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 Intelligent Sensing
and Communications
for Internet of
Everything
This page intentionally left blank
 Intelligent Sensing
and Communications
for Internet of
Everything

Zhengyu Zhu
School of Information Engineering,
Zhengzhou University,
Zhengzhou, China

Zheng Chu
Institute for Communication Systems,
University of Surrey,
Guilford, United Kingdom
Xingwang Li
School of Physics and Electronic Information Engineering,
Henan Polytechnic University,
Jiaozuo, China
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Contents

CHAPTER 1 Background and introduction . . . . . . . . . . . . . . . . . . . . 1

Zhengyu Zhu, Zheng Chu, and Xingwang Li
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2.1 Progress of 6G around the world . . . . . . . . . . . . . . . . . 2
1.2.2 6G vision and its performance indicators . . . . . . . . . . . 5
1.2.3 Potential key technologies of 6G . . . . . . . . . . . . . . . . . 8
1.3 Suggestions to promote 6G research and development . . . . . . 12

CHAPTER 2 Three major operating scenarios of 5G: eMBB,

mMTC, URLLC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Zhengyu Zhu, Xingwang Li, and Zheng Chu
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.1 The comprehensive introduction for eMBB . . . . . . . . . 17
2.1.2 The comprehensive introduction for mMTC . . . . . . . . 17
2.1.3 The comprehensive introduction for URLLC . . . . . . . . 18
2.2 Opportunistic spectrum sharing for D2D-based URLLC . . . . . 20
2.2.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.2.2 Optimal resource allocation . . . . . . . . . . . . . . . . . . . . . 24
2.2.3 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.4 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.2.5 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.3 Cooperative wireless-powered NOMA relaying for B5G IoT
networks with hardware impairments and channel estimation
errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.3.2 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.3.3 Exact outage probability . . . . . . . . . . . . . . . . . . . . . . . 43
2.3.4 Asymptotic OP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.3.5 Energy efficiency (EE) . . . . . . . . . . . . . . . . . . . . . . . . 48
2.3.6 Power optimization for the sum rate . . . . . . . . . . . . . . 49
2.3.7 Performance evaluation results and discussion . . . . . . . 51
2.3.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
2.4 I/Q imbalance aware nonlinear wireless-powered relaying of
B5G networks: security and reliability analysis . . . . . . . . . . . 56
2.4.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

v
vi Contents

2.4.2 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 60

2.4.3 Outage probability analysis . . . . . . . . . . . . . . . . . . . . . 60
2.4.4 Intercept probability analysis . . . . . . . . . . . . . . . . . . . . 63
2.4.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
CHAPTER 3 Backscatter technology and intelligent reflecting
technology surface technology in the Internet of
Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Zhengyu Zhu, Zheng Chu, and Xingwang Li
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.1.1 The classification of backscatter communication
systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
3.1.2 Fundamental of backscatter modulations . . . . . . . . . . . 81
3.1.3 Interplay of backscatter with other technologies . . . . . . 82
3.1.4 The physical layer security . . . . . . . . . . . . . . . . . . . . . 85
3.1.5 Intelligent reflecting surface assisted wireless powered
IoT networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
3.2 Secrecy analysis of ambient backscatter NOMA systems under
I/Q imbalance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.2.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.2.2 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 90
3.2.3 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
3.2.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
3.3 Hardware impaired ambient backscatter NOMA systems:
reliability and security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
3.3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
3.3.2 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 100
3.3.3 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
3.3.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
3.4 Physical layer security of cognitive ambient backscatter
communications for green Internet-of-Things . . . . . . . . . . . . . 116
3.4.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
3.4.2 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 118
3.4.3 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
3.4.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
3.5 Future research prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
3.5.1 Security and privacy . . . . . . . . . . . . . . . . . . . . . . . . . . 130
3.5.2 Backscatter communication circuitry design . . . . . . . . 130
3.5.3 EM energy harvester . . . . . . . . . . . . . . . . . . . . . . . . . . 130
3.5.4 Hardware impairments . . . . . . . . . . . . . . . . . . . . . . . . 130
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
 Contents vii

