Wireless Personal Communications (2021) 118:1775–1792

https://doi.org/10.1007/s11277-021-08115-w

A Survey on Advanced Multiple Access Techniques for 5G

and Beyond Wireless Communications

Harshita Mathur1 · T. Deepa1

Accepted: 14 January 2021 / Published online: 31 January 2021

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021

Abstract
This paper summarizes the ongoing research initiatives based on the advanced multiple
access techniques towards the fifth generation (5G) wireless communication and beyond.
Prior cellular network generations have embraced various multiple access techniques with
a common feature that is to have orthogonal signals at the side of the receiver for different
users. The diverse requirements of huge number of connections about latency and through-
put is the need of the hour. Therefore, 5G wireless systems and beyond, are preferring the
design method to shift towards non-orthogonal from orthogonal in multiple access tech-
niques. The paper will mainly focus on the non-orthogonal multiple access techniques con-
sidering the types of its candidates in multiple domains which can help us in identifying
the impacts on the designs of multiple access for 5G network and beyond. This survey aims
to discover the obstacles and possibilities of utmost importance for multiple access designs
for 5G networks.

Keywords  Multiple access techniques · 5G · 5G and beyond · NOMA

1 Introduction

Cellular communication technologies have evolved from second generation (2G) Global
system for mobile communication (GSM) to fourth generation (4G) Long term evolu-
tion—Advanced (LTE-A) during the  last two decades. An array of multiple access tech-
niques (MA) is  used by the cellular standards including frequency division multiple
access (FDMA), Time division multiple access (TDMA), Code division multiple access
(CDMA), and orthogonal-frequency division multiple access (OFDMA) which are a form
of orthogonal multiple access (OMA) [1]. Here, theoretically, there is no interference with
one another while sharing the wireless medium except in CDMA, where non-orthogonal
transmission takes place from wireless device to base station. In OFDMA, at various time

* Harshita Mathur
harshitm@srmist.edu.in
T. Deepa
deepat@srmist.edu.in
1
Department of Electronics and Communication Engineering, SRM Institute of Science
and Technology, SRM Nagar, Kattankulathur‑603203, Chengalpattu District, Tamil Nadu, India

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 1776 H. Mathur, T. Deepa

slots, clients are assigned to the different categories of sub carriers. OFDMA is still uti-
lized for the next-generation cellular systems where the duration of the time slot and the
sub-carrier spacing is flexible for supporting wide varieties of use cases and needs.
Therefore, 5G advancement and 6th generation (6G) innovation is expected to be a
prominent candidate for bolstering industry and society in the 2030s. The  third genera-
tion partnership project (3GPP) suggests four key applications that need to be backed by
5G networks. They comprise massive machine type communications (mMTC), enhanced
mobile broadband (eMBB), ultra-reliable and low-latency communications (URLLC), and
the enhanced vehicle-to-everything (eV2X) communications. 5G needs to fulfill the new
requirements of all these applications such as improved spectral efficiency (SE) and high
system throughput catering to massive connectivity by exploring new modulations and
multiple access schemes. 4G and current broadband transmission have adopted orthogonal
frequency division multiplexing (OFDM) method wherewith simple detection scheme and
appropriate cyclic prefix, it can avoid the wireless channel’s delay spread. However, the
broad requirements of the 5G networks are not satisfied by the OFDM system.
The notion of multicarrier modulation (MCM) has appeared in [2] which explained the
practical implementation using the  Fast Fourier transform method. Access to frequency
selective channels is allowed by MCM which uses high gain links and at the same time
avoids fading dips. 4G LTE has been using OFDM in the downlink (DL) due to the benefits
of the MCM techniques [3]. OMA is fundamental to all the wireless networks in which
resource blocks (RB) are orthogonally divided in to three domains such as time, frequency,
and code. Hence, signal detection becomes easy since there is minimal interference among
adjacent blocks. However, a  reduced number of users can be supported by OMA on
account of restrictions in the total number of orthogonal RB, which restricts spectral effi-
ciency and network capacity. By the provision of a huge number of and various categories
of applications and their users within 5G networks, multiple nonorthogonal multiple access
(NOMA) techniques have been proposed. Same resource elements are shared by multiple
users in the NOMA technique. While CDMA has been considered as an OMA technique
by a  majority of recent works [4, 5]. With the expansion of Internet-empowered smart
devices, its creative implementations are enabled by complex new services facilitated by
the advancement of 5G systems that require new MA strategies. NOMA is classified into
the  following classes, (1) code-domain NOMA (2) power domain NOMA [6–9]. Power
domain NOMA makes sure that several clients are given services inside a given RB. At the
transmitter side, this is assisted by superposition coding (SC) and on the receiver side by
successive interference cancellation (SIC), which is on a considerably basic level unique
with the great OMA methods. NOMA is equipped for exploiting the accessible assets more
productively by deftly benefiting from the client’s particular channel situations and it is
fit for serving various clients at various QoS prerequisites in a similar RB. OMA modula-
tion techniques are classified based on pulse shaping, subband filtering, and other modula-
tion techniques [10–13]. Major emphasis is on the classification of NOMA in this paper.
The most prominent agent code-domain NOMA strategies [14, 15] incorporate, Interleave
division MA (IDMA), and low-density spreading CDMA (LDS-CDMA) and LDS-OFDM.
These arrangements are supplemented by the more as of late proposed multiuser shared
access (MUSA) system, pattern division MA (PDMA) and sparse code multiple access
(SCMA), the building block sparse constellation based OMA (BOMA), and Lattice parti-
tion multiple access (LPMA)as shown in Fig. 1.
The remaining paper is as follows. Section 2 describes what leads to NOMA as a 5G
wireless candidate. Section 3 explains about the concept of NOMA followed by Sect. 6
which gives the detail about the categories of NOMA. Section 5 explains the superiority

