write a research paper after reading the article bellow Question 1: In this question, you will investigate important 5G-enabling technologies and the rol

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write a research paper after reading the article bellow Question 1:

In this question, you will investigate important 5G-enabling technologies and the role of spectrum sharing in this regard. More specifically, refer to the following reference (a PDF copy is attached as well for convenience):

W. Ahmad et al. “5G Technology: Towards Dynamic Spectrum Sharing Using Cognitive Radio Networks,” IEEE Access, 2020, to write a report of 1200-1400 words explaining and discussing the following issues:

• A brief overview of the most important 5G-enabling technologies

• Different spectrum sharing (SS) concept techniques

• SS techniques relevant to 5G networks. Discuss in brief network architecture,

spectrum allocation behaviour and spectrum access method

• Cognitive radio technology in applications related to 5G implementation

• The issues and challenges in the implementation of SS

You should adhere to the following guidelines in writing the report:

o The report MUST be written in YOUR OWN WORDS. You should grasp the idea

and show your understanding. Any act of plagiarism WILL NOT BE tolerated.

o The report should be between 1200-1400 words in length. The report should include at least one figure and/or table. Inclusion a caption for each

figure/table is necessary. o Use cross-referencing and citation (You can benefit from other extra academic

resources if needed). o All the references must be cited in proper format. o The report should have appropriate structure and style (introduction, body, and

conclusion.) Received December 4, 2019, accepted January 7, 2020, date of publication January 13, 2020, date of current version January 24, 2020.

Digital Object Identifier 10.1109/ACCESS.2020.2966271

5G Technology: Towards Dynamic Spectrum
Sharing Using Cognitive Radio Networks
W. S. H. M. W. AHMAD 1, N. A. M. RADZI 1,2, (Senior Member, IEEE), F. S. SAMIDI1,
A. ISMAIL 1,2, (Member, IEEE), F. ABDULLAH 1,2, (Senior Member, IEEE),
M. Z. JAMALUDIN1,2, (Senior Member, IEEE), AND M. N. ZAKARIA3
1Institute of Power Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia
2Electrical and Electronics Engineering Department, College of Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia
3Architecture and Governance, Tenaga Nasional Berhad Information and Communication Technology (TNB ICT), Kuala Lumpur 59200, Malaysia

Corresponding author: N. A. M. Radzi (asyikin@uniten.edu.my)

This work was supported in part by UNITEN R & D Sdn Bhd through Tenaga Nasional Berhad Seed Fund under Grant U-TC-RD-19-04,
and in part by the Universiti Tenaga Nasional BOLD2025 under Grant 10436494/B/2019019.

ABSTRACT The explosive popularity of small-cell and Internet of Everything devices has tremendously
increased traffic loads. This increase has revolutionised the current network into 5G technology, which
demands increased capacity, high data rate and ultra-low latency. Two of the research focus areas for meeting
these demands are exploring the spectrum resource and maximising the utilisation of its bands. However,
the scarcity of the spectrum resource creates a serious challenge in achieving an efficient management
scheme. This work aims to conduct an in-depth survey on recent spectrum sharing (SS) technologies
towards 5G development and recent 5G-enabling technologies. SS techniques are classified, and SS surveys
and related studies on SS techniques relevant to 5G networks are reviewed. The surveys and studies are
categorised into one of the main SS techniques on the basis of network architecture, spectrum allocation
behaviour and spectrum access method. Moreover, a detailed survey on cognitive radio (CR) technology
in SS related to 5G implementation is performed. For a complete survey, discussions are conducted on the
issues and challenges in the current implementation of SS and CR, and the means to support efficient 5G
advancement are provided.

INDEX TERMS 5G, new radio, spectrum sharing, spectrum efficiency, cognitive radio, enabling
technologies.

