys provide more details on the challenges
broadcasting, and beamforming [162]. A comprehensive and potential solutions of cellular-supported UAV com-
survey on the 3GPP standardization efforts for UAS is munications [620], [622]–[625].
given in [620]. • Literature and Future Directions: The research on
• Opportunities and Challenges: Diverse opportunities cellular-connected UAVs began gaining popularity in
 69

TABLE XII
S UMMARY OF SERVICE - ORIENTED TECHNOLOGIES FOR 6G

Service-Oriented
Vision Description Opportunities Challenges Past Present
Technologies

Secure PNs for Customized for New business Security & 4G private 5G private
Private Networks
diverse verticals vertical customers opportunities guaranteed QoS networks networks

the 2010s. Diverse aspects and issues have been ad- emerging technologies (e.g., AI/ML, massive MIMO,
dressed and solutions proposed. In the past few years, mmWave, THz, RISs, NTNs), U2X communications, col-
researchers have conducted numerous surveys, reviewing laborative UAVs (e.g., UAV swarms), channel modeling
topics that range from fundamentals to standardization, (e.g., channel measurements, system-level 3D models),
recent advancements, open challenges, and future re- and security (e.g., cyber security, physical security) [162],
search guidelines [162], [164]–[166], [619], [620], [622]– [164], [620], [622]–[625], [627].
[629]. In [622], the article reviewed cellular-connected
UAV operations in terms of communication/spectrum
I. Service-Oriented Technologies for 6G
requirements, design aspects, potential technologies, and
future directions. The authors in [623] presented a survey It is anticipated that 6G will significantly expand the
on cellular UAV communications, with the focus on services of mobile networks, especially in vertical domains.
UAV types, standardization, UAV-BSs, prototyping/field Private networks will be at the core of this evolution, offering
testing, regulations, security, and future research areas. customized services for vertical clients and creating novel
The work [619] introduced a novel concept of U2X business opportunities. Private networks are reviewed in the
communications from the perspectives of fundamentals, following and summarized in Table XII.
key techniques, reinforcement learning framework, and
future extensions. Cellular-operated UAVs were explored
in [624], covering applications/use cases, challenges, NETWORK
5G/B5G innovations, trials/prototyping, standardization, TYPES
and future research guidelines.
The paper [620] reviewed 3GPP standardization of cellu-
lar UAS support, and introduced the key research drivers.
In [626], the authors discussed enabling technologies, PUBLIC PRIVATE
standardization efforts, security, and open issues for ad-
vanced cellular UAV operations. The authors envisioned
an evolution road for cellular UAV connectivity from
5G to 6G in [625]. Many aspects were discussed, in- MOBILE VERTICAL
cluding 5G NR and beyond, sub-6 GHz massive MIMO, SUBSCRIBERS CUSTOMERS
mmWave/THz, AI/ML, NTNs, RISs, UAV-to-UAV com-
munications, and future challenges. The study [627] dis- Fig. 43. Two main types of mobile networks.
cussed cellular UAV support using THz frequencies. An
overview of UAV clients for beyond 5G was presented in
1) Private Networks:
[162]. The paper [628] reviewed advanced air mobility in
• Vision: In the 6G era, private networks are expected to
cellular networks, with a particular focus on use cases and
beamforming techniques. In [629], the authors explored become a key technology for extending the applicability
the use of unmanned vehicles in 6G networks. The sur- of mobile networks to vertical industries by providing
veys [164]–[166] explored cellular-supported cooperative tailored high-quality wireless services.
• Introduction: While public networks serve traditional
UAV swarms.
Major research and development efforts are required in mobile subscribers, private networks are tailored exclu-
the future to provide reliable and ubiquitous cellular sively to vertical customers, as summarized in Figure
support for UAVs. The earlier discussed challenges need 43. Typical customers vary from private enterprises to
to be carefully addressed. Although some studies have public sector organizations, requiring secure non-public
been conducted to overcome these issues, extensive re- network services. Hybrid networks also exist, i.e., a mix
search is still needed. In this regard, key future top- of private and public networks, where a part of the net-
ics on cellular-connected UAV communications include work functions are private and other parts public. Private
3D network design (e.g., up-tilted cell design, resource networks are expected to expand the service opportunities
allocation, interference control, mobility management), of mobile networks in the future, thereby enabling novel
applications in diverse vertical industries.
 70

