Survey on NOMA and Spectrum Sharing Techniques in 5G

Full text

2021 IEEE Smart Information Systems and Technologies (SIST)
28-30 April 2021, Nur-Sultan, Kazakhstan
Survey on NOMA and Spectrum Sharing
Techniques in 5G
Mohamed Hassan1*, Manwinder Singh2, Khalid Hamid3
1*Lovely Professional University, India, mhbe4321@gmail.com
2Lovely Professional University, India, manwinder.25231@lpu.co.in
3University of Science & Technology, Sudan, khalidhamidk9@gmail.com
Abstract — Two innovations multiple access
technologies for efficient spectrum use in future wireless
communications standards, non-orthogonal multiple access
(NOMA) and cognitive radio (CR). The NOMA is one of the
most promising performance improvement methods in 5G
cells and CR will make the most of dynamic spectrum access
and diversity throughout the broad spectrum possible, to
alleviate the spectrum scarcity problem and meet the huge
demands for wireless connectivity. The paper aims to look
and survey at methods and techniques that maximize
spectrum efficiency and performance. In order to evaluate
the important functions of spectrum optimization
techniques, a descriptive approach was used. We found that
these are effective methods to solve the problems of a
specific frequency spectrum and additional spectral
efficiency benefits would be provided. combining NOMA
and CR can meet 5G standards. This article discusses the
basic principle of NOMA, the basic concept of cognitive
radio, the spectrum sharing way, and the advantages and
challenges of NOMA and CR spectrum sharing.
Keywords — Non-Orthogonal Multiple Access (NOMA),
Orthogonal Multiple Access (OMA), Cognitive Radio (CR).
I. INTRODUCTION
Wireless networking has been witnessed to a
revolution in the past few decades through various
approaches. The key wireless networking networks
multiple users are assigned to orthogonal radio services
within the time, frequency, and code domain, or their
combination by traditional Orthogonal multiple access
(OMA) schemes, such as frequency division multiple
access (FDMA), time division multiple access (TDMA),
and code division multiple access (CDMA) have been
used. Orthogonal frequency division multiple access
(OFDMA) for 1G, 2G, 3G, and 4G respectively.
Each user sends one signal via its frequency resource
FDMA so that all user data in their respective frequency
bands can be detected readily by the receiver. Multiple
users can share the same frequency resources in CDMA
and orthogonal sequences can be mapped to symbols
transmitted by various users. The OFDMA can be
referred to as an intelligent FDMA and TDMA
integration, where the radio sources are split in the time
flow grid orthogonally.
However, the maximum number of supportive users
is strictly limited to the number of orthogonal resources
available in traditional OMA, which becomes a tough
limit when a massive 5G connection is needed. Besides, it
has been theoretically proven that OMA cannot always
achieve the maximum attainable rate for multi-user
wireless systems.
5G is mainly concerned with high data rates, low
latency, low power usage, increased system capability,
and most notably mass networking of devices. These
needs can be satisfied by the inclusion of non-orthogonal
multiple access (NOMA) technique in the 5G system, as
NOMA can achieve multi-user capacity through time-
sharing or rate-splitting if necessary. The main
distinguishing feature of NOMA is to serve a larger
number of users than the number of orthogonal resources.
The NOMA family can be divided into two
categories, (1) NOMA power domain and (2) NOMA
code domain. The first one serves multiple users which
employ different transmission powers in the same time-
frequency resource, while the second design a sparse
codebook for each user whose data is then mapped
accordingly based on the codebook [1].
There is a problem in the available radio spectrum
due to the growth, the excellent progress and the
technical advancement of communication systems [2].
Unfortunately, the wireless band has a restricted resource
and the available wireless supply does not cover the
required wireless band. Hence, it will be necessary for
wireless networks in the next decade to build new
technologies to meet the increasing demand for traffic
and services to address the inevitable spectrum
breakdown [3].
Spectrum sharing where multiple consumers,
whether in time or space, participate in spectrum bands is
a very feasible and feasible solution to the efficient use
and expected increase in transport demand on the
spectrum (i.e. scarcity of counter bandwidth). Thus, the
spectrum share can be divided into two types: (1)
unlicensed band sharing and (2) permissible band share.
II. BASIC CONCEPT OF NOMA
The main concept in NOMA is that multiple users,
e.g. frequency channel, time or code dissemination, are
served in one single resource block are shown in figure 1.
This paper is focus on Power Domain NOMA, which
simultaneously serves multiple users, channel frequency
or code delivery, and multiple accesses are enforced by
2021 IEEE International Conference on Smart Information Systems and Technologies (SIST) | 978-1-7281-7470-9/20/$31.00 ©2021 IEEE | DOI: 10.1109/SIST50301.2021.9465962
Authorized licensed use limited to: Raytheon Technologies. Downloaded on February 02,2023 at 16:55:13 UTC from IEEE Xplore. Restrictions apply.