I. INTRODUCTION
5G is the next-generation mobile communication technol-
ogy designed to provide greater capacity and higher data
speeds than the previous generation Long Term Evolution
(LTE). 5G technology, which is expected to be realised
by 2020 [1], [2], promises ultra-low latency and ultra-
high reliability, thus enabling innovative services across
different industry sectors [3]. 5G standards are currently
under development and will include the evolution of exist-
ing LTE and 5G New Radio (NR) technologies. Several
5G application services have been identified according
to International Telecommunication Union (ITU) stan-
dards. These services include enhanced Mobile Broadband
(eMBB), massive Machine Type Communication (mMTC),
Ultra-Reliable Low-Latency Communication (URLLC) and

The associate editor coordinating the review of this manuscript and

approving it for publication was Ke Guan .

fixed fibre-like wireless access. Each user is expected
to experience a minimum of 100 Mbps data rate with
a peak data rate of 20 Gbps [2], [3]. For data rates
higher than 100 Mbps, Fixed Wireless Access (FWA) or
fibre-like wireless can be used. This broadband wireless
access is beneficial for residential customers and enterprises
using pre-5G or 5G access technologies, including full-
dimensional Multiple-Input Multiple-Output (FD-MIMO),
massive MIMO and millimeter wave (mmWave) radio access
technologies [3], [4]. In ITU’s radiocommunication Inter-
national Mobile Telecommunications (IMT) 2020 vision,
at least 800 MHz of contiguous spectrum per 5G network is
required for very-high-capacity 5G networks, such as hotspot
and FWA connectivity.

In recent years, applications, such as virtual reality, aug-
mented reality and cloud-based services, have emerged and
become an integral part of the new generation’s lifestyle.
By 2030, the vision of connecting 50 billion devices is

14460 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020

https://orcid.org/0000-0001-6364-6341

https://orcid.org/0000-0003-0481-7686

https://orcid.org/0000-0003-4169-3061

https://orcid.org/0000-0002-1030-7554

https://orcid.org/0000-0001-7229-7446

W. S. H. M. W. Ahmad et al.: 5G Technology: Towards Dynamic Spectrum Sharing

FIGURE 1. 5G application services.

expected to be realised as part of the Internet of Things
(IoT) evolution. Sensors, actuators, electronic appliances,
street lighting and other devices will be wirelessly connected
to the Internet and one another via device-to-device (D2D)
communication, which is also known as massive Machine
Type Communication (mMTC). Other advancements will
demand URLLC; these advancements include connected and
autonomous cars, aerial vehicles, remote control of robots in
extreme hazardous conditions, industry automation as part
of Industry Revolution 4.0, remote surgery and smart grid
applications. With the realisation of 5G technology, ultra-fast,
ultra-reliable and ultra-low latency application services can
be achieved, as compactly illustrated in Figure 1.
5G will benefit numerous industry sectors and acceler-

ate many applications, such as IoT and Mobile Edge Com-
puting (MEC). According to a study by Rimal et al. [5],
highly localised services are required in Radio Access Net-
works (RANs) that is in close proximity to mobile sub-
scribers. This requirement has led to the emergence of
the MEC concept, in which cloud services are delivered
directly from the network edge. Authors have also discussed
potential service scenarios for MEC, such as edge video
orchestration and distributed caching, backhaul optimisation,
vehicle-to-vehicle/roadside communication and IoT services.
Other have identified the design challenges of MEC-enabled
networks, namely, network integration and coordination,
distributed resource management, coexistence of human-to-
human and MEC traffic, cloud and cloudlet interoperabil-
ity, reliability and mobility. Furthermore, the possibility of
integrating Fiber Wireless (FiWi) access networks to offer
MEC capabilities has been explained with different design
scenarios from the architectural perspective. The scenarios
are as follows: (1) MEC over FiWi networks, (2) MEC over
Ethernet-based FiWi networks, (3) MEC over 4G LTE-based

FiWi networks and (4) coexistence of MEC and centralised-
RAN (C-RAN) in FiWi LTE-A Heterogeneous Networks
(HetNets). In the same study, the authors provided a per-
formance analysis of MEC over Ethernet-based FiWi in
terms of delay, response time, efficiency and battery life to
demonstrate the feasibility of MEC over FiWi. The results
showed the significant benefits of MEC over FiWi networks,
with efficient human-to-human/MEC coexistence without
network performance degradation.