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Fig. 1  Modulation techniques in 5G communication and beyond

of NOMA over OMA. Opportunities and challenges faced by NOMA are discussed in
Sect. 6. Section 7 comprises some simulation results which explain the basics and few
parameters associated with NOMA followed by the conclusion in Sect.  8 and future
work in Sect. 9.

2 What Leads to NOMA?

Requirements of 5G communication and the network includes a peak data rate minimum

of 10 Gbps (100 times greater than 3GPP-LTE), a latency of 1  ms (10 times smaller
than 4G networks), and a connection density of 1,000,000 devices that are per km (100
times greater than 4G networks) [16]. NOMA can address all these challenges more
efficiently and in a better way than the traditional OFDM scheme by letting many users
to share all domains, time, frequency, and space, in the next generation of the wireless
network. The main features of NOMA can be summarized as:

1. RB (time/code/frequency) can be exploited by multiple users which exhibits the fact of

high spectral efficiency in NOMA [17, 18].
2. At the base station, perfect uplink channel state information is not needed in the case of
NOMA. In the channel feedback, only received signal strength (RSS) information has
to be incorporated.
3. NOMA supports greater connectivity for a large number of smart devices and can
support multiple users within one RB which is one of the most important features of
the internet of things (IoT) devices that require a multiple users with low data rates.
4. It is not needed to schedule requests from users to the base stations in the uplink-NOMA
which is a requirement in case of OMA. Therefore, transmission latency reduces in
NOMA and a grant free uplink transmission can be recognized.

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 1778 H. Mathur, T. Deepa

3 Concept of NOMA

In a NOMA cluster, the superposition of different message signals of the different users is
allowed [19]. When the user will be in the downlink and the base station in the uplink, the
detection, and decoding of the desired message signal is done by applying signal interfer-
ence cancellation at the receiver side.

3.1 NOMA Downlink Transmission

In the transmitter section of the downlink NOMA, the base station transfers the joined sig-
nal. That is the superposition of ideal waves of numerous clients with numerous distributed
power coefficients, to every single mobile user. In the receiver section of every client, the
successive interference cancellation on the system is believed to be implemented continu-
ously till the customer’s signal is regained. Power coefficients of customers are allotted
by the conditions of the channel, in an oppositely related approach. The customer has an
awful channel condition is administered greater transmission power compared to one that
has a better than average channel condition [20]. Therefore, the client with the most raised
transmission power thinks about the signal of various clients as clatter, it recovers its signal
expeditiously instead of implementing the SIC strategy. In any case, various clients need
to perform SIC forms. In SIC, all the signals that are more grounded than an individual
client’s grounded optimal signal are recognized by their receiver. Then, these signals are
deducted from the acquired signal as shown in Fig. 2 where s: transmitter. This strategy is
continued till the related customer’s inherent signal is settled or decided [21–23]. Lastly,
every client disentangles their inherent signals by treating various clients with neither
power coefficients as obstruction or commotion. The transmitted signal at the base station
can be formed as given below:
L
� √
S= bz PS xz (1)
z=1