multiplexing the power domain. In Power Domain
NOMA, multiple users in the same cell are allocated the
single frequency channel, so Power Domain NOMA
offers better communication in comparison to OMA [4].
Figure 1 - The transmit power levels in the NOMA scheme
a. NOMA for downlink
The base station overlaps information wave for its
serviced users on the NOMA downlink. To detect their
signals, every user (U) uses successive interference
cancellation (SIC). The BS and N numbers with SIC
recipients are shown in figure 2. The U1 will be the
nearest to the base station (BS), and Un will be the
farthest in the network.
Figure 2 - Downlink NOMA for n users
The NOMA framework provides U users with the full
WT bandwidth and NSC number of subcarriers.
Moreover, the NOMA system uses the SIC to ensure
the cancellation of interference between the N users of
the same subcarrier. On the nth sub-carrier (n {1, 2
..., NSC}) the BS transmits the Xu,n signal to the
consumer uth (u {1, 2 ... U}) with a transmitting
power Pu,n. The received signal Yu got from the uth
user on nq the subcarrier.
where Gi, n is the channel gain between the BS and the ith
users multiplexed on the nth subcarriers, while is Ni the
white additive Gaussian noise.
b. NOMA for uplink
The implementation of the NOMA uplink is very
different from the downlink. Figure 3 indicates the
network that uses NOMA in the uplink. In the
transmission NOMA uplink, a control message should
normally be sent to the BS at the initial stage containing
the power allocation information. This time, BS uses SIC
to differentiate user signals.
The Optimal detection order will first be to decode
from the stronger signal and switch to the weaker.
Figure 3 - Uplink NOMA for n users.
In the uplink, the received signal by the BS that
includes all the user signals is written as:
where gk is the channel attenuation factor for the link
between the BS and the Un and wk(t) is the additive
white Gaussian noise at the Un with mean zero and
density N0 (W/Hz).
III. BASICS OF COGNITIVE RADIO
The first description of cognitive radio is given by J.
Mitola. Cognitive radio describes the stage in which
wireless digital assistants and their associated networks
are adequately coordinated on radio and related computer
resources to provide: (a) discovery of user
communication needs as a function of the context of their
use, and (b) provision of radio resources and wireless
services [6].
The cognitive radio senses and adjusts its operating
parameters to allow efficient use of bandwidth. The main
goal of this technology is to optimize spectrum utilization
because usable frequency channels are ideally safe for
90% of the time. At a specific time and place unused
spectrum, the CR recognizes and transmits or describes a
set of frequencies. Use this blank tape for secondary use
efficiently without interfering with the licensed consumer
in the first place. Thus, the CR system must distinguish
the primary user from the secondary user. Authorized
users are given higher priority and primary users are
named. Provides ample bandwidth to improve content
and data rate services. Spectrum sensing, spectrum
analysis, spectrum decision-making, and movement of
the spectrum are the major steps towards working a CR.
A. System for Spectrum Detection
During intra and interframe data transmission silent
times, spectrum sensing is performed. Frequency hopping
or multiplex search and communications protocol for the
discovery of the previously used channels with the
transmission of the next channel [7] is achieved.
The following methods are widely used for spectrum
sensing.
1) Energy Sensing: the most basic technique
because of its technical simplicity and quick strategy of
Authorized licensed use limited to: Raytheon Technologies. Downloaded on February 02,2023 at 16:55:13 UTC from IEEE Xplore. Restrictions apply.

implementation. By comparing the measured energy to
an appropriate threshold, a spectral hole is determined
using this process.
2) Coherent sensing: in this technique, the detector
knows accurately primary user signals such as the type
of modulation, order, pulse size, data frequency, and
bandwidth. A creative copy of the message is connected
to the signal received; the effect is compared with a limit
value.
3) Cyclo-stationary Sensing: if the function of (x) is
not fully understood but other features are known, these
details may be used to create test statistics that fit a
signal closely. It includes a cyclical function of self-
relation for a received data signal, which is regular but
stationary to noise or broad phrase.
4) The autocorrelation feeling: the main data signal
is static and is used to differentiate between white noises
and the principal data signals with its autocorrelation.
c. Sharing of spectrum
This is a critical mechanism for avoiding conflict
between cognitive radio and primary licensing, allowing a
greater functionality of wireless radiofrequency. Two
ways of doing this.
1) Spectrum Sharing Cooperative
This frequency range involves a data collection
center and a control channel between them or over
distributed networks. The first method is more
accurate, but the time is much longer, the
implementation is very complex, and energy usage
is greater than the second method [8].
2) Spectrum sharing non-cooperative
This does not allow a kind of user-to-user
information exchange, but it is a very useful method
of communication for a small number of cognitive
user networks [9].
d. Access types of spectrum
The CR activity can be graded as follows according
to the spectrum use scenario:
1) Interweave: The SU can only transmit when the
licensed spectrum is not occupied by a PU.