CHAPTER 4 Unmanned aerial vehicle technology in IoE . . . . . . . 137

Zhengyu Zhu, Zheng Chu, and Xingwang Li
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
4.1.1 Research status and development trend . . . . . . . . . . . . 138
4.1.2 Research on transmission theory of UAV
Communication System . . . . . . . . . . . . . . . . . . . . . . . 138
4.1.3 Physical layer security of wireless power supply
network based on IRS-UAV . . . . . . . . . . . . . . . . . . . . . 139
4.1.4 Channel estimation and beamforming for UAV
Communication System . . . . . . . . . . . . . . . . . . . . . . . 139
4.2 Energy efficiency characterization in heterogeneous IoT
system with UAV swarms based on wireless power transfer . . 140
4.2.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
4.2.2 Transmission probability of the IoT-Ts . . . . . . . . . . . . 147
4.2.3 Coverage probability . . . . . . . . . . . . . . . . . . . . . . . . . . 150
4.2.4 Energy efficiency . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
4.2.5 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
4.2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
4.3 UAV-aided multiway NOMA networks with residual hardware
impairments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
4.3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
4.3.2 Achievable sum rate analysis . . . . . . . . . . . . . . . . . . . . 161
4.3.3 Numerical results & discussion . . . . . . . . . . . . . . . . . . 164
4.3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
4.4 A unified framework for HS-UAV NOMA networks:
performance analysis and location optimization . . . . . . . . . . . 167
4.4.1 System model and fading model . . . . . . . . . . . . . . . . . 168
4.4.2 Outage probability analysis . . . . . . . . . . . . . . . . . . . . . 172
4.4.3 Outage probability . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
4.4.4 Location optimization . . . . . . . . . . . . . . . . . . . . . . . . . 175
4.4.5 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
4.4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
4.5 Future research prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

CHAPTER 5 MmWave technology and Terahertz technology IoT

communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Zhengyu Zhu, Xingwang Li, and Wanming Hao
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
5.1.1 mmWave technology IoT communications . . . . . . . . . 186
5.1.2 Terahertz technology IoT communications . . . . . . . . . 188
5.1.3 MIMO-OFDMA Terahertz IoT networks . . . . . . . . . . . 190
viii Contents

5.2 Hybrid precoding design for wideband THz massive

MIMO-OFDM systems with beam squint . . . . . . . . . . . . . . . . 191
5.2.1 Antenna structure and hybrid precoding design . . . . . . 192
5.2.2 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
5.2.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
5.3 Robust beamforming designs in secure MIMO SWIPT IoT
networks with a non-linear channel model . . . . . . . . . . . . . . . 197
5.3.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
5.3.2 Problem formulation and robust design methods . . . . . 200
5.3.3 Computational complexity . . . . . . . . . . . . . . . . . . . . . 214
5.3.4 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
5.3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
5.4 Robust design for intelligent reflecting surface assisted
MIMO-OFDMA Terahertz IoT networks . . . . . . . . . . . . . . . . 219
5.4.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
5.4.2 Solution of the weighted sum rate optimization problem 222
5.4.3 Extension to imperfect CSIs from IRS to users . . . . . . 227
5.4.4 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
5.4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
5.4.6 Proof of Theorem 5.4.1 . . . . . . . . . . . . . . . . . . . . . . . . 237
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
CHAPTER 6 Artificial intelligence technology in the Internet of
things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Zhengyu Zhu, Miao Zhang, and Wanming Hao
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
6.2 Exploiting deep learning for secure transmission in an
underlay cognitive radio network . . . . . . . . . . . . . . . . . . . . . . 246
6.2.1 System model and problem formulation . . . . . . . . . . . 248
6.2.2 Conventional optimization based power allocation
approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
6.2.3 Power allocation framework based on NN . . . . . . . . . . 252
6.2.4 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
6.2.5 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
6.2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268
6.3 Q-learning based task offloading and resources optimization
for a collaborative computing system . . . . . . . . . . . . . . . . . . . 269
6.3.1 System model and problem formulation . . . . . . . . . . . 269
6.3.2 Wireless communication model . . . . . . . . . . . . . . . . . . 272
6.3.3 MDP model of offloading decision process . . . . . . . . . 273
6.3.4 Communication and computation resources
optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
6.3.5 QLOF algorithm for optimal offloading scheme . . . . . . 283
6.3.6 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284
 Contents ix

6.3.7 The impacts of computing frequency of edge cloud . . . 290

6.3.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
CHAPTER 7 Fog/edge computing technology and big data
system with IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
Zhengyu Zhu, Ming Zeng, and Wanming Hao
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
7.1.1 MEC: overview and resource allocation . . . . . . . . . . . . 300
7.1.2 Massive MIMO-assisted MEC . . . . . . . . . . . . . . . . . . . 302
7.2 Edge cache-assisted secure low-latency millimeter wave
transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
7.2.1 Related works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304
7.2.2 System model and problem formulation . . . . . . . . . . . 305
7.2.3 Problem formulation . . . . . . . . . . . . . . . . . . . . . . . . . . 310
7.2.4 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317
7.2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
7.3 Delay minimization for massive MIMO assisted mobile edge
computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
7.3.1 System model and problem formulation . . . . . . . . . . . 324
7.3.2 Problem formulation . . . . . . . . . . . . . . . . . . . . . . . . . . 325
7.3.3 Joint resource allocation for the perfect CSI case . . . . . 326
7.3.4 Joint resource allocation for the imperfect CSI case . . . 327
7.3.5 Numerical results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
7.3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332
7.4 Future research directions . . . . . . . . . . . . . . . . . . . . . . . . . . . 332
7.4.1 NOMA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332
7.4.2 MmWave . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
7.4.3 HetNets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337
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 CHAPTER