• Past and Present: Traditionally, mobile networks have In [630], [632]–[634], recent surveys provide detailed
been mostly public, offering services to conventional discussions on the main challenges of private networks.
mobile subscribers. Private networks were first introduced • Literature and Future Directions: In the literature,
in 4G. However, the usage has been rather marginal, the first studies on private mobile networks date back
partly due to the limitations of 4G. 5G private net- to the early 2010s, with the main focus on 4G LTE.
works, also known as non-public networks in 3GPP, were However, research interest in private networks remained
introduced in Release 16 [630]. Compared to 4G, 5G relatively mild until the late 2010s. Then, the research
provides significantly better performance and capabilities started to gain more attention since the focus shifted
for private networks, opening up new service oppor- to more promising 5G private networks. Currently, the
tunities, especially in industrial environments [631]. In latest works look beyond 5G. Commonly studied topics
the 5G NR standards, private networks are supported in in the private network research include industry 4.0,
two categories, i.e., public network integrated and stand- industrial IoT, spectrum operation, network architecture,
alone non-public networks [630]. The former relies on a edge computing, network slicing, and security. Private
PLMN and the latter performs independently. Full control networks have been thoroughly reviewed in [630]–[636].
and independence to customize the stand-alone network The paper [631] discussed private 5G networks in an
according to the customer’s needs comes at the price of industrial context. The covered topics include indus-
higher capital and operational costs [630]. Further details trial networking demands, 5G opportunities for industrial
on the standardization of 5G non-public networks can be wireless, functional architecture of 5G private networks,
found in [630]. In the big picture, 5G is paving the way industrial usage scenarios, licensed/unlicensed spectrum
for a paradigm shift where mobile networks are not only operation, network design challenges, and standardiza-
used for serving public subscribers but also providing tion efforts. In [635], 5G and beyond private networks
versatile services for a wide range of vertical industries. were explored in terms of application scenarios, stan-
• Opportunities and Challenges: Private networks are dardization aspects, operator models, and technological
expected to significantly expand the service opportuni- enablers. The authors of [630] reviewed 5G non-public
ties of mobile networks in the 6G era, enabling novel networks from a standardization perspective, focusing on
applications in diverse vertical industries. This will gen- enterprise customer requirements, enabling technology
erate new business opportunities for mobile network solutions, 3GPP standardization, single- and multi-site
vendors and operators, as well as customer industries. network scenarios, and implementation challenges.
Potential application domains include versatile industries The work [632] provided a survey on the research of
and utilities [630], such as manufacturing, healthcare, private 5G networks, with discussions on the basic ar-
transportation, retailing, agriculture, energy, education, chitectures, implementation issues, technology enablers,
sports, and tourism, to list a few. In particular, private application scenarios, real-world field trials, and open
mobile networks are seen as a key enabler for industry problems. In [633], 5G and beyond private networks were
4.0 [630]. From a wider perspective, private networks will considered to deliver tailored services for vertical indus-
integrate mobile networks more deeply into society. In tries with integrated eMBB, URLLC, mMTC, and posi-
this regard, 6G is expected to penetrate all levels of future tioning. A thorough survey of 5G private networks was
society, impacting all walks of life, utilities, businesses, given in [634]. Numerous topics were covered, includ-
and industries. ing requirements, enablers, deployment modes, spectrum
Although private networks have been included in the 5G operations, network slicing, services, mobile operators’
standardization and commercial solutions exist around roles, applications, security, and future research. In [636],
the world, they are still at a rather early evolutionary private 5G networks were discussed in terms of vertical
stage and far from their true potential. There are diverse industries, providing design and research guidelines.
technological obstacles on the way toward freeing the As mentioned earlier, private networks are still at a rather
full potential of private networks. First, private networks early evolutionary stage, requiring major research and
must fulfill the requirements of customer verticals, such development efforts in the future. Since 6G is expected to
as tailored services, guaranteed QoS, accurate coverage, provide the tools needed for the next major leap in the pri-
protected data, and secure networking [630]. Addition- vate network paradigm, it is pivotal to consider the unique
ally, there is a constant need to further enhance the perfor- characteristics of 6G in research and design. Some fruitful
mance and capabilities of private networks. Whereas 5G future topics on private networks include operation in
evolution can provide rather limited enhancements, 6G is the 6G spectrum, advanced fronthaul/backhaul networks,
expected to take private networks to the next level, with AI/ML-based network optimization, ultra-massive IoT
extreme performance, pervasive AI/ML, and integrated support, integration of beyond-communication technolo-
beyond-communication technologies. In addition to op- gies, realistic channel models, end-to-end performance
portunities, 6G will introduce new challenges as well. evaluation, and security/privacy. Future research direc-
In this picture, the main issues are related to resource tions have been discussed in surveys [630], [632]–[634].
management, spectrum use, AI/ML-assisted network op-
timization, integrated computation, control, and sensing,
fronthaul/backhaul, data privacy, and network security.
 71

TABLE XIII
S UMMARY OF SECURITY TECHNOLOGIES FOR 6G

Security
Vision Description Opportunities Challenges Past Present
Technologies

Holistic Network
Security Trustworthy & Protection against Safe use of 6G Evolving threat 4G security 5G security
Architecture secure 6G outside threats networks landscape architecture architecture