where xz is the client z ( Uz ) information with unit energy. PS is the transmission power at
∑L
the base station and bz is the power coefficient allocated for client z subjected to z=1 bz = 1
and b1 ≥ b2 ≥ ⋯ ≥ bL since with no loss of channel gains are believed to be ordered as
|h1 |2 ≤ |h2 |2 ≤ ⋯ ≤ |hL |2 where hl is the channel coefficient of the lth client depending
upon NOMA. The received signal at lth client can be expressed as:

Fig. 2  Downlink NOMA transmission

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Yl = hl S + nl (2)
where nl is zero mean complex additive Gaussian noise with the variance of 𝜎 2.

3.2 NOMA Uplink Transmission

In the uplink, individual signals are transmitted by each of the users with a transmit power.
Power transmitted per user is restricted to the user’s highest possible battery power. While
the channel gains of the users are different, users can individually use the battery power to
its maximum [24–27]. In this network, the signal is transmitted to the base station by the
mobile user as shown in Fig. 3 where r: receiver. At the BS, SIC cycles are done to iden-
tify the signals of clients. By accepting that the downlink, as well as the uplink channels,
are complementary to each other and the base station imparts power allocation coefficients
to mobile clients, the wave which has been received at the base station for synchronic
uplink-NOMA can be written as:
L
� √
a= hz bz Pxz + n (3)
z=1

where hz : coefficient of channel of the zth user, P: max transmission power that is supposed
to be identical for all the clients, N: zero mean complex additive Gaussian noise with vari-
ance of 𝜎 2.

4 Categories of NOMA

NOMA can be categorized into power, code and multiplexing of NOMA in multiple
domains.

1. Power domain NOMA: It is a favorable multiple access technique for 5G networks [28].
It has been demonstrated that NOMA can improve the capacity of system and user
experiences. This was proved when MUST was proposed. It is in particular a downlink
form of NOMA for 3GPP LTE-A. Power-domain (PD) NOMA helps in distinguishing
the multiple users with varying power levels inside the same time/frequency/code RB.
PD-NOMA only has a single observation as opposed to CDMA or MIMO systems

Fig. 3  Uplink NOMA transmission

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 1780 H. Mathur, T. Deepa

which have multiuser detection [29]. The received signal at the base station in the uplink
transmission of NOMA can be expressed as:
B
� √
y= hb Tb xb + n (4)
b=1

where ­Tb = Transmit power from the bth user, x­ b = Transmit symbol from the bth user,
n = AWGN with variance σ2, B = users number sharing the same RB.
  The received signal-to-interference-noise ratio (SINR) of the bth NOMA user can be
calculated for all correct first detected symbols as:
2
Tb ��hb ��
SINRb = ∑B (5)
a=b+1 Ta �ha �2 + 𝜎 2

2. Code domain NOMA: This scheme allocates multiple transmissions in similar time/
frequency RB by assigning dissimilar codes to diverse users. In contrast with power-
domain NOMA, it has particular spreading and shaping gain with the price of additional
signal bandwidth. Current explanations to code-domain NOMA which have been dis-
cussed here are LDS-CDMA, LDS-OFDM, SCMA, and IDMA.
3. NOMA Multiplexing in Multiple domains: In multiple domains, solutions to the NOMA
have been anticipated to multiplex, for example power, the code, and spatial domain, to
provision massive connectivity for 5G systems. Other forms are PDMA, BOMA, and
LPMA.

NOMA can be executed in different structures, for example, CD (code domain) and PD
(power domain) NOMA. We may arrange the useful types of NOMA likewise into i) single
carrier ii) multiple carrier NOMA. The points of interest and inconveniences for these will
be inspected.

4.1 Single Carrier NOMA (SC‑NOMA)

We start our analysis with single-carrier NOMA to build systems for numerous carrier’s
NOMA structures.