Background and
introduction

Zhengyu Zhua , Zheng Chub , and Xingwang Lic

1
a School
of Information Engineering, Zhengzhou University, Zhengzhou, China
b Institute
for Communication Systems, University of Surrey, Guildford, United Kingdom
c School of Physics and Electronic Information Engineering, Henan Polytechnic University,

Jiaozuo, China

1.1 Background
The information and communication industry is the basic industry for constructing
national information and providing network and information services. As the most
active, widely used and influential technology field in the world, network informa-
tion technology is an important foundation and key support for economic and social
development, with a strategic and pioneering position. With the rapid development of
the Internet, the Internet of Things, cloud computing, big data, artificial intelligence
and other technologies, the content of the information and communications industry
has been constantly enriched, extending from traditional telecommunications and In-
ternet services to new forms of business such as the Internet of Things. At present,
everything is connected and information is exchanged. The Internet has increasingly
become the basis and platform for people’s production and life, which has greatly
improved people’s cognition of the world.
At present, the new generation of the wireless network is being promoted in depth,
a batch of new wireless services will be applied. However, the new network system
is more complex, heterogeneous and dynamic than before, and the network business
is also diversified and personalized with the development of The Times and the needs
of users. 5G aims to meet the information consumption needs of individual users, and
at the same time penetrate into various industries and fields of society, so as to up-
grade the mobile communication network from consumer applications to industrial
applications. Although the use of 5G is becoming more and more popular, some of its
technical means are still not mature enough to meet people’s initial requirements and
expectations of 5G, and there are problems of limited space range and insufficient
performance indicators in terms of information interaction. For example, from the
perspective of the space coverage of the communication network, 5G is still a diffuse
coverage centered on the base station. There will be communication blind areas in
the desert, no man’s land, ocean, and other areas not covered by the base station. It is
estimated that more than 80% of the land area and more than 95% of the ocean area
will still have no mobile network signal in the 5G era. In addition, from the perspec-
Intelligent Sensing and Communications for Internet of Everything. https://doi.org/10.1016/B978-0-32-385655-3.00005-9
Copyright © 2022 Elsevier Inc. All rights reserved.
1
2 CHAPTER 1 Background and introduction

tive of network performance requirements for industrial applications, 5G provides

performance indicators such as large bandwidth, low latency and wide connection
with obvious advantages over 4G, but it still fails to meet the intelligent commu-
nication requirements for virtual reality, autonomous driving, telemedicine, and the
Internet of Everything in real life. This has stimulated the research and exploration
of the more advanced and perfect communication systems. People expect to achieve
the key performance indicators required by virtual reality and automatic driving in
6G network, and also carry out the research on 6G vision, enablement, and some po-
tential key technologies from this starting point. In addition, since the birth system
for mobile communications, mobile communications and the development of related
technology changes with each passing day, the mobile communication development
has “the use of one generation, the construction, research and development genera-
tion”, since the 1980s, basically follow the update generation every ten years, and
every generation communication system from research into the commercial deploy-
ment of all need about 5 ∼ 10 years (this is shown in Fig. 1.1). Therefore, when
the previous generation of mobile communication system into commercial use, it is
necessary to synchronously look forward to the communication needs of the future
information society, and carry out research on the system concept and technology of
the next generation of mobile communication.

FIGURE 1.1
Evolution of mobile communication (1G∼6G).

1.2 Introduction
1.2.1 Progress of 6G around the world
The competition of 5G is still in full swing, the pace of commercialization has just
begun, and the more advanced 6G communication has quietly laid out strategically.
Starting to study 6G will not affect the commercialization of 5G, but will dig out some
advanced technologies to be applied in 5G evolution system, which will promote the
long-term vitality of 5G.
 1.2 Introduction 3

