The Impact of Heterogenous Ultra-dense Network Technologies on the Performance of 4G and 5GNetworks

Abstract

The flood of applications that demand massive data has imposed a challenge for 5G cellular network in order to deliver high data rates, a better quality of service, and low energy consumption. Heterogenous ultra-dense networks are one of the major technologies to address such challenges. HUDNs play a big role in a cellular system. They deliver cost-effective coverage with low transmit power and high capacity to face the risen data and the high expectations of the user's performance. In this paper, we introduce the impact of small cells on the cellular system and the technologies the small cells utilize to make the cellular system faces the subscriber's demands. First, we discuss the fundamentals of used technologies in small cells. Next, we studied small cell management. Then, self-organizing networks are studied. After that, we have reviewed the small cell's power consumption, mobility, and handover. Finally, the real-world experience of mm-waves and MIMO in 5G small cells.

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International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075, Volume-10 Issue-1, November 2020
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Retrieval Number: 100.1/ijitee.A80701110120
DOI: 10.35940/ijitee.A8070.1110120
The Impact of Heterogenous Ultra-dense Network
Technologies on the Performance of 4G and
5GNetworks
Abstract-The flood of applications that demand massive data has
imposed a challenge for 5G cellular network in order to deliver
high data rates, a better quality of service, and low energy
consumption. Heterogenous ultra- dense networks are one of the
major technologies to address such challenges. HUDNs play a
big role in a cellular system. They deliver cost-effective coverage
with low transmit power and high capacty to face the risen data
and the high expectations of the user's performance. In this
paper, we introduce the impact of small cells on the cellular
system and the technologies the small cells utilize to make the
cellular system faces the subscriber's demands. First, we discuss
the fundamentals of used technologies in small cells. Next, we
studied the small cell management. Then, self-organizing
networks are studied. After that, we have reviewed the small
cell's power consumption, mobility, and handover. Finally, the
real-world experience of mm-waves and MIMO in 5G small cells.
Keywords—4G,5G, small cells, mm-wave, SON,MIMO
I. INTRODUCTION
The fifth generation of cellular wireless
communication provides smooth continuous communication
for machines and users. High-resolution video streaming,
telemedicine, telesurgery, smart transportations, and real-
time control are new applications that precept an updating
for reliability, throughput, end-to-end latency, and network
robustness. However, small cell densification is imperative
to achieve the success of the 5G network and make it meet
the highly anticipated increase of capacity to a thousand
times. Network densification will increase the capacity of
the network and cell sites including, macro sites, small cell
deployments, and radio access. The most favorable location
for network densification will be close to urban areas and
large places where there are huge numbers of digital users
who demand high connectivity and fast speeds ten times
faster than 4G. Increasing the number of antennas and small
cell sites besides using sector splitting and massive multiple
input multiple output (mMIMO) technologies achieve
network densification. Cell splitting increases the number of
antennas and that leading to an increasing number of hand-
off which produces larger interference between the small
cell sites. “Fig. 1”shows the interference between the small
cells and macrocells [1]. 5G aims to be autonomously
intelligent and the resources must match all patterns of
traffic, which can be achieved by presenting new wireless
technologies and by increasing node density.
Revised Manuscript Received on November 01, 2020.
Abdullah Mohammed Abdullah Al – Amodi, Ph.D. degree in School
of Electronic Engineering of KIIT deemed to be University, India.
Dr. Amlan Dattaisa Professor and Associate Dean, School of
Electronics Engineering, KIIT, deemed to be university. India.
To be more accurate, deploying small cell densification on
both licensed and non-licensed bands, a live example of
unlicensed bands is WiFi access points (APs), and device-
to-device (D2D) communication that exists to mitigate the
tension between resources and traffic in the conventional
networks. However, due to user mobility and diversity, and
spectrum limitation, new challenges have arisen. Small cell
traffic offloading classified as an effective and important
mechanism to alleviate those challenges [2]. İn small cell
traffic offloading, the heavily loaded cells offload a portion
of their traffic to the low utilized cells which have an
available resource that can be shared with the heavily loaded
cells. Small cell traffic offloading improving the utilization
of resources, alleviating the congestion of the network,
enhancing user service quality and network availability, and
extending the sustainability of the network.
Many technologies have been introduced to enhance the
performance of 4G and 5G networks which will be dis
cussed. In this paper, we studied the developed technologies
of small cell management, self-organizing networks, and the
revolutionary impact on cellular systems. After that, we
have introduced how small cells affect the power
consumption of the system. Subsequently, mobility and
handover through heterogeneous ultra-dense networks
(HUDNs) were reviewed. Finally, the real-world experience
of (HUDNs) using mm-waves and mMIMO in 5G small
cells.