• IDMA: Major thought of the IDMA depends on a remarkable user/client explicit chip
inter-leaver for recognizing the signals of various users. In this way, like chip-inter-
leaved CDMA, IDMA provides an advantage of greatly assorted diversity gain [30]. In
such a case, a few chips get debased; then low-complexity chip-by-chip iterative multi-
user detection (IMD) methodology is used to recover the relating spreading sequence.
• LDS-CDMA: LDPC (low-density parity check) code can be examined to establish an
improved variant of CDMA. For traditional CDMA, a promising arrangement for every
client is to allocate orthogonal spreading sequences respectively, and henceforth to
wipe out obstruction lower-complexity receiver are assembled at receivers. The main
feature of LDS-CDMA is that it is mainly working for the codebook construction [31].
It is similar to in LDPC matrix. Regardless, this orthogonal spreading code configura-
tion is just fit for supporting an equivalent amount of chips and users, which inspires
the improvement of the non-orthogonal spreading code plan. Instead of dense spread-
ing sequences of customary CDMA, alleged sparse spreading sequences are utilized

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as in OVSF (orthogonal variable spreading factor) codes [32]. Such structure requires
refined multiuser deciphering at the side of the receiver. At the receiver, a message-
passing algorithm (MPA) taking into account multiuser-detection, can be implemented
for LDS-CDMA, which is equipped for accomplishing the nearest ML (maximum like-
lihood) detection.
• LPMA: Lattice partition MA is a downlink non-orthogonal, multi-client superposi-
tion transportation scheme. It attains a multiplexing gain in power and code domain.
By super imposing the different power streams, power-domain multiplexing expands
its throughput [33, 34]. Conversely, code-domain multiplexing overlaps a few streams
by taking advantage of the consolidation of lattice codes likewise brings about a lat-
tice code. All added explicitly, LPMA ciphers the data of the client by the application
of lattice coding on the transmitting end and conjures SIC on the receiving end for
revelation. LPMA has the  merit that it has the capability of bypassing hindrance of
PD-NOMA, to be specific the performance gain relies upon the difference of channel
characteristics of the clients. Be that as it may, LPMA forces a greater encoding and
decoding complexity compared to the PD NOMA.

4.2 Multiple‑carrier (MC) NOMA (MC‑NOMA)

According to preferences given to OFDM waveform, this configuration is probably going

to be joined in 5G systems. Primary advantages of MCM are that rather than the short dis-
persal basically for subtle symbols of sequential modems, several of the parallel long-term
spreading safe symbols get transported across the dispersive channels. Henceforth, these
long-span symbols can be smoothed out through a single tap frequency domain equalizer.
In these segments, a few types of MC-NOMA plans are worked upon.

• LDS-OFDM: It is a blend of LDS-CDMA [35] as well as OFDM, and it can be viewed

as a propelled variation of LDS CDMA in a diversified-carrier system. Consequently,
the transmitters use equivalent sparse spreading sequences and the equivalent MPA-
dependent recognition is embraced at the receiver side. The information stream map-
ping procedure comprises of dual stages: (1) every bit of information stream is fore-
most disseminated by the LDS sequences, and (2) information streams are transported
upon various subcarriers by employing OFDM-modulator. Various strategies for map-
ping of spreading sequences on OFDM are present, and all of them have various advan-
tages as well as disadvantages. For instance, each chip might be profiled to an alternate
subcarrier for accomplishing the diversity of the frequency domain. Then again, each
subcarrier may pass on a spread lower-rated stream. Be that as it may, this structure
brings about a higher multifaceted nature because of the utilization of MPA recognition
contrasted with an ordinary OFDMA scheme.
• SCMA: The  sparse codebook is like low density spread based signature matrix.
Through spreading, a certain number of RB can provision more users. Figure 4 shows
the SCMA encoder where six users contribute to four RB. SCMA increases the over-
all connectivity and rate as it supports the overloaded access over the coding domain
[36–39]. The coding, as well as the shaping gain, can be achieved at the same time by
creating the codebook and multi-dimensional modulation constellations. Even though
the same block is shared by the users, another block would be accepted to differentiate
several users during the occurrence of collisions.

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 1782 H. Mathur, T. Deepa

Data 1 2 3 4 5 6

FEC Encoder 1 2 3 4 5 6

SCMA Modulaon codebook mapping 1 1 1 4 5 6

SCMA block

Low density spreading

Fig. 4  Sparse code multiple access encoding

• PDMA: It is a different type of sparse signature matrix-based multiple carriers NOMA.