Numerous researchers have exerted a substantial amount
of work to enable applications, such as MEC. An overview
of the current status of 5G industry standards, architecture,
spectrum allocation, use cases, relevant scenarios and state
of the art system advances was presented in [3], [6]–[11].
[12] and [13] studied the opportunities and challenges faced
by existing solutions in implementing mmWave for 5G,
including the characteristics of and standards in enabling
mmWave and related applications (small cell (SC) access,
cellular access and wireless backhaul). The authors pre-
sented a thorough discussion of the directions of mmWave
in the future mainly in terms of physical layer technol-
ogy (MIMO at mmWave and full-duplex (FD)), software-
defined architecture, control mechanisms, network state
measurement and HetNet. A comprehensive analysis of var-
ious types of 5G potential waveforms was recently per-
formed by Samal et al. [14]. They discussed issues related
to single-carrier modulation schemes suitable for mmWave
in 5G wireless communication systems and enumerated the
limitations of Orthogonal Frequency-Division Multiplexing
(OFDM), Orthogonal Frequency-Division Multiple Access
(OFDMA) and single-carrier frequency-division multiple
access (SC-FDMA) spectrum access schemes.

A survey of the current state-of-the-art research in
5G-IoT was presented by Lie et al. [15], with focus
on the key enabling technologies, the main research
trends and the challenges. Despite extensive research effort
on 5G-IoT, the technical challenges identified by the
authors involved the 5G-IoT architecture, namely, scalabil-
ity and network management (NM), interoperability and het-
erogeneity, security assurance and privacy concerns. The
challenges in wireless Software Defined Network (SDN)
for 5G data networking, Network Function Virtualisa-
tion (NFV), D2D communication with efficient spectral
resource and interference management, large-scale (with
limited resource) and heterogeneous environment of IoT
application deployment and multiple access FD transmission
remain to be addressed for the successful commencement
of 5G-IoT.

Considering recent research, this study is expected to
provide an overview of the most recent advancements in
5G-enabling technologies. Our latest study has shown that
one of the most urgent issues in future implementation is
the scarcity of the radio spectrum [16]. Currently, wireless
connectivity is prevalent worldwide and makes full use of
the available spectrum band. Unlicensed bands are often
congested due to overuse [17], and licensed bands are always

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W. S. H. M. W. Ahmad et al.: 5G Technology: Towards Dynamic Spectrum Sharing

underutilised. The Federal Communication Commission
indicated that only 5.2% of bands below 3 GHz are utilised
at a given time or location. This situation presents an oppor-
tunity to solve spectrum scarcity by using the spectrum
sharing (SS) concept within a band to maximise spectrum
utilisation. An in-depth survey of previous reviews on SS
by other authors is conducted, followed by a discussion of
the most recent methods in SS. CR is one of the methods
with promising implementation. The analysis performed in
this study highlights the issues and challenges in current CR
implementation to provide insights into potential research
directions.

The main contributions of this study are summarised as
follows:

• A complete list of the most important 5G-enabling tech-
nologies and a brief overview of each technology are
provided.

• Different SS techniques are classified.
• Related SS surveys conducted from 2014 to 2019 are
reviewed. The focus and contributions of each study are
summarised and presented in a table.

• Related studies on SS techniques relevant to 5G net-
works are reviewed. The studies are categorised into
network architecture, spectrum allocation behaviour and
spectrum access method, which is also one of the main
SS techniques. Related SS works focusing on energy-
efficient (EE) improvements are also discussed. The
related works are summarised, compiled and presented
in a table.

• CR technology in SS and other applications related to 5G
implementation are reviewed. CR in SS can be consid-
ered a potential technology that can propel 5G networks
into the future.