II. SMALL CELLS MANAGEMENT
In LTE, the small cells play a big role in term of
the macro station, it has helped to cover the locations which
macros could not manage very well such as the edge of the
cells. Many kinds of research have been done to manage the
interference of adjacent macro base stations or adjacent
small base stations or interference between adjacent small
and macro base stations
A. Inter-tier interference
When a connection is done between two network elements
of two different tiers, this could be called Inter-tier
interference or cross-tier interference. It's interference
between small cell equipment user and Macro base station
due to the difference of several situations, i.e., Case (1) for
upload inter-tier interference between the macro station and
the small cell user, Case (2) represents downlink inter-tier
interference between the small cell user and (MBS), case (3)
and (4) are upload and download cross-tier interferences
between (MBS) user and (SCBS) respectively [3], [4].
Abdullah Mohammed Abdullah Al-Amodi, Amlan Datta

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Fig. 1. Inter-tier & intra-tier interference scenario
B. Intra-tier interference
Intra-tier or co-tier interference designates the same tier base
stations in the network, it could be between the same macro
base station (MBSs) or the same small cell base stations
(SCBSs) which are positioned randomly and separated at
small distance densely. Furthermore, (SCBSs) will interfere
with each other due to the process of sharing the same band
as a result of not using an allocated orthogonal sub-channel.
Figure (1) demonstrates the intra-tier interference as two
cases, (5) and (6) wherein case(5) an upload intra-tier
interference between small cell user of a cell and small cell
base station (SCBS) of another cell. Case (6) shows the
download intra-tier interference between small cell users
and SCBS of another cell which is not meant to be
connected to that SCBS [4]. In [5], interference management
in ultra-dense networks has been investigated for several
domains by an algorithm that deals with SBSs co-tire
interference. That algorithm schedules OFDM, TDMA, and
interference alignment (AI), besides power optimization.
Firstly, Neighbouring SBS interference is reduced using
OFDMA scheduling and that's by allocating Sub-channel
and establishing stable transmission links. Secondly,
depends on overlapping coalition formation game (OCFG),
SBSs forming a coalition structure which is stable
overlapping where the IA aligns the intra-coalition
interference and TDMA scheduling reduces the co-tier
interference among coalitions. Finally, mitigating the
remaining of the interference by the optimization of the
power further.
C. Fractional Frequency Reuse (FFR)
In cellular networks, managing the radio resources
to address the cross-interference is called fractional
frequency reuse. It is different in the WiFi networks, to
manage the transmission over the cells it`s required
intelligent scheduling for download and upload synchronous
operations. For microcell networks, “Fig. 2”shows the
popular 1-3 FFR scheme which divides the spectrum into
four fixed size bands, one of the bands in each cell is used
by the clients of the cell interior, those do not experience the
interference due to the closeness to the base station, where
the other three bands usually used by clients of the cell
exterior in an orthogonal way between the three cell sectors
just to mitigate the adjacent cells interference. Therefore, the
band used by the clients of the cell interior is used in each
cell, the reuse of the three bands are submitting to the
possible spatial reuse [7]. Dynamic FFR methods for small
cells have been proposed by [8] which calculate the size and
number of bands
Fig. 2. Popular 1-3 FFR scheme (Network deployment)
[6]
used by each small cell based on the cumulative traffic
demand from the clients of the interior and exterior of the
cell; they permit only for better spectral utilization and do
not rely on planned sectorization (unlike microcells). Note
that the FFR schemes only determine the set of spectral
resources assigned to cells - scheduling of clients within
those resources is done by each cell locally (based on per
client feedback) to leverage multi-user diversity. For FFR
was adopted in FluidNet, although other FFR schemes can
also be easily used. While point-to-point MIMO is
automatically incorporated in FFR, other cooperative
techniques such as multi-user MIMO and co-ordinated
multipoint transmissions (CoMP) can also be applied under
FFR [8]. In [9] an algorithm proposed to manage
interference between macro and femtocells by developing
the FFR concept as to manage the interference as the
following: if the femtocell inside the inner region and in low
density it uses arbitrary FFR radio resource hopping but if
the femtocells are in the outer region or inner region with
high density then it uses orthogonal FFR radio resource
allocation. The handover strategy between the macrocells
and femtocells under the hybrid access mode in LTE
network has proposed in [10], the authors introduce a
handover algorithm for the hybrid access mode (registered
and unregistered users ) based on two factors (the velocity
of the user equipment UE and specific stay time interval T),
and they consider the capacity which the femtocell accepts
and the SINR. They gave the priority for those UE velocities
less than 30km/h and signal level more than the threshold.