PDMA permits changeable numerous clients to be plotted to every RB. For instance,
the main client supposedly activates all the subcarriers for transmission, while the 6th
client just initiates a solitary subcarrier [40]. Another principle contrast among PDMA
as well as SCMA is PDMA does not aim for accomplishing a constellation shaping
gain, that gainfully maintains a strategic distance from the complicated multi-spatial
constellation pattern plan of SCMA. On the receiver side, the MPA might likewise
be embraced for combined deciphering, which is like LDS-CDMA as well as SCMA.
Besides, additional MPA SIC location methodologies can likewise be utilized for
improving the decoding performance.
• BOMA: Building blocks sparse constellation-based OMA is a method that  attributes
the information from a user with decent channel state information to the symbols of
a user with inadequate channel state information. This scheme enhances the capacity
of the multiuser system. The configuration of BOMA is simple and easy and has been
accepted in the present 4G systems. To implement BOMA with high- frequency bands
and massive MIMO, some modifications to the software are essential. Changes should
be such that it is compatible with the other 5G requirements as well. Moreover, BOMA
requires no complicated power allocation and successive interference cancellation
receivers that are required for other NOMA schemes.

5 Superiority of NOMA over OMA

• Considering spectral efficiency as well as throughput, in OFDMA a particular fre-

quency asset is allotted to every client even if it encounters a great or awful channel
state; in this way the general framework experiences lower spectral efficiency and also

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lower throughput. In NOMA, almost similar frequency asset is allocated to various

mobile clients, with great and awful channel situations, simultaneously. Consequently,
the resources relegated for the fragile client are likewise brought into use by the power-
ful client, and the obstruction can be alleviated by SIC at the user’s receiver side. Along
these lines, the chances of having large throughput and spectral efficiency will be sub-
stantially expanded.
• Considering massive connections, lower latency, and user fairness, in OMA, such as in
OFDMA with organizing client by a reasonable channel situation has a considerable
requirement to be carried out, although client with an awful channel scenario needs to
hang tight, which prompts a fairness issue and higher latency. This methodology cannot
bolster a massive network. Notwithstanding, NOMA can serve numerous clients with
different channel situations at the same time; consequently, it can give a better user fair-
ness, low latency, and heavy massive connections.
• In the case of being accordant, NOMA is likewise perfect with the present and eventual
communication frameworks after all it does not feel a necessity for huge adjustments on
the actual composition.

6 NOMA: Opportunities and Challenges

A definite objective of utilizing NOMA is to accomplish greater spectral efficiency along

with sensible user fairness. It is presented as a worldview change because of the plan of
future radio access strategies. NOMA is good with different propelled communication
strategies and schemes to be utilized in the fifth generation and beyond it. Nonetheless, the
open doors accompany different opportunities and challenges [41–46]. Few of them are as
laid out underneath:

6.1 NOMA Based Heterogenous Network

With regards to 5G prerequisites, a heterogeneous network (HetNet) is a compelling answer

to accomplishing high capacity upgrades, brilliant usage of limited assets, and minimal
cost networks. In HetNets, notwithstanding essential BS also known as macro-BS, there
are different kinds of mini BSs, for example, micro and pico-BS in every cell, rather than
a homologous network that has just a single BS in every cell [47–49]. The mini BSs with
lesser transmit powers and littler coverage are introduced inside the inclusion of the macro
cell to increment spectral-efficiency and quantity of offered clients. NOMA-based HetNet
essentially boosts the downlink coverage in collaborative-communication. The NOMA-
dependent two-level HetNet with non-uniform mini cell formation is discovered higher
energy proficient contrasted with OMA-empowered HetNet. In NOMA-based multi-cell
systems, the control of power is a fundamental affair to concentrate on the grounds that
both intra-cell intervention and inter-cell noise should be coordinated.

6.2 NOMA in mmWave Communication

MmWave correspondence speaks to specifically the most encouraging innovations for

the 5th generation and beyond due to its enormous bandwidth assets. Its applications are
feasible in a different context, for example, IoT and cloud-helped vehicular networks. Be
that as it may, the presentation of mmWave frameworks [50–54] is seriously degraded on

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 1784 H. Mathur, T. Deepa

the grounds that its transmission is exceptionally directional, and along these lines, user’s
channels are profoundly correlated. Interestingly, such an excessive interconnection is a
great prerequisite for the utilization of NOMA. The utilization of NOMA in millimeter-
wave has been examined in various locales and situations, and NOMA is demonstrated to
be much more effective than OMA. Regardless of its potentiality, investigation of mmWave
which is NOMA-based communication is yet in the beginning time. Consequently, multidi-
mensional analysis, for example, resource allocation improvement, cooperative millimeter
Wave NOMA, and mmWave NOMA HetNets are needed to additionally support the frame-
work execution.