J. Security Technologies for 6G threats. The first three mobile generations faced more
Since future society will be highly dependent on 6G, it traditional types of threats, mainly related to authenti-
is of utmost importance to make 6G networks trustworthy cation, authorization, encryption, eavesdropping, physical
and secure. A special attention needs to be paid to privacy attacks, and cloning [637]. Since mobile internet and its
as well, as data is becoming more abundant. Therefore, a applications became mainstream in the 4G era, the se-
comprehensive network security architecture is required, as curity and privacy threat landscape expanded to malware
discussed below and summarized in Table XIII. applications and the denial of service attacks [637].
New types of security and privacy threats were intro-
duced for 5G due to its expanded capabilities and a
broad range of novel applications. In this respect, 3GPP’s
THREAT
LANDSCAPE Release 15 introduced an advanced security architecture,
with features such as access-agnostic authentication, en-
hanced subscription privacy, user plane integrity protec-
tion, network slice-specific authentication/authorization,
6G and advanced authentication/authorization between net-
SECURITY work functions [638]. During the entire evolution of 5G,
its security architecture will be constantly updated, con-
sidering newly added technology features and extended
HOLISTIC TECHNOLOGY capabilities. Currently, a security and privacy threat
ARCHITECTURE SOLUTIONS
paradigm is studied for 6G in academia and industry,
while paying attention to the emerging 6G technologies,
services, and applications.
Fig. 44. Three main phases to build 6G network security. • Opportunities and Challenges: The aim of a holistic
security architecture is to ensure the trustworthy, secure,
and privacy-protected use of 6G for all users. This is one
1) Network Security Architecture: of the cornerstones of 6G, and is vital for its success.
• Vision: It is expected that 6G networks will be secured Secure 6G enables the safe evolution of mobile networks
by a comprehensive security architecture, advancing trust and a bloom of novel applications. Developing a secure
and privacy as well. 6G ecosystem is a major challenge, which requires a
• Introduction: Mobile network security protects against holistic approach, covering security, privacy, and trust
external threats and attacks, aiming to ensure the safe from the perspective of technology and regulations. To
and trustworthy use of the network for all customers. tackle diverse threats at different levels of the network,
To achieve this target, a holistic security architecture a comprehensive 6G network security architecture needs
is required, which secures all network layers from the to be developed, considering privacy protection as well.
PHY and MAC to the network and application layers. At a high level, building a thorough 6G network secu-
Network security will become increasingly important in rity framework requires three (interrelated) phases, as
the future since mobile networks will be more integrated summarized in Figure 44. First, the entire 6G threat
into different levels of society. For example, security vector landscape must be identified and regularly updated,
is particularly critical in healthcare, transportation, and considering all network layers. Second, technological
industrial automation scenarios. In addition, data privacy solutions must be developed for each identified threat.
must be protected. Since the use of AI/ML is constantly Third, a holistic network security architecture has to
increasing, data is becoming more abundant, making it be built based on the identified threats and proposed
more vulnerable to attacks. solutions.
• Past and Present: Since each new mobile generation New threat vectors arise from the emerging 6G tech-
introduces novel technologies, services, and applications, nologies (e.g., pervasive AI/ML, NTNs, V2X, integrated
it encounters new security threats as well. Therefore, beyond-communication technologies, and heterogeneous
novel security solutions are required to address these
 72

network architecture) and diverse applications (e.g., smart The paper [650] reviewed the research landscape of 5G
healthcare, smart factories, smart cities, connected au- security, and discussed promising security mechanisms
tonomous vehicles, XR, and digital twins). Moreover, for 6G. In [651], the authors explored AI-based security
data will become increasingly important and abundant approaches for 6G networks. Although 6G security has
in the future, making 6G networks more vulnerable to been actively researched in academia and industry for
attacks, and raising concerns on data privacy. The threat years, major efforts are still required to make 6G truly
landscape of these technologies and applications need secure and trustworthy. Further research and development
to be carefully studied, potential solutions developed, work is needed to identify the 6G threat vector landscape,
and a holistic security architecture designed, covering all develop AI/ML-based security and privacy solutions, and
network layers. In this framework, AI/ML has been rec- build a comprehensive architectural security framework.
ognized as a powerful technology for protecting against
diverse security threats. On the other hand, integrated
EXTREME
AI/ML is also a target of novel attacks. Thus, AI/ML CAPACITY &
can be seen as a double-edge sword [639], calling for se- PERFORMANCE
cured AI/ML solutions. The work on 6G security/privacy
threats, solutions, and architecture is currently ongoing, THOROUGHLY ULTRA-
requiring constant development efforts. 6G security has SECURE & FLEXIBLE &
TRUSTWORTHY AGILE
been thoroughly discussed in [637]–[641].
• Literature and Future Directions: Recent surveys have
provided comprehensive discussions on the security, pri- 6G
vacy, and trust issues for 6G [32], [637]–[651]. The FEATURES
white paper [32] presented a thorough review of the trust
networking, network security, PHY layer security, and
privacy protection aspects for 6G. In [642], a detailed HIGHLY
TRULY GREEN &
INTELLIGENT &
survey was provided on the privacy violation and pro- SUSTAINABLE
AWARE
tection in 6G by exploiting ML. In [637], the authors
discussed the security and privacy issues in the context
UBIQUITOUSLY
of 6G requirements, technologies, applications, and stan- AVAILABLE &
dardization. In [643], PHY layer security was considered RELIABLE