However, registered UEs have the priority for handover
while unregistered UEs should wait for a threshold time
interval, and then the next procedure of handover can
conclude them. The simulation`s results showed a better
handover results and minimized many of those unnecessary
handovers. Frequent exchange of information between the
small cells and their neighbor smalls cells or between small
cells and macrocells is a direct consequence of non-uniform
user traffic [11]. Self-organizing networks (SON) used to
interact with handover problems, mobility management, and
load balancing. the large scale networks are divided into
small cells, with features of SON, the network provides a
link between the users for task synchronizations and self-
optimization [12].

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DOI: 10.35940/ijitee.A8070.1110120
Handover mobility self-optimization in LTE network was
proposed using handover parameters such as hysteresis (hys)
and time-to-trigger (TTT), the authors in [13] proposed
away to improve the performance of the network to be
specific to increase the throughput and decrease the network
jitter and delay, by tuned the mentioned parameters.
In [14] designed a strategy aims to overcome the of
conventional received power (RSS)-based association
strategies, by user mobility-awareness for mmW networks,
which have proved five aspects: The ability to track the
dynamic changes in the topology of the network and the
conditions of the channel which made by the user mobility.
The strategy considers the load distribution for a small base
station (SBSs) so that the UE connection overcomes the
small base station which is already congested. The need for
periodic reassociation as a result of overcoming repeated
handoffs between SBSs.The unusual aspects of millimeter
waves have been considered such as NLoS propagation,
sensitivity to blockage, and directionality effects. Each UE
connects to an SBS individualistically.
The use of mobile devices has expanded enormously. As a
result of that, conventional networks such as long-term
evolution (LTE) and LTE Advanced will not be able to face
future demands. The researchers come with the fifth-
Generation mobile communication system (5G) which
provides lower latency and higher data rates. 5G technology
has been through many evaluated levels, one of those
creative ideas proposed by [1], the researchers suggested a
potential cellular architecture included the separation of
indoor and outdoor to avoid potential loss through the
buildings using distributed Antenna (DAS) and massive
MIMO (multiple inputs multiple outputs). However,
splitting the plane of SDN and changing the paradigm of 5G
architecture from base station centric to user-centric
(paradigm shift) is poised to achieve sub-millisecond latency
as shown in figure (3) [15]. Small cell base stations (SCBSs)
are controlling the user plane signaling to their mobile
stations (ME) [3].
The enabler's key technologies introduced for next-
generation network densification i.e., user-centric and cloud-
radio access (CRA) mechanisms, device-to-device
communications (D2D), techniques of advanced inter-cell
interference cancellation, separation of control and user
plane, and caching.
D. Device-to-device communications (D2D)
In conventional cellular networks, the communication
between devices can only occur through a base station.
However, in HetNets; the users communicate directly
without using smart devices.
Recently, smart devices became ubiquitous; almost every
user has a smart mobile device that paved the way for
deploying D2D networks. D2D communications alleviate
the load pressure of network loads, improve quality of
service (QoS) and reliability. For service providers, instead
of sending content to all users; it's preferable to send the
content to some users to share it with the rest of the users,
which alleviates the load pressure of the cellular network.
Fig. 3. Paradigm`s shifting from base station centric to
user-centric
“Fig. 4”reveals the D2D communication scenario; Macro
station node (MeNB) sends content to mobile user (MUE1);
MUE1 spread the content to MUE2 which shares the content
to MUE3& MUE4. İn the other hand, the MUE5 received
content from MeNB then it shares the content to MUE6
which sends the content to MUE7. D2D communications
(in-band and out-band) improve the performance of cellular
networks; in terms of cellular coverage, energy, and
efficiency [16]. D2D-aware handover, smart mobility
management, and D2D triggered handover are solutions
proposed by Nokia Research Centre [17].
Fig 4. A scenario of D2D communications
İn cellular systems, D2D communications is an ideal
technology for traffic offloading. Trafic offloading
categorized in terms of delay into two types (sensitive and
tolerant). İn the delayed-sensitive traffic offloading,
interactive and real-time applications are targeted [18],
while in delay-tolerant, non-real-time applications are
targeted such as e-mail, and used to deal with the traffic
storms and promoting the performance of a network., which
rises throughput by linear increase [2]. Many research
papers confirmed that short-range D2D and joint cellular
communications providing flexible transmission
mechanisms [18]-[19].