• The issues and challenges in the current implementation
of SS and the improvement of current methods to sup-
port 5G advancement and efficiency are discussed.

The rest of this paper is organised as follows. Section 2 dis-
cusses current 5G-enabling technologies in literature.
Section 3 focuses on SS methods, including surveys and
recent works, and summarises them in a tabular form.
Section 4 discusses the evolution of CR technology related
to SS and 5G applications. Section 5 discusses the issues,
challenges and future research directions of SS and CR.
Section 6 concludes the work. Table 1 lists the acronyms and
notations used in the paper.

II. 5G ENABLING TECHNOLOGIES
The deployment of 5G systems has sparked countless aca-
demic studies and greatly benefited society. A few impor-
tant enablers empower 5G technology in communication
networks, as illustrated in Figure 2. Each enabler has its
own features, and the combinations of enablers define 5G
technology.

TABLE 1. Definitions of acronyms and notations.

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W. S. H. M. W. Ahmad et al.: 5G Technology: Towards Dynamic Spectrum Sharing

FIGURE 2. Important 5G enablers.

A. HETEROGENEOUS NETWORK
Currently, the emergence of various devices using wireless
and IoT technologies is increasing remarkably. Networks
that combine different cell types and access technologies are
called HetNets. An example of the HetNet architecture is
shown in Figure 3. Various types of devices are connected
to a femtocell base station (BS) covering multiple small
subsets of macro BS. Given that the network is flexible,
further research on implementing this network is important
to avoid interference and fulfil the Quality of Service (QoS)
promise to end users [18]. Therefore, researchers are eval-
uating the performance of FiWi-enhanced LTE Advanced
(LTE-A) HetNets. For example, Beyranvand et al. [19] inves-
tigated the temporal and spatial probability, delay, maximum
aggregate throughput and offloading efficiency of FiWi con-
nectivity. They proposed an algorithm to improve the max-
imum aggregate throughput performance of FiWi and used
the algorithm to enhance LTE-A HetNets as an initial step
towards achieving 5G.

A study [21] conducted a comprehensive review of the
challenges, technologies and potential use cases of HetNets,
with focus on implementing mmWave and massive MIMO
in 5G networks. Several challenges that are crucial for effec-
tive deployment, such as issues in network planning, traffic
management and radio resource management, were reported.
The solutions to these issues were presented in several papers.
For instance, in [22], the authors improved the call ses-
sion control function server by adding traffic prediction,
bandwidth negotiation and connection admission control to
improve traffic management and increase the accuracy of
traffic forecasting without sacrificing the prediction accuracy
of the system. For ideal large-data streaming in 5G HetNets,
an improved version of traditional traffic prediction was pro-
posed by [23]. Another study proposed the development of

a linear predictor that uses compressed sensing by adopting
support vector classification. The proposed predictor has a
simple structure, and its results are promising. The predictor’s
performance is better than that of the traditional load predic-
tion method. With regard to HetNet network planning, [24]
presented a fast handover technique that uses a wireless link
signature based on the user location as the handover authen-
tication data. The techniques are time-varying, unpredictable
and secured with physical encryption to guarantee a distinct
and safe handover.

B. MASSIVE MIMO
Another important 5G enabler is massive MIMO, where data
rates are increasing with reduced interference by using the
beamforming technique to focus signals on one another [2].
The use of massive MIMO provides low latency and achieves
EE communication, which is suitable for 5G develop-
ment [25]. Massive MIMO is implemented by adopting large-
scale and advanced antenna arrays whose width and tilt
can be controlled vertically and horizontally. An example
of massive MIMO implementation is shown in Figure 4.
A uniform planar array, which can be rectangular, hexag-
onal or circular, is used [26]. Enabling massive MIMO
requires regulatory masks to support its statistical nature,
and spectrum regulation management must be enhanced
to consider time, spatial and direction domains. A recent
work addressed Non-Orthogonal Multiple Access (NOMA)
in various forms of MIMO-NOMA transmission protocols,
designed a cooperative NOMA and identified the relationship
between two 5G technologies (NOMA and CR) [27]. The
security issues in 5G networks, specifically in the physi-
cal layer of massive MIMO, HetNet and mmWave, were
also discussed in [27]. A comprehensive survey was con-
ducted by [28], who addressed physical layer technologies,
including massive MIMO, new channel model estimation,
directional antenna design, beamforming algorithms, Media
Access Control (MAC) layer protocols and multiplexing
schemes.