• On November 3, 2019, China established the National 6G Technology Research

and Development Promotion Working Group and the General Expert Group,
marking the official launch of China’s 6G R&D. In terms of technology research
and development, Chinese company Huawei has started to develop 6G technol-
ogy, which will be pushed forward in parallel with 5G technology. Huawei has
set up a 6G research and development lab in Ottawa, Canada, which is currently
in the early stage of the theoretical exchange. Huawei has proposed that 6G will
have a wider spectrum and higher speed, and should be extended to sea, land,
air, and even underwater space. In terms of hardware, antennas will be even more
important. On the software side, artificial intelligence will play an important role
in 6G communication. In the field of terahertz communication technology, China
Huaxun Ark, Sun Chuang Electronics, Hengtong Optoelectronics, and other com-
panies have also begun to the layout. On April 26, 2019, the Millimeter Wave
Terahertz Industry Development Alliance was established in Beijing. On the op-
erator side, China Telecom, China Mobile, and China Unicom have all started
6G research and development. China Mobile and Tsinghua University have es-
tablished a strategic partnership to conduct scientific research cooperation in key
areas such as 6G communication network and next-generation Internet technol-
ogy. China Telecom is working on 6G technology with millimeter-wave as the
main frequency and terahertz as the second frequency. China Unicom has carried
out research on 6G terahertz communication technology.
• As early as 2018, Federal Communications Commission (FCC) officials envi-
sioned 6G systems. In September 2018, US FCC officials for the first time in
public in the prospect of 6G technology, proposed that 6G will use terahertz fre-
quency band, 6G base station capacity will be up to 1,000 times that of 5G base
station. In 2019, the United States decided to open up part of the terahertz spec-
trum to promote the development of 6G technology experiments. In early 2019,
US President Donald Trump publicly vowed to accelerate the development of US
6G technology. In March 2019, the FCC announced the opening of the 95 GHz-
3 THz band as an experimental spectrum, which could be used for 6G services
in the future. In terms of technology research, the United States currently mainly
sponsors universities to carry out related research projects, mainly to carry out
early research on 6G technology containing chips. The New York University Wire-
less Center (NYUWireless) is rolling out wireless technology that uses terahertz
frequency channels to transmit at speeds up to 100 Gbps. The Comsenter Research
Center at the University of California has received a $27.5 million grant to conduct
research on “integrated terahertz communication and sensing.” The Nano Com-
munication Integrated Circuits Laboratory at the University of California, Irvine,
has developed a tiny wireless chip operating at 115 GHz to 135 GHz, capable
of transmitting at a rate of 36 Gbps over a distance of 30 cm. According to the
Virginia Tech study, 6G will learn and adapt to human users, the era of the smart-
phone will come to an end, and we will see the development of communication on
wearable devices. The United States is far ahead in integrated communications be-
tween space, space and Haiti, especially in satellite Internet communications. By
4 CHAPTER 1 Background and introduction

the end of February 2020, SpaceX had successfully launched nearly 300 Starlink
satellites, making it by far the world’s largest commercial satellite operator with
the largest number of satellites. The company expects to be able to start offering
satellite Internet broadband service in the US as early as mid-2020.
• As the first country in the world to realize the commercialization of 5G, South
Korea is also one of the first countries to carry out 6G research and development.
In April 2019, the Korea Institute of Communication and Information Science
held the 6G Forum, officially announced the beginning of 6G research and set up
a 6G research team, with the task of defining 6G and its use cases/applications
and developing 6G core technologies. In January 2020, the Korean government
announced that it would take the lead in commercial 6G in the world in 2028.
To this end, the Korean government and enterprises will jointly invest 976 bil-
lion won. South Korea’s 6G R&D project has passed the technical evaluation of
the feasibility study. In addition, among the 14 strategic topics announced by the
Ministry of Science, Information and Communication Technology of Korea, the
research and development of wireless devices for 6G over 100 GHz is listed as
the “first” topic. In terms of technology research and development, a number of
enterprise 6G research centers have been set up by leading communication enter-
prises in Korea. South Korea LG announced the establishment of 6G laboratory in
January 2019. In June, SK, the largest mobile operator in South Korea, announced
that it would establish a strategic partnership with Ericsson and Nokia to jointly
develop 6G technology, and promote the early development of South Korea in the
6G communication market. Samsung Electronics also set up a 6G research center
in 2019, and plans to cooperate with SK Telecom to develop 6G core technol-
ogy and explore 6G business model, with blockchain, 6G and Al as the future
development direction.
• Japan plans to formulate a comprehensive strategy to achieve “post-5G” (6G) by
2030 through cooperation between the government and the people. According to
reports, the program is chaired by the president of Tokyo University in Japan,
and technology giants such as Toshiba in Japan will provide full technical support
to summarize the 6G comprehensive strategy by June 2020. Japan has obvious
global leading advantages in terahertz and other electronic communication ma-
terials, which is its unique advantage in developing 6G. Hiroshima University
cooperated with the Information and Communication Research Institute (NICT)
and Panasonic Corporation, and first realized terahertz communication in 300 GHz
band based on CMOS low-cost technology in the world. The equipment technol-
ogy laboratory of Japan Telegraph and Telephone Corporation (NTT) Group has
developed 6G ultra-high-speed chips with transmission speed five times as high
as 5G by using InP compound semiconductors. At present, the main problem is
that the transmission distance is extremely short, and there is still a long distance
from real commercial use. In June 2019, NTT Group put forward an idea called
“IOWN”, hoping that this idea can become a global standard. At the same time,
NTT has cooperated with Sony and Intel in the research and development of 6G
and will launch this network technology around 2030.
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