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E. Distributed Antenna Systems (DAS)
In DAS, dilevering a common signal from the same source
to many RRHs that transmitted simultanously to provide
more indoor/outdoor coverage. The signal foot print is
increased across many transmit points and under-utlizes
spectrum without any scope for spectral reuse which is
unlike FR that foucses on capacity only. The relation
between configuration and stratigies: in FFR, for each cell, a
different frames is generated due to the different operated
spectral bands for cells, therefore, the logical mapping
between BBU and RRHs is one-to-one, which is currently
the conventional maping in C-RAN. İn DAS, a single frame
is transmitted by many RRHs which is achieved by using
single BB, therefore, the logical mapping between BBU and
RRHs is one to many.
1) Adaptive RANs
For more than forty years, cellular communications have
relied on the stationary deployment of radio access.
However, the densification of the network is one of the most
promising ways to tolerate radio access networks (RAN) to
deal with the expected increase of the traffic of data as well
as with the tremendously increased crowding atmospheres
such as conferences, malls, and stadiums [21]. Small cell
base stations (SCBSs) are required for RAN densification
due to the huge number of users and traffic generated is
extremely raised even it is for a small duration of time.
Recently the vision of 5G aims to place hundreds or
thousands of SCBSs per km2. On one hand, in the morning
where people go to their work considered as busy hours for
mobile operators, where the SCBSs capacity is needed
unlike the time after work, the capacity of RAN turns out to
be lower and many of the SCBSs becomes terminated. On
the other hand, in residential zones, the capacity and density
of RAN are needed in the evening when people come back
to their homes. For those reasons, the moving SCBSs can
provide adaptive densification and achieve advanced
efficiency and lesser cost. Instead of installing small cell
base stations on the business areas and residential areas
which will be expensive for the operators while these only
operate at s small duration of time, the idea of moving
SCBSs will make it easier and less expensive by moving the
SCBSs depending on the need i.e., densify the RANs on the
business areas in the morning and in the evening at
residential areas. This mechanism has increased the capacity
of 150% and throughput 120% [4].
2) Cloud-based Radio Access Network (C-RAN)
One of the most cost-efficient ways proposed to deploy 5G
small cells is a cloud-based radio access network which
decouples the processing of baseband unit (BBU) from the
remote radio head (RRH) and allows the centralization
process of BBUs and scaled deployment of RRHs in form of
small cells. Cell densification is the promised method which
refers to increasing the utilization of spatial reuse for the
small cells, each new cell is added expenses the operators or
the service providers. This problem has been addressed by
(C-RAN) [20]. the transmission power between their tiers as
well as the coverage and path loss of the given tiers. Figure
(1) shows the interference between the small cells and
macrocells.
Fig. 5. Cloud-based Radio Access Network
Figure (5) demonstrates the C-RAN, where the BBU and
RRH are decoupled so the BBU moved to datacentre
introducing data signal processing and high-performance
purpose as well as providing high optical transporting
bandwidth to the antennas which called remote radio heads
(RRH) unlike the conventional RAN which have the BBU
and RRH matched together. The fronthaul is defined as the
high-bandwidth optical transport which carries the signals
between the RRHs and BBUs. The bandwidth of the
fronthaul required to be higher than backhaul depending on
the signal's nature [22].
III. SELF-ORGANIZING NETWORK (SON)
SON is a technology that has been designed to make
configuration, planning, optimization, healing, and
management of the network easier and faster by modifying
the various parameters of the network supported by rollback
algorithms [23]. The functionality and behavior of SON
have been defined in the accepted recommendations of the
mobile industry produced by a well-known organization
such as the New Generation of Mobile Network (NGMN)
and third Generation Partnership Project(3GPP). SON has
been introduced progressively with the arrival of the fourth-
generation (4G) in the radio access network, to limit
gradually the impact of teeth trouble potential and to
increasing the confidence as well of the system. The existing
3G networks have been modified by SON for reducing the
cost and enhance the reliability of service. Long-term
evaluation (LTE) is the first technology that uses SON
features and then the technology has been adjusted for the
previous technologies of radio access as UMTS.
Specifications of LTE support the features of SON
inherently such as detection of Automated Neighbour
Relation (ANR) [23]-[25]. Deployment of SON helps the
mobile operators to enhance the network services, for
instance, saving the roll times of network, dropped calls are
reduced, enhancing the throughput, minimizing the
congestion, and saving energy and cost).