Beamforming is a spatial filtering technique that aims to
enhance spectral and energy efficiency and increase system
security. Hybrid beamforming is a method that combines
digital and analogue beamforming. Fully digital beamform-
ing requires a complete radio frequency chain behind each
antenna and is impractical for mmWave. Sun et al. [29]
explored the multi-cell, multi-user, multi-stream commu-
nication in mmWave homogeneous networks. The follow-
ing hybrid beamforming techniques were proposed and
compared: (1) leakage-suppressing and signal-maximising
precoding, (2) signal-to-leakage-plus-noise-ratio-based pre-
coding, (3) generalised maximum-ratio precoding and
(4) feasibility of zero-forcing precoding. The highest spectral
efficiency was obtained with the second method. The digital
predistortion issue in massive MIMO transmitters for lin-
earising the radio frequency hybrid beamforming array was
addressed by [30]. The solution involved the linearisation of
the main beam direction for its combined far-field signal,

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W. S. H. M. W. Ahmad et al.: 5G Technology: Towards Dynamic Spectrum Sharing

FIGURE 3. Example of HetNet architecture [20].

FIGURE 4. Uniform Planar Array configurations, from left to right:
rectangular, hexagonal or circular [26].

which can effectively broaden the linear angle range. Hybrid
beamforming for single users was applied in mmWave mas-
sive MIMO by [31] by using the dual-stage approach based
on singular value decomposition and zero-forcing. An issue
was identified in the singular value decomposition algorithm,
that is, too small or too large channel matrix eigenvalues limit
the frequency-selective channels. Adaptive beamforming is a
versatile approach of detecting and estimating the signal of
interest at the output sensor array via data-adaptive spatial
or spatiotemporal and interference cancellation. Research
on this method in moving vehicles was conducted by [32]
by using a predictor antenna with a 64-element massive
MIMO for complex OFDM downlink channels. The obtained
accuracy was close to the ideal beamforming gain for non-
line-of-sight channels. Further investigation of real-time pre-
diction with realistic time-frame structures in time division
duplex (TDD) systems was suggested. Pei etal. [33] emulated
the line-of-sight channel accurately via pre-faded synthesis
and analysed over-the-air 5G cellular communication with

adaptive beamforming using a sectored multi-probe anechoic
chamber. A recent study by [34] tackled the interference
issue by using the adaptive beamforming algorithm to miti-
gate interference. The algorithm achieves coherence between
different beams, and each beam is suitable for a specific
terminal. The beamwidth of the main lobe is narrow, and
massive MIMO systems can manage the good sectorisation
between user equipment without interference. The network
capacity and data rate can also be increased.

A highly potential 5G network infrastructure for com-
munication known as cell-free massive MIMO was intro-
duced by [35]. It entails joint signal processing from many
distributed access points (APs) and can offer similar QoS
to all user equipment despite its low complexity. An illus-
tration of how cell-free and cellular differs is shown in
Figure 5. Each AP in cellular massive MIMO is serving
an exclusive subset of the users. While cell-free massive
MIMO has many distributed APs that are jointly serving
the users with the signal encoding/decoding taking place
in a CPU. Björnson and Sanguinetti [36] performed the first
comparison of cell-free and cellular massive MIMOs. Cell-
free massive MIMO was implemented with four levels of
receiver cooperation from fully centralised to fully dis-
tributed with multi-antenna APs. Cell-free massive MIMO
exhibited higher spectral efficiency for all user equipment
compared with cellular massive MIMO. Through mini-
mum mean-squared error processing, the received and esti-
mated signals are sent to a central processing unit instead
of being preprocessed at APs. Ullah et al. [37] proposed