for 6G networks, focusing on challenges, solutions, and

visions. The authors in [640] explored new security Fig. 45. Defining features for 6G.
threats, arising from the introduction of promising 6G
technologies and possible solutions against them.
In [638], the focus was on the technology enablers IX. D EFINING F EATURES FOR 6G
for 6G security, including automated software cre- In this section, we identify 12 main features that define the
ation, automated closed-loop security operation, privacy- essence of 6G. These features are summarized in Figure 45.
preserving technologies, hardware and cloud embedded • Extreme Capacity and Performance: Extreme capacity
trust, quantum-safe security, jamming protection, physical and performance will be the cornerstones of 6G. There
layer security, and distributed ledger technologies. In are six main performance dimensions that need to be
[641], a systematic survey was presented on the 6G pushed to the extreme levels, i.e., capacity, latency, re-
security and privacy issues in the physical, connection, liability, density, coverage, and mobility. Other important
and service layers of the network. The authors in [644] dimensions are energy efficiency and positioning accu-
presented a detailed review of recent research progress on racy. By pushing the performance into its limits, 6G will
the security threats, attack methodologies, and defense form a fruitful platform for a broad range of demanding
countermeasures for 6G space-air-ground-sea network services and applications.
architecture. In [645], 6G security was studied in terms • Ultra-Flexible and Agile: To adapt itself to a wide range
of context-awareness, focusing on the PHY layer secu- of wireless environments and application scenarios, 6G
rity aspects. The paper [639] provided a comprehensive will be designed to be ultra-flexible and agile. Flexibility
review of the security and privacy of the network edge and agility need to be optimized at all levels of the
toward 6G, examining edge computing, edge caching, and network, from device and communication to network and
EI as the targets of attacks and the sources of protection. service levels.
In [646], the authors discussed the opportunities that PHY • Highly Intelligent and Aware: One of the most revo-
layer security can offer to the security of 6G. The work lutionizing features of 6G will be network intelligence
[647] explored the combination of AI/ML and a zero- based on pervasive AI/ML. The extensive use of AI/ML
trust architecture as an enabler of 6G network security. will make 6G highly intelligent, enhancing network de-
In [648], AI-enhanced PHY layer security was studied sign, operation, and management. AI/ML must be ex-
for 6G networks. The authors of [649] examined 6G se- ploited at all levels of the network, including the core,
curity in the physical, connection, and application layers. edges, and air interface. The most promising technologies
 73

to realize AI/ML are DL, FL, and TL. In addition, 6G 1.5X/3X ◦ Area Traffic Capacity: 30/50 Mbit/s/m2 ◦ User
is expected to become aware of the surrounding envi- Plane Latency: 0.1–1 ms ◦ Reliability: 1-10-5 –1-10-7 ◦
ronment through network sensing. This extends the ca- Connection Density: 106 –108 /km2 ◦ Maximum Mobility:
pabilities of 6G, opening up new beyond-communication 500-1000 km/h ◦ Positioning Accuracy: 1-10 cm
service and application opportunities. Technologies:
• Ubiquitously Available and Reliable: To enable a vast • Spectrum-Level Technologies: THz Communications ◦
variety of robust services, 6G will be designed to be Optical Wireless Communications
highly available and reliable. The key to ubiquitous • Antenna System Technologies: Ultra-Massive MIMO ◦
availability is broad coverage, which is enabled by the Reconfigurable Intelligent Surfaces ◦ Holographic MIMO
integration of terrestrial and non-terrestrial networks. Re- • Transmission Scheme Technologies: Multi-Waveform
liability has to be maximized at different network levels, Scheme ◦ Advanced Modulation and Coding Methods ◦
ranging from robust PHY layer schemes to network-level Non-Orthogonal Multiple Access ◦ Grant-Free Medium
mechanisms. Access
• Truly Green and Sustainable: Since the total energy • Network Architectural Technologies: Integrated Non-
consumption of mobile networks is constantly increasing, Terrestrial and Terrestrial Networks ◦ Ultra-Dense Net-
6G networks will be designed for greenness and sustain- works ◦ Cell-Free massive MIMO ◦ Integrated Access
ability by enhancing the energy efficiency at every level and Backhaul
of the network, from the core and edges to the MAC • Network Intelligence Technologies: Intelligent Core ◦
and PHY layer protocols. This will provide significant Intelligent Edge ◦ Intelligent Air Interface
ecological and economic benefits. • Beyond-Communication Technologies: Integrated Com-
• Thoroughly Secure and Trustworthy: As future society munication, Computation, and Caching ◦ Integrated Sens-
will be profoundly dependent on 6G networks, it is of ing and Communication ◦ Wireless Energy Transfer
utmost importance to make 6G secure and trustworthy. A • Energy-Aware Technologies: Green Networks ◦ Energy
holistic network security architecture needs to be devel- Harvesting ◦ Backscatter Communications
oped for 6G, taking into account also privacy and trust • End-Device-Oriented Technologies: D2D Communica-
issues. Security and trustworthiness are vital elements to tions ◦ V2X Communications ◦ Cellular-Connected UAV
ensure the safe use of 6G. Communications
• Service-Oriented Technologies: Private Networks
X. 6G IN A N UTSHELL
• Security Technologies: Network Security Architecture
This section provides a compact summary of our 6G vision Features:
in bullet points.
• Extreme Capacity & Performance ◦ Ultra-Flexible &
Vision:
Agile ◦ Highly Intelligence & Aware ◦ Ubiquitously
• Smart Wireless World via 6G-Enabled Mobile Intelli-
Available & Reliable ◦ Truly Green & Sustainable ◦
gence
Thoroughly Secure & Trustworthy
Elements:
• Wireless ◦ Artificial Intelligence ◦ Internet of Everything
XI. 7G V ISION : A H IGH -L EVEL S KETCH
Applications:
In this section, we place 6G into a wider perspective by
• Human-Machine Interactions: Metaverse ◦ Extended Re-
discussing the post-6G era and sketching the first high-level
ality ◦ Holographic-Type Communications ◦ Digital
vision of 7G. As each generation, 6G will eventually reach
Twins ◦ Tactile Internet
its limits and the next generation (7G) will gradually take
• Smart Environments: Smart Society ◦ Smart City ◦ Smart
over. Most likely, this evolution will follow the same ten year
Factory ◦ Smart Home
cycle seen in the past. While 6G is expected to dominate
• Connected Autonomous Systems: Connected
in the 2030s, we envision that the 2040s will be the 7G
Autonomous Vehicle Systems ◦ Connected Autonomous
era. The sooner we start visioning the next generation, the
Aerial Vehicle Systems ◦ Connected Autonomous
more prepared we are and the more time we have to develop
Robotic Systems
it. Although 6G is in the development process and many
Use Cases: years from the deployment phase, we can already see some
• Communication-Oriented: Ultra-Broadband Multimedia major trends that evolve beyond 6G. While wireless will
Communications ◦ Extreme Time-Sensitive and Mission- evolve toward unlimited, AI will expand vertically (deeper)
Critical Communications ◦ Ultra-Massive Communica- and horizontally (broader). In addition, the range of connected
tions ◦ Global-Scale Communications ◦ Hyper-Mobility devices will become wider and wider. Based on these trends,
Communications we can envision the next major disruption after 6G.
• Beyond-Communication-Oriented: Network Intelligence What comes to the disruptions provided by mobile net-
◦ Network Sensing ◦ Network Energy works, it seems that the major disruptions occur in the cycles
Requirements: of two generations, i.e., 1G/2G, 3G/4G, and 5G/6G. In this cy-
• Peak Data Rate: 50/100/200 Gbit/s ◦ User Experienced cle, the first generation introduces the new disruption, whereas
Data Rate: 300/500 Mbit/s ◦ Peak Spectral Efficiency: the second one makes it boom. For example, 1G introduced
 74