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DOI: 10.35940/ijitee.A8070.1110120
A. Architectural types of SON
SON has three architectural types which are: Distributed
SON (D-SON), Centralized SON(C-SON), and hybrid SON.
1) Distributed SON (D-SON)
in this type, the network functions are always distributed
through the element of the network edges or E-node
elements [46]., which indicates a grade of localization
functionality supported by equipment manufacturing of the
radio cell.
2) Centralized SON(C-SON)
In this type, the network functions are concentrated
on the network operational support system (OSS), (in some
countries as the UK is a computer system used for network
management) for allowing a wider overview of the
coordination and elements of the network edges. C-SON
systems are supplied in the network by third parties.
3) Hybrid SON
The combination of the elements of centralized and
distributed SONs produced a hybrid SON[23],[25].
B. Subfunctions of SON
Self-organizing network functionalities are
commonly divided into three major sub-functional groups,
each one of them containing a varied range of use cases
[23].
1) Self-configuration functions
Self-configuration struggles towards the paradigm
of "plug-and-play" so that each newly-installed base station
would be configured and unified into the network
automatically and unified into the network. In other words,
establishing the connectivity, and downloading the
parameter configuration is software. The equipment vendors
must supply the radio cell self-configurations software as
apart of delivery. By using self-configuration, each small
station is added to the network, it is directly registered and
recognized by the network. The parameters of neighbour
small cells (such as antenna tilt, emission power, etc) are
adjusted to deliver a required capacity and coverage as
avoiding the interference at the same time. [23], [25].
2) Self-optimization functions
Every small cell holds hundreds of parameters
configuration that governors various cell site features. Each
of the parameters can be changed based on network
behavior, based on the observations of the UE
measurements and the small cell. ANR is one feature of a
SON that establishes the relations of neighbors
automatically. Other features enhance the parameters of
mobility robustness or random access in terms of the
fluctuations of handover. A very expressive use case is
when small cells automatically switch-off at night hours to
save the operator's energy, to cover the whole area then the
neighbor small cells re-configure their parameters.
However, when the neighbor small cell can't cover the area
demands, the sleeping small cells wake up to serve its users
[23]. Capacity and Coverage Optimization (CCO), Mobility
Load Balancing (MLB), Mobility Robustness Optimization
(MRO), and RACH Optimization SON for Adaptive
Antenna Systems (AAS) are self-optimization functions
[23]-[25].
3) Self-healing functions
When small cells in the network turn out to be
inoperative the mechanism of self-healing aims to reduce
the failure effects, by adjusting the algorithms and
parameters in the neighbor cells to support the inoperative
small cell.[49].
C. SON and load balancing
SONs have been studied intensively to enhance the
small cell user QoS, introducing load balancing algorithms
were proposed in [27], [28]. İn [27] the authors proposed an
algorithm for macrocells, small cells, and HetNets load
balancing, which limits the released load of the full loaded
cells to the neighbor cells. To estimate the cell load status,
the centralized SON (c-SON) has been introduced, which
then decides the user handover for the proper cell for
providing network load balance and avoiding performance
oscillations. To define and estimate the heavily loaded cells,
a threshold was presented. The resource block utilization
ratio was introduced as a method for measuring the cell
load. However, the impact of the neighbor shifted load was
considered to decrease the PingPongs (PPs) of the load
among the cells. In [28] an enhanced adaptive load
balancing algorithm for small cells was introduced using
SON, the parameters of HO are adjusted over the network
by proposing "load balancing efficiency factor". the
algorithm estimates the after-handover edge UE loads, and
remaining available load of neighbor cells then specifying
the operation sequence. However, the offloading from an
overloaded cell to light loaded cell was restricted with
conditions, one of these conditions was the difference load
between the overloaded and light loaded cells is less than
the gap threshold (0.1) to restrict moving loads between
closed loaded neighbor cells.
IV. POWER CONSUMPTION FOR SMALL
CELLS
Minimization of the power consumption and increasing the
throughput are challenges that face the 5G networks. To
minimize the consumption of network power many
proposals have been introduced such as dense small cell
deployment which offloads the macro station`s traffic
instead of serving all the users in the cell, the load is divided
into many surrounding small base stations which will
decrease the load and consequently the transmission power
will be decreased. However, the power consumption of
small base stations cannot be discounted, because saving its
power consumption means saving the total power
consumption of the heterogeneous network like the
following: In [29] three algorithms have been proposed that
aim to consume the power of the heterogeneous network,
the first algorithm based on the distance between the MBS
and SBS. the transmission power is increased with the
distance of the MBS and hence, the algorithm gives the
deactivation priority for the closet SBSs to MBS and serving
their users by MBS just to save power consumption of the
SBSs, but in case the load of SBS is big by users density
that costs the MBS power consumption more than the SBS
consumed power when it`s activated.