6.3 Visible Light Communication (VLC) Based NOMA

Despite the mmWave communications, an additional communication worldview with good

spectrum resources that have pulled in huge consideration as of late is VLC. By reason of
light can’t infiltrate by walls, VLC inalienably proposed a more significant height of data
security [55–58]. In addition, VLC is especially helpful in some delicate conditions, for
example, airplane cabins as well as clinics, where the obstruction to actual radio frequency
(RF) frameworks is commonly risky. In spite of the significant contrasts amid VLC as well
as RF channel, the utilization of NOMA to the downlink VLC situation can possibly addi-
tionally expand the exhibition of VLC systems without influencing the light-emitting diode
lighting character. Further research should be done to make NOMA-empowered VLC use-
ful in various environments and situations remembering NOMA for uplink VLC as well
as MIMO NOMA in VLC. An open issue is additional which is of resource allocation in
NOMA-aided VLC.

7 Results and Discussion

1. NOMA at Transmitter: The transmission and reception are done simultaneously by the
two under the NOMA scheme using the same frequency. Figure 5 shows that at the
transmitter side, superposition coding is done. Two users x­ 1 and x­ 2 are assumed to be
communicating simultaneously using the same frequency having 4 bits of data each
sends where ­x1 = 1111 and ­x2 = 1110. BPSK has been considered which maps 0’s to
− 1’s and 1’s to + 1’s. × 1 and × 2 has been multiplied with different power levels and
then added together. They both have unit power as the peak amplitude of + 1 and − 1
has been observed. Power weights a­ 1 and a­ 2 has been considered as 0.5 each considering
the rule of summing up to 1. Considered the fixed power allocation, values of a1 and a2
are fixed. Since a1 and a2 depicts the power scaling factors so, scaling has been done
for scale ­x1 and ­x2 with √a1 and √a2, respectively.
  Amplitude scaled versions of the data are, √a1x 1  and √a 2x 2. Scaled output
has been added to get the superposition coded signal output which is denoted by
x = √a1x1 + √a2x2.
2. NOMA at receiver: Successive Interference Cancellation (SIC) is an operation per-
formed on the receiver end that makes NOMA possible where data is decoded in the
order of decreasing power levels. BPSK demodulation has been directly applied to x and
the threshold has been set to zero. If the amplitude exceeds zero, we are going to decode
it as 1, and 0 otherwise. Three main steps of performing SIC are to get the signal which
has been weighed with high power, multiplying the signal which has been decoded by

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Fig. 5  NOMA at the transmitter side

its corresponding weight and subtract it from x, and finally to decode the signal which
has been obtained so as to get the other signal which was multiplexed with low power
as shown in Fig. 6.
3. NOMA-BER in AWGN channel: Two user NOMA system using MATLAB is simulated
and the performance of BER versus SNR is plotted in the AWGN channel. To estimate
the BER, the comparison is made in decoded and transmitted bits by using the inbuilt
biterr() function. A waterfall trend is observed in which user 2 has lower BER than user
1 in the low SNR region. The data must be decoded correctly by user 2 for both user 1
and its own since user 2 must do SIC. If any error occurs during the decoding, it will
have an impact on BER directly. This is the reason why user 2 has a high value of BER
than user 1 as shown in Fig. 7.
4. NOMA: Outage probability and capacity for Rayleigh fading channel Non-line of sight
(NLOS) path use Rayleigh fading model in between the transmitter and the receiver. Due
to multipath transmission, each bit that has been transmitted goes under a different phase
shift and attenuation. The capacity and outage power of NOMA has been plotted here
concerning transmitting power. It has been observed that the SNR and achievable rates
have been calculated with their average and outage has been checked upon considering
the distance of the users from the base stations as 500 and 1000 m and power allocation
factors as 0.7 and 0.3 where ­R1, ­R12, and ­R2 are average achievable rates as observed in
Fig. 8.