TABLE XIV easy to use super-precision user interfaces; fully immersive

A SPECULATIVE EVOLUTION FROM 6G TO 7G applications exploiting all human senses; and advanced AI
deeply integrated into all parts of the ecosystem. The 7G-
enabled mobile hyperverse will create countless application
6G 7G
and business opportunities at all levels of the future society.
Disruption Unlimited wireless refers to virtually unlimited wireless re-
sources in diverse dimensions, including connectivity, compu-
Mobile Intelligence Mobile Hyperverse
tation, control, information, positioning, sensing, and energy.
Elements As AI will expand vertically and horizontally in the future, we
refer to this advanced level of AI as DI. Due to DI, IoE will
Wireless (Extreme) Wireless (Unlimited)
Artificial Intelligence Deep Intelligence evolve toward IoI, which can be seen as a network of deeply
Internet of Everything Internet of Intelligence intelligent entities. What comes to the 7G-level applications,
human-DI interactions refer to diverse types of interactions
Applications
between people and deeply intelligent entities. Examples in-
Human-Machine Interactions Human-DI Interactions clude an augmented human, brain-DI interfaces, personal DI,
Smart Environments Deeply Intelligent World telepathic communications, and holographic worlds. A deeply
Autonomous Systems Intelligent Ecosystems
intelligent world refers to a world enhanced by DI at all levels
and scales. Example applications in this domain include global
intelligent systems, global monitoring/management/prediction
mobile telephony, while 2G freed its potential. Mobile internet entities, and a deeply intelligent society. Interconnected intel-
was first enabled by 3G and became mainstream in the 4G era. ligent ecosystems refer to large-scale entities on the ground,
Currently, 5G is introducing mobile and intelligence and it is in the air, and at the sea, exploiting wireless, DI, and IoI
expected that 6G will take the mobile intelligence to the next technologies. The evolution from 6G to 7G is summarized
level. This evolution will most likely continue after 6G. We in Table XIV.
envisage that the next major disruption in the post-6G era will
be the 7G/8G-enabled mobile hyperverse. Mobile hyperverse
will rely on the cornerstones of 7G. We identify these three XII. C ONCLUSION
fundamental pillars as unlimited wireless, deep intelligence This article provided a comprehensive vision, survey, and
(DI), and the Internet of Intelligence (IoI). These elements tutorial on 6G. First, we presented the evolution road from 1G
are vital to enable 7G-level applications. We identify some to 6G, overview of 5G, 6G development process, 6G research
possible applications in three categories, i.e., human-DI inter- activities, and a literature review on 6G visions and surveys.
actions, deeply intelligent world, and interconnected intelligent We then introduced our overall 6G vision. After painting
ecosystems. In the following, we provide further details on the the big picture, the focus was shifted to the main details
aforementioned disruption, elements, and applications. of 6G by identifying the fundamental elements, disruptive
We envision that the mobile hyperverse will be the next evo- applications, key use cases, target performance requirements,
lution phase after mobile intelligence, creating real-time intel- potential technologies, and defining features. A special focus
ligent, interconnected, interactive, and immersive entities that was given to a comprehensive set of potential 6G technologies,
can ultimately integrate the digital, physical, biological, and which were reviewed in a tutorial presentation style. Finally, a
even abstract worlds. The scale of integration can vary from high-level vision was introduced for 7G so that the current 6G
nano to global range. Roughly speaking, the hyperverse can vision could be placed into a wider perspective. This article
be seen as an extension of the metaverse. Mobile hyperverse aims to provide a comprehensive guide to 6G to inspire future
can take many forms and serve different purposes. Ultimately, research and development work in academia, industry, and
this evolution might lead to the Internet of Hyperverses. At standardization bodies.
a high level, mobile hyperverses can be divided into three
categories: public, non-public, and hybrid. Public hyperverses XIII. A PPENDIX
are intended for consumers, whereas the non-public ones are
for industrial, organizational, and enterprise purposes. Hybrid List of Abbreviations
hyperverses are a mix of both, being partly public and partly 1G 1st generation
non-public. From a human perspective, mobile hyperverse will 2D two-dimensional
enrich human interactions with other people, devices, systems, 2G 2nd generation
and applications, revolutionizing the human experience of the 3C communication, computation, and caching
world. We envisage that the mobile hyperverse will become
3D three-dimensional
mainstream when all seamlessly interconnected parts of the
entire ecosystem have reached a certain level of maturity, 3G 3rd generation
including networks, devices, user interfaces, applications, and 3GPP 3rd Generation Partnership Project
intelligence. Mobile hyperverse requires ubiquitous, super- 4G 4th generation
quality, and intelligent wireless network infrastructure; smart, 5G 5th generation
lightweight, and affordable XR device entities; smooth and 6G 6th generation
 75