2) Underlay: Primary and secondary simultaneous
transmissions are permitted, provided the primary
network interference is below the controllable
level.
3) Overlay: A SU offers primary network
transmission facilities and transmits its signal at
the same time.
IV. RELATED WORK
Two new technologies toward 5G wireless networks,
namely NOMA and CR, would provide more effective
use of wireless spectrum in the future. However, it does
not generally achieve the highest possible data-rate for
spectrum efficiency [10].
CR based spectrum sharing technique for 5G would
improve the efficiency of the current detectors for
spectrum sensing. However, the integrated system must
be created for all users (unlicensed and licensed) [11]. In
[12], the authors concentrate on Wireless Full-Duplex
regarded as one of the applicant technologies for the fifth
generation of wireless communication systems. FD can
provide various advantages and options including
simultaneous sensing and transmission. Although,
mitigation of heavy self-interference is one of the key
challenges in FD technology.
While the authors in [13] focus on the optimal power
allocation for maximizing the achievable sum-rate of
sharing depends on the target data rate requirement. For
higher values of peak interference power, the spectrum
sharing system based on CRS-NOMA outperforms the
spectrum share system for SC and MRC schemes.
Nevertheless, the interference canal between the
secondary user and the primary user is more serious on the
secondary network.
The author concentrates primarily on Improving the
cognitive radio networks (CRNs) performance by using
the timing mismatch between the primary and the
secondary users and enhanced SINR at the PU and SU
receivers. Although asynchronous transmission can be
used to improve the performance of cognitive radio
networks, it is not beneficial when used for high traffic
and big data [14].
NOMA with CR spectrum sharing
The principal concept of non-orthogonal multiple
access NOMA is the use of energy multiplexing which is
fundamentally different from traditional orthogonal
access technologies (OMAs), to promote the allocation of
the spectrum between multiple users within a single
resource network [15].
The combination of NOMA and CR it can meet 5G
standards for high performance, great connectivity, and
low latency. Also, given these potential advantages, the
successful cognitive construction of NOMA is a very
difficult problem in practice, as both NOMA and CR are
susceptible to interference, resulting in NOMA
multiplexing in the control domain, which inevitably leads
to significant interference between networks Primary,
secondary, and intra-network interference (also called co-
channel interference) [16].
Therefore, to reduce interference and allow efficient
use of the core tools of the system, NOMA and CR must
be properly integrated. By combining CR and NOMA
spectrum sharing, cognitive NOMA aims to better share
the spectrum in a proactive way to increase spectrum
utilization. The advantages of an insightful cognitive
sharing of the NOMA spectrum:
• Enhanced spectrum use: NOMA cognitive
networks will enable both PUs and SUs at an
appropriate level of reception.
• Massive Connectivity: Many smart devices are
planned for 5G wireless networks. NOMA
Authorized licensed use limited to: Raytheon Technologies. Downloaded on February 02,2023 at 16:55:13 UTC from IEEE Xplore. Restrictions apply.

cognitive networks, where multiple PU and/or
modules are supplied in a single source block at
different power levels simultaneously, will satisfy
this requirement [17].
• Low latency: In cognitive NOMA networks,
transmission delays in SUs can be high, resulting in
low latency. For example, several SU units can be
connected simultaneously by making use of
NOMA to support CR networks [18].
• Better Justice: NOMA Perceptual Networks will
ensure better equality among consumers. This
results in a healthy compromise between equity and
secondary network efficiency [19].
V. CONCLUSION
Through the study and reviewing the basic principles
of non-orthogonal multiple access (NOMA) and the
concept of cognitive radio (CR), we found that they are
effective methods for solving problems of scarcity of a
particular frequency spectrum and additional spectrum
efficiency benefits will be provided. Combining NOMA
and CR can meet 5G standards for high performance,
great connectivity and low latency, but there are many
challenges and complexities facing NOMA integration
with CR that need further study, implementation and
analysis.
Studies recommend that the wireless the spectrum can
be used more effectively by combining non-orthogonal
multiple access (NOMA) and perceptual radio (CR)
techniques with the determination of the sharing method.
REFERENCES
[1] S. Sharma, C. C. Tripathi and R. Rishi, "Cognitive Radio: An efficient
and effective solution for future spectrum implications," 2017
International Conference on Computer, Communications and
Electronics (Comptelix), pp. 112-117, Jaipur, 2017.
[2] T. Yucek, H. Arslan, "A Survey of Spectrum Sensing Algorithms for
Cognitive Radio Applications", IEEE Communications Surveys &
Tutorials, Vol. 11, No. 1, pp. 116-129, 2009.