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 1786 H. Mathur, T. Deepa

Fig. 6  Successive Interference Cancellation steps for NOMA

Fig. 7  NOMA-BER for AWGN channel

5. NOMA-BER for Rayleigh channel: Once the outage and capacity have been plotted,
noise samples have been generated for both the users followed by the random binary
data. BPSK has been used for modulating the data and superposition coded signal x has

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Fig. 8  NOMA-outage probability and capacity for Rayleigh channel

been calculated followed by the received signal y1 and y2. BPSK demodulation has been
performed once the output signal is equalized. As shown in Fig. 9 BER as a function of
transmit power has been plotted while not considering the dBm value and only using
the linear value of power in all the analysis, also theoritical BER has been referred to.
6. NOMA versus OMA for Rayleigh channel: Rayleigh fading channel with two users SISO
has been assumed, considering 1000 samples under Monte Carlos approach for strong
as well as weak users. The capacity of NOMA vs OMA has been observed for the dif-
ferent values of power coefficients. Figure 10 demonstrates that the output performance
of NOMA is improved than OMA.

Fig. 9  NOMA-BER for Rayleigh channel

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Fig. 10  Capacity of NOMA vs OMA for Rayleigh channel

8 Conclusion

In this survey, the latest literature for NOMA in 5G systems and beyond has been esti-
mated with significance on the 5G advancement and upcoming innovations. The motiva-
tion behind the usage of NOMA as a prominent candidate for 5G and beyond has been
discussed in detail considering the principle of NOMA, the  concept of NOMA followed
by the categories of power, and the code domain NOMA. Also, the comparison has been
done for NOMA to the conventional OMA technique while discussing the superiority of
NOMA over OMA. At last, the study centers around numerous open possibilities and dif-
ficulties that need to be routed to brand NOMA adaptable with additional up-and-coming
communication standards, for example, mmWave communications, visible light communi-
cation, etc. All NOMA plans examined a similar soul of non-orthogonal transportations to
improve the achievable bandwidth efficiency and to give availability to various users inside
the predetermined values of RBs. Based on the above discussion and by employing non-
orthogonality, 5G networks will offer enhanced throughput, improved spectral efficiency,
and massive connectivity.

9 Future Work

This paper has examined several NOMA schemes. A common thread across different tech-
niques has been their use of non-orthogonality to boost the capacity of the system and
enable restricted RB to be used by more users. To develop the performance of NOMA sys-
tems, further research is required. The joined design of various modulations and NOMA
schemes is a crucial way that needs to be researched in 5G networks. Also, the layout of

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A Survey on Advanced Multiple Access Techniques for 5G and Beyond… 1789

modulation and multiple access schemes for frequencies beyond 40 GHz is commencing to
acquire improved interest. In mmWave and TeraHz band, high-level impairments such as
phase noise, etc. should also be taken care of.

Funding  We declare that there is no funding for this work.

Compliance with Ethical Standards 

Conflict of interest  The authors declare that they have no conflict of interest.

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Publisher’s Note  Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional affiliations.

Harshita Mathur  received the B.Tech. degree in Electronics and Com-

munication Engineering from Sir Padampat Singhania University,
Udaipur, India, 2015, the M.Tech. degree in Telecommunication and
Networks from SRM Institute of Science and Technology, Chennai,
India, 2018, and is currently pursuing Ph.D. in Electronics and Com-
munication Engineering from SRM Institute of Science and Technol-
ogy, Chennai, India. She has worked as an assistant professor in elec-
tronics and communication engineering department, SRMS CET&R,
Uttar Pradesh, India, 2019. Her research interests include 5G and
beyond wireless systems, digital signal processing and optical wireless
communication. She has published papers in various national and
international journals and conferences and is an associate member of
the IEI in ET division.

T. Deepa  received her B.Tech. degree in Electronics and Communicai-

ton Engineering (ECE) from Madras University, Chennai, India and
her M.Tech. degree in Communication Engineering from VIT, Vellore,
Chennai, India in 2004 and 2006, respectively. She completed her
Ph.D. in 2015. She is currently working as an Associate Professor in
the Department of ECE, SRM Institute of Science and Technology,
Kattankulathur, Chennai, India. She has more than 15 publications in
SCI/SCOPUS indexed journals and 20 proceedings in International
and national conferences. She is currently supervising 6 Ph.D. stu-
dents. She is an active participant in both academic and research activ-
ities. Her research interests are in the areas of wireless communication
systems,signal processing, visible light communication, IoT, multicar-
rier and multiple access techniques for 5G communications.

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