14464 VOLUME 8, 2020

W. S. H. M. W. Ahmad et al.: 5G Technology: Towards Dynamic Spectrum Sharing

FIGURE 5. Comparison between cellular and cell-free massive MIMO systems [39].

training size optimisation for cell-free massive MIMO sys-
tems that is effective when the coherence is low or the
number of users is very large. The method can achieve
a higher downlink rate than the conventional pilot length
method. Zhang et al. [38] conducted a comprehensive survey
on cell-free massive MIMO systems by exploiting chan-
nel hardening and favourable propagation conditions. The
exploitation aimed to reduce the transmission energy and
inter-cell interference in a centralised or distributed man-
ner. The study showed that cell-free systems provide better
coverage than conventional cellular systems and uncoordi-
nated small cells. Chen and Björnson [39] investigated a cell-
free massive MIMO network with channel hardening and
favourable propagation from a stochastic geometry perspec-
tive. They found that hardening can be obtained efficiently by
deploying multiple antennas per AP, and having a few multi-
antenna APs is better than having many single-antenna APs.
Users that are spatially well-separated communicate with dif-
ferent APs subsets and thus exhibit favourable propagation.
However, [39] suggested not to rely on both properties when
designing and analysing cell-free networks; instead, resource
allocation schemes and achievable rate expressions that work
well without the two properties should be used.

The 5G network is expected to serve a massive num-
ber of users and support instantaneous demand variations
at different times and events. Therefore, NOMA has been
explored as one of the promising solutions to this problem.
An example of work in NOMA is the study of [40], who
elaborated on the working principle of the uplink NOMA
framework. The data of two users are transmitted simultane-
ously, and frequency resources and Successive Interference
Cancellation (SIC) are used for reliable data transmission.
The authors also presented the challenges in implementing a
massive number of IoT devices in 5G cellular networks, such
as BS and traffic estimation, channel estimation, interference
management, power allocation and management of device
synchronisation. For NOMA-based multi-user MIMO, [41]
presented a joint interference alignment with the power allo-
cation framework to overcome the immense increase in traffic
in the data network. The framework utilises the sum rate

to provide QoS and guarantee an effective SIC constraint
whilst managing the power to reduce interference within a
cluster. Furthermore, a NOMA two-way relaying method was
developed by [42] by using Karush–Kuhn–Tucker conditions
with dual composition techniques. The relay divides single-
source data into two parallel parts, which are then transmitted
using amplify-and-forward relay. The method can be further
expanded to multiple users. The use of NOMA also aims
to provide control over the complexity of data processing
and signal overhead in 5G networks. In the study of [43],
compressed sensing for NOMA for mMTC was presented.
The proposed schemes use low coherent spreading, which can
improve spectral efficiency and reduce latency by enabling
user data detection and joint activity without activity infor-
mation from the user.

C. ULTRA-LEAN DESIGN
Future 5G technology is expected to enable an ultra-lean
design [2], [44] where ‘always-on’ signals are reduced to a
bare minimum to achieve an EE network at a low opera-
tional cost, as shown in Figure 6. The implementation of this
ultra-lean design can reduce network transmissions without
affecting user data delivery [45]. This feature is critical for
very dense local areas to reduce the overall interference level
for end-user performance at low-to-medium loads and is
essential to high-frequency bands where networks are yet to
be deployed. Ultra-lean design also needs special attention
in terms of backward compatibility for low-frequency bands
because a large number of terminals are already deployed.
Moreover, the implementation of ultra-lean design in Ultra-
Dense Network (UDN) has exhibited significant improve-
ment in enhancing mobility support, increasing throughput
and saving energy as experimentally confirmed by [46], who
provided future research insights into the deployment of 5G.