[3] G. Zheng, S. Song, K. Wong and B. Ottersten, "Cooperative Cognitive
Networks: Optimal, Distributed and Low-Complexity Algorithms,"
in IEEE Transactions on Signal Processing, vol. 61, no. 11, pp.
2778-2790, June1, 2013.
[4] Islam, S. R., Avazov, N., Dobre, O. A., & Kwak, K. S, "Power-domain
non-orthogonal multiple access (NOMA) in 5G systems: Potentials
and challenges." IEEE Communications Surveys & Tutorials, 721-
742, 2016.
[5] Al-Abbasi, Z. Q., & So, D. K., "Power allocation for sum
rate maximization in non-orthogonal multiple access system." IEEE
26th Annual International Symposium on Personal, Indoor, and
Mobile Radio Communications (PIMRC),pp. 1649-1653, August
2015.
[6] J. Mitola and G.Q. Maguire, "Cognitive Radio: Making
Software Radios More Personal", IEEE Personal Commun., vol. 6,
no. 4, pp. 13-18, Aug. 1999.
[7] L. J. Greenstein, "Principles of Cognitive Radio", Cambridge
University Press, Jan. 2012.
[8] A. Khan, M. Rehmani and M. Reisslein, “Cognitive Radio
for Smart Grids: Survey of Architectures, Spectrum Sensing
Mechanisms, and Networking Protocols,” vol. no.18, IEEE
Communications Surveys & Tutorials, 2015.
[9] S. Tzeng, Y. Lin and L. Wei, "Spectrum Hand-Off for RF
Energy Harvesting in Cognitive Radio Based Machine to Machine
Communication Networks," 2018 International Conference on
System Science and Engineering (ICSSE), New Taipei, pp. 1-4,
2018.
[10] Z. Shi, W. Gao, S. Zhang, J. Liu and N. Kato, "AI-Enhanced
Cooperative Spectrum Sensing for Non-Orthogonal Multiple
Access," in IEEE Wireless Communications, vol. 27, no. 2, pp.
173-179, April 2020.
[11] S. Sodagari and H. Jafarkhani, "Enhanced Spectrum Sharing
and Cognitive Radio Using Asynchronous Primary and Secondary
Users," in IEEE Communications Letters, vol. 22, no. 4, pp. 832-
835, April 2018.
[12] S. K. Sharma, T. E. Bogale, L. B. Le, S. Chatzinotas, X.
Wang and B. Ottersten, "Dynamic Spectrum Sharing in 5G
Wireless Networks With Full-Duplex Technology: Recent
Advances and Research Challenges," in IEEE Communications
Surveys & Tutorials, vol. 20, no. 1, pp. 674-707, First quarter 2018.
[13] P. K. Sangdeh, H. Pirayesh, A. Quadri and H. Zeng, " A
Practical Spectrum Sharing Scheme for Cognitive Radio Networks:
Design and Experiments," in IEEE/ACM Transactions on
Networking, vol. 28, no. 4, pp. 1818-1831, Aug. 2020.
[14] V. Kumar, B. Cardiff and M. F. Flanagan, "Fundamental
Limits of Spectrum Sharing for NOMA-Based Cooperative
Relaying Under a Peak Interference Constraint," in IEEE
Transactions on Communications, vol. 67, no. 12, pp. 8233-8246,
Dec. 2019.
[15] L. Liu, Y. Zhou, L. Tian and J. Shi, "CPC-based backward-
compatible network access for LTE cognitive radio cellular
networks," in IEEE Communications Magazine, vol. 53, no. 7, pp.
93-99, July 2015.
[16] M. Naeem, A. Anpalagan, M. Jaseemuddin and D. C. Lee,
"Resource Allocation Techniques in Cooperative Cognitive Radio
Networks," in IEEE Communications Surveys & Tutorials, vol. 16,
no. 2, pp. 729-744, Second Quarter 2014.
[17] B. Zhong, Z. Zhang, X. Chai, Z. Pan, K. Long and H. Cao,
"Performance Analysis for Opportunistic Full-Duplex Relay
Selection in Underlay Cognitive Networks," in IEEE Transactions
on Vehicular Technology, vol. 64, no. 10, pp. 4905-4910, Oct.
2015.
[18] Q. Y. Liau and C. Y. Leow, "Amplify-and-forward relay
selection in cooperative non-orthogonal multiple access," 2017
IEEE 13th Malaysia International Conference on Communications
(MICC), pp. 79-83, Johor Bahru, 2017.
[19] X. Zhang et al., "Performance Analysis of NOMA-Based
Cooperative Spectrum Sharing in Hybrid Satellite-Terrestrial
Networks," in IEEE Access, vol. 7, pp. 172321-172329, 2019.
Authorized licensed use limited to: Raytheon Technologies. Downloaded on February 02,2023 at 16:55:13 UTC from IEEE Xplore. Restrictions apply.