6G-IA 6G Smart Networks and Services Industry GFDM generalized frequency division multiplex-
Association ing
7G 7th generation GFMA grant-free medium access
A&B access and backhaul GHz gigahertz
AI artificial intelligence GMSK Gaussian minimum-shift keying
AMPS Advanced Mobile Phone Service GSM Global System for Mobile Communica-
AP access point tions
AR augmented reality HAPS high-altitude platform station
ATIS Alliance for Telecommunications Industry HMD head-mounted display
Solutions HMIMO holographic MIMO
B5G beyond 5G HMIMOS holographic MIMO surfaces
BF beamforming HTC holographic-type communications
BPSK binary PSK HW hardware
BS base station i3C integrated 3C
CAAVS connected autonomous aerial vehicle sys- i4C integrated 3C and control
tem IAB integrated access and backhaul
CARS connected autonomous robotic system ICC International Conference on Communica-
CAV connected autonomous vehicle tions
CAVS connected autonomous vehicle system ICT information and communication technol-
CDMA code-division multiple access ogy
CDMA2000 family of 3G technology standards IEC International Electrotechnical Commission
cdmaOne original IS-95 standard IEEE Institute of Electrical and Electronics En-
CD-NOMA code-domain NOMA gineers
CF-mMIMO cell-free massive MIMO IMT International Mobile Telecommunications
CoMP coordinated multi-point IMT-2020 IMT for 2020 and beyond
COVID-19 coronavirus disease 2019 IMT-2030 IMT for 2030 and beyond
CP cyclic prefix INTNs integrated non-terrestrial and terrestrial net-
CPU central processing unit works
CSI channel state information IoE Internet of Everything
C-UAV cellular UAV IoI Internet of Intelligence
D2D device-to-device IoT Internet of Things
DFT discrete Fourier transform IoU Internet of UAVs
DFT-s-OFDM DFT-spread-OFDM IoV Internet of Vehicles
DI deep intelligence IR infrared
DL deep learning IRS intelligent reflecting surface
DSRC dedicated short-range communications ISAC integrated sensing and communication
DTL deep transfer learning ISO International Organization for Standardiza-
E2E end-to-end tion
EE energy efficiency ITU International Telecommunication Union
EH energy harvesting ITU-R ITU Radiocommunication Sector
EI edge intelligence KAIST Korea Advanced Institute of Science and
Technology
eMMB enhanced mobile broadband
KHz kilohertz
ETSI European Telecommunications Standards
Institute LD laser diode
EU European Union LDPC low density parity check
FBMC filter bank multi-carrier LED light-emitting diode
F-OFDM filtered OFDM LEO low Earth orbit
FR1 frequency range 1 LIS large intelligent surface
FR2 frequency range 2 LOS line-of-sight
FSO free-space optical LTE Long-Term Evolution
FTL federated transfer learning LTE-A Long-Term Evolution Advanced
FTT future technology trends M2M machine-to-machine
GEO geostationary orbit MAC medium access control
 76