D. ULTRA-RELIABLE LOW-LATENCY COMMUNICATION
Another important promise of 5G is the ultra-low latency
enabler [2] that can reduce processing delays and transmis-
sion time intervals and widen the bandwidth of radio resource
blocks in which a specific amount of data is transmitted.

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W. S. H. M. W. Ahmad et al.: 5G Technology: Towards Dynamic Spectrum Sharing

FIGURE 6. Ultra-lean design for 5G data transmission [47].

This feature can also avoid queuing delays at the radio trans-
mitter whilst the direct communication link (i.e. D2D) pro-
vides low-latency transmission for devices in close proximity.
To achieve this vision, the physical channel structure must be
designed for fast decoding at the receiver, and the MAC has to
enable immediate access. Collision risks must be minimised
by providing dimensioned instant-access resource alloca-
tions. Several recent studies performed detailed analyses to
achieve this low latency requirement. Lauridsen et al. [48]
measured the performance of current LTE network imple-
mentations and compared it with the initial LTE requirements.
They also identified key performance indicators for consider-
ation in designing and standardising 5G technology, includ-
ing an analysis of critical connected mobility parameters,
such as user and control plane latency, handover execution
time and coverage. In 2018, Moradi et al. [49] proposed a
scalable architecture by combining SDN and NFV for a
customisable and low-latency 5G core network. The system
enabled the creation of custom services for user equipment
with low latency and efficient signalling.

E. ENABLERS FOR mMTC
5G technology also needs enablers for mMTC [2] to achieve
‘zero-overhead’ communication by simplifying the connec-
tivity states of devices and providing channel access with
minimal signalling. Maximising the devices’ sleep opportu-
nities is also useful in reducing energy consumption. Doing
so would lead to long battery life, and devices can operate
for years with small batteries. Optical transmission modes
are also needed to provide connectivity at low rates. This
feature can be attained by providing a ‘spectrum-compatible’
interface for the best coexistence with legacy radio technol-
ogy. Jovović et al. [50] presented an overview of a next-
generation mobile network that integrates all machines and
devices via the IoT concept enabled by the deployment of
mMTC in 5G network. The main advantages of 5G machine
communication is the increased data speed transmission and
capacity of up to 1 Gbps, with latency as low as 1 ms. mMTC
is also targeted to support emerging services and applications
based on the IoT concept. With the implementation of 5G
in the future, mMTC will not only promote the IoT concept
but will also provide an open opportunity to explore the
implementation of the Internet of Everything (IoE).

F. NETWORK MANAGEMENT
Managing a network is one of the crucial issues in any
communication technology. Given the multitude of exist-
ing services and the additional services to be offered in
the new economic sector using 5G technology, intelligent
means of managing the network efficiently are urgently
needed. Autonomous NMs that have self-awareness, self-
configuration, self-optimisation and self-healing proper-
ties are necessary for enhanced cost and energy savings.
Pulcini et al. [51] demonstrated the use of specific proce-
dures based on carrier Ethernet for the reliable management
of HetNets dedicated to 5G networks using SDN configured
for the implementation of energy saving tasks and QoS con-
trol. Self-Organising Network (SON) management in 5G was
identified by Moysen and Giupponi [52] as the key driver of
improvements in operation, administration and management
activities with minimal human intervention. The authors also
reviewed the basic concepts and taxonomy of SON, NM and
machine learning (ML). SON reduces the installation and
management costs of 5G by simplifying operational tasks due
to its capability of configuring, optimising and healing itself.
The autonomous management vision using SON is expected
to be extended to end-to-end networks to satisfy 5G NM
requirements.

The planning of ultra-dense wireless networks [53] and the
characteristics of typical UDNs that appear in a 5G network
were explained by [54]. The study included a comparison
with traditional cellular networks based on the definition by
ITU. The key issues in applying UDNs in 5G were identi-
fied as follows: network architecture and protocol procedure
enhancements, interference avoidance and inter-cell coordi-
nation, EE and super SON. To address one of these UDN
key issues, a survey was conducted on …

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