MDT minimization of drive tests SNS JU European Smart Networks and Services
MEC multi-access edge computing Joint Undertaking
MEO medium Earth orbit SON self-organized network
MIMO multiple-input multiple-output SRIT set of RITs
MISO multiple-input single-output SWIPT simultaneous wireless information and
mMIMO massive MIMO power transfer
mmWave millimeter wave THz terahertz
ML machine learning TDD time-division duplex
mMTC massive MTC TR technical report
ModCod modulation and coding TSG technical specifications group
MoU memorandum of understanding TSG RAN TSG radio access network
MR mixed reality TSG SA TSG service and system aspects
MTC machine-type communications TX transmitter
MWC Mobile World Congress U2X UAV-to-everything
NFV network function virtualization UAS unmanned aerial system
NG-RAN next-generation RAN UAV unmanned aerial vehicle
NGMN Next-Generation Mobile Networks UDN ultra-dense network
NICT Japanese National Institute of Communica- UE user equipment
tion and Technology UFMC universal filtered multi-carrier
NMT Nordic Mobile Telephony UK United Kingdom
NOMA non-orthogonal multiple access UL uplink
NR New Radio umMIMO ultra-massive MIMO
NTNs non-terrestrial networks UMTS Universal Mobile Telecommunications
NTT Nippon Telegraph and Telephone System
OFDM orthogonal frequency-division multiplexing URLLC ultra-reliable low-latency communications
OMA orthogonal multiple access US United States
O-RAN open RAN UTM UAS traffic management
OWC optical wireless communications UV ultraviolet
PAPR peak-to-average-power ratio V2I vehicle-to-infrastructure
PDC Personal Digital Cellular V2N vehicle-to-network
PD-NOMA power-domain NOMA V2P vehicle-to-pedestrian
PHY physical V2V vehicle-to-vehicle
PHz petahertz V2X vehicle-to-everything
PIN positive-intrinsic-negative VL visible light
PLMN public land mobile network VLC visible light communications
PN private network VR virtual reality
PSK phase-shift keying WET wireless energy transfer
QAM quadrature amplitude modulation WiFi wireless fidelity
QoS quality of service WIPT wireless information and power transfer
QPSK quadrature phase-shift keying W-OFDM windowed OFDM
RAN radio access network WP working party
R&D research and development WPT wireless power transfer
RFID radio frequency identification WRC World Radio Conference
RIS reconfigurable intelligent surfaces XL-MIMO extremely large-scale MIMO
RIT radio interface technology XR extended reality
S&C sensing and communication
SAGIN space-air-ground integrated network
SBA service-based architecture XIV. ACKNOWLEDGMENT
SCS subcarrier spacing
SDN software-defined networking The authors would like to thank graphical designer Salla-
SIC successive interference cancellation maari Syrjä for helping with the figures. The language of the
SIM subscriber identity module article has been checked using Paperpal, as recommended in
the submission guidelines of the IEEE Access.
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[634] S. Eswaran and P. Honnavalli, “Private 5G networks: a survey on Tuomo Hänninen is a Research Director at the Cen-
enabling technologies, deployment models, use cases and research tre for Wireless Communications (CWC) in the Uni-
directions,” Telecommunication Systems, vol. 82, no. 1, pp. 3–26, 2023. versity of Oulu. He holds a M.Sc. degree in electron-
[635] M. Maman, E. Calvanese-Strinati, L. N. Dinh, T. Haustein, ics and D.Sc. degree in telecommunications. He has
W. Keusgen, S. Wittig, M. Schmieder, S. Barbarossa, M. Merluzzi, been coordinating several applied research projects
F. Costanzo et al., “Beyond private 5G networks: applications, ar- and activities in the field of Spectrum Sharing, Crit-
chitectures, operator models and technological enablers,” EURASIP J. ical Communication, IoT, Energy, Unmanned Aerial
Wireless Comm. and Netw., vol. 2021, no. 1, pp. 1–46, 2021. Vehicles (UAVs) and 5G/6G Test Network. Cur-
[636] J. Collin, J. Pellikka, and J. T. J. Penttinen, 5G Private Network rently, he is coordinating one of the four Strategic
Guidelines for Industry Verticals. Wiley-IEEE Press, 2024, pp. 205– Research Areas of 6G Flagship research programme:
218. Human-centric Wireless Services.
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J. Commun. Soc., vol. 2, pp. 1094–1122, May 2021.
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[639] B. Mao, J. Liu, Y. Wu, and N. Kato, “Security and privacy on 6G Oskari Tervo received the D.Sc. (Tech.) degree
network edge: A survey,” IEEE Commun. Surveys Tuts., vol. 25, no. 2, from the University of Oulu, Finland, in 2018 with
pp. 1095–1127, 2nd Quart. 2023. distinction. In 2014 and 2016, he was a Visiting
[640] D. Je, J. Jung, and S. Choi, “Toward 6G security: Technology trends, Researcher at Kyung Hee University, Seoul, South
threats, and solutions,” IEEE Commun. Stand. Mag., vol. 5, no. 3, pp. Korea, and the Interdisciplinary Centre for Security,
64–71, Sep. 2021. Reliability and Trust, University of Luxembourg,
[641] V.-L. Nguyen, P.-C. Lin, B.-C. Cheng, R.-H. Hwang, and Y.-D. Lin, Luxembourg City, Luxembourg, respectively. He is
“Security and privacy for 6G: A survey on prospective technologies and currently working at Nokia Bell Labs, Oulu. His cur-
challenges,” IEEE Commun. Surveys Tuts., vol. 23, no. 4, pp. 2384– rent research interests include physical layer aspects
2428, 4th Quart. 2021. for cellular standardization.
[642] Y. Sun, J. Liu, J. Wang, Y. Cao, and N. Kato, “When machine learning
meets privacy in 6G: A survey,” IEEE Commun. Surveys Tuts., vol. 22,
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J. Bechtold, I. Morales, R.-A. Stoica, G. Abreu, and H. Haas, “Physical-
layer security in 6G networks,” IEEE Open J. Commun. Soc., vol. 2,
pp. 1901–1914, Aug. 2021.
[644] H. Guo, J. Li, J. Liu, N. Tian, and N. Kato, “A survey on space-air- Antti Tölli (M’08–SM’14) is a Professor with the
ground-sea integrated network security in 6G,” IEEE Commun. Surveys Centre for Wireless Communications (CWC), Uni-
Tuts., vol. 24, no. 1, pp. 53–87, 1st Quart. 2022. versity of Oulu. He received the Dr.Sc. (Tech.) de-
[645] A. Chorti, A. N. Barreto, S. Köpsell, M. Zoli, M. Chafii, P. Sehier, gree in electrical engineering from the University of
G. Fettweis, and H. V. Poor, “Context-aware security for 6G wireless: Oulu, Oulu, Finland, in 2008. From 1998 to 2003, he
The role of physical layer security,” IEEE Commun. Stand. Mag., vol. 6, worked at Nokia Networks as a Research Engineer
no. 1, pp. 102–108, Mar. 2022. and Project Manager both in Finland and Spain. In
[646] M. Mitev, A. Chorti, H. V. Poor, and G. P. Fettweis, “What physical May 2014, he was granted a five year (2014-2019)
layer security can do for 6G security,” IEEE Open J. Veh. Technol., Academy Research Fellow post by the Academy
vol. 4, pp. 375–388, Mar. 2023. of Finland. During the academic year 2015-2016,
[647] H. Sedjelmaci, K. Tourki, and N. Ansari, “Enabling 6G security: The he visited at EURECOM, Sophia Antipolis, France,
synergy of zero trust architecture and artificial intelligence,” IEEE while from August 2018 till June 2019 he was visiting at the University of
Network, Early Access, Oct. 2023. California Santa Barbara, USA. He has authored numerous papers in peer-
[648] S. Zhang, D. Zhu, and Y. Liu, “Artificial intelligence empowered reviewed international journals and conferences and several patents all in the
physical layer security for 6G: State-of-the-art, challenges, and op- area of signal processing and wireless communications. His research interests
portunities,” Computer Networks, vol. 242, 2024. [Online]. Available: include radio resource management and transceiver design for broadband
https://www.sciencedirect.com/science/article/pii/S1389128624000872 wireless communications with a special emphasis on distributed interference
[649] G. Tripi, A. Iacobelli, L. Rinieri, and M. Prandini, “Security and trust management in heterogeneous wireless networks. From 2017 to 2021 he
in the 6G era: Risks and mitigations,” Electronics, vol. 13, no. 11, 2024. served as an Associate Editor for IEEE Transactions on Signal Processing.
[Online]. Available: https://www.mdpi.com/2079-9292/13/11/2162
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J. Reed, “A systematic survey on 5G and 6G security considerations,
challenges, trends, and research areas,” Future Internet, vol. 16, no. 3,
2024. [Online]. Available: https://www.mdpi.com/1999-5903/16/3/67
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intelligence for the 6G network security: Impacts and challenges,”
arXiv:2404.08643, 2024. Matti Latva-aho (IEEE Fellow) received the M.Sc.,
Lic.Tech. and Dr. Tech (Hons.) degrees in Electrical
Engineering from the University of Oulu, Finland
in 1992, 1996 and 1998, respectively. From 1992 to
1993, he was a Research Engineer at Nokia Mobile
Harri Pennanen (M’16) received the D.Sc. (Tech.) Phones, Oulu, Finland, after which he joined the
degree in telecommunications from the Centre for Centre for Wireless Communications (CWC) at the
Wireless Communications (CWC), University of University of Oulu. Prof. Latva-aho was Director of
Oulu, Oulu, Finland, in 2015 with distinction. In CWC during the years 1998-2006 and Head of the
2015, he was a Research Associate in the Inter- Department for Communication Engineering until
disciplinary Centre for Security, Reliability, and August 2014. Currently, he is a Professor at the
Trust, University of Luxembourg, Luxembourg City, University of Oulu on wireless communications and Director for the National
Luxembourg. He is currently a Senior Researcher 6G Flagship Programme. He is also a Global Fellow at Tokyo University.
in CWC at the University of Oulu. His research Prof. Latva-aho has published over 500 conference or journal papers in the
interests include 6G and beyond networks. field of wireless communications. He received the Nokia Foundation Award
in 2015 for his achievements in mobile communications research.