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The second algorithm is based on density which aims to
deactivate the SBSs with lower density users and serve them
by MBS so that their consumed power is low to be served
by the MBS and activate the SBS when the power is
consumed by MBS is more than that when the SBS is active.
Those two proposed algorithms lead to the third algorithm
which combines the previous two, if the SBS is close to
MBS and the users are density then it`s deactivated to save
the transmission power of serving the far users as long as the
MBS consumes less power than SBS power consumption
when activated.in the other hand, for those SBS which are
far from the MBS and low user density, can be deactivated
when the power consumption does not exceed the maximum
power, and their power consumption is more than the MBS
when they are deactivated. The third algorithm showed the
ability to save 20% of the daily power consumption of the
HetNet without using small cell deactivation. However, the
antenna array system presented in [30] which was designed
to be cost-effective, and an adaptive cell densification
technique by sectorizing the cell into nine sectors to deal
with the non-uniform and uniform angular traffic loads
using fractional frequency reuse, the results have shown that
when the base station`s load is less than or equal the
minimum of threshold value there will be 40% energy
saving. To achieve the 1000 fold capacity increasing, ultra-
dense small cell networks USNs is one of the techniques
that deliver such a challenge in 5G. it increases the
deification of the network by deploying numerous
Heterogeneous small cells which are described as low power
and cost, SBSs categorized as plug and play, increase the
throughput and coverage of network and improve the
utilization of spectrum [5], [31]. The main challenge that
every small base station is concerned about its performance
and ignoring the damage that it causes to adjacent SBS.
However, SBS should be cooperative with others.
V. SMALL CELL HANDOVER LITERATURE
SURVEY
When a User Equipment (UE) moving from one
place to another with an ongoing data session or ongoing
call, transferring the channel connected to the core network
to another to keep the session or the call connected is calling
handover (HO). HO is considered one of the critical
challenges that face UHDNs due to the closeness of small
cells to each other and to macrocells to provide high data
rates and capacity. Many types of research have been
conducted deeply in the handover to avoid pinpongs, HO
failures, unnecessary HOs, reducing HO, improving the
performance of HO [33]- [44], as well as to make load
balance between small cells and HUDNs [32], [45]-[48]. İn
this section, we briefly reviewed the HO management;
proposed methods, their features, and the challenges that
face the proposed methods as in table (1).
Table I. Handover management literature review
Reference
Tech.
Proposed
method
Features
Challenges
32
LTE
Calculation
the distance
of UE and
load
balancing
Calculation
the distance
of moving
UE by using
the RSS
changes,
the accurate
real UE
distance
Cannot be
estimated due
to changeable
releasing the
load from the
overloaded
cell, and
shifting to
nearest
neighbor
cells
fading,
increasing the
number of
handovers.
33
LTE
HO scheme-
based
distance for
Macro and
small cells.
Reduce the
handover
familiars and
unnecessary
handovers
The distance
of moving UE
cannot be
estimated
accurately
34
5G
HetNet
Minimization
unnecessary
HOs
algorithm
Minimize the
unnecessary
handovers
and signaling
overheads of
scanning
The
computational
complexity be
increased
35
5G
Mobility
aware user
association
strategy
Tracking the
channel
condition,
load
balancing,
and stopping
recurrent
scanning
The procedure
of HO for the
mmwaves has
not been
addressed and
the accuracy
of GPS for
indoor
situations is a
big challenge
36
5G
HetNet
Decouple the
control and
user plane
HO
frequency
was reduced
High
computational
complexity
37
LTE,5G
HO strategy
of MMB
along with
multi-cell
connectivity.
Minimize the
number of
handover
familiars
Increase the
complexity of
UE and
resources
utilizations
38
5G
Markov chain
is based on
the strategy of
handover
management.
Reduces the
handover
fails to 21%
and delays to
and 52 %
Effected on
PP, frequent
and
unnecessary
HO was not
considered
39
LTE
advance
HO detection
with SO HO
parameters
algorithm.
Improve the
performance
of user
mobility by
reducing call
drops and
HOF
increase
computational
complexity
40
5G
HetNet
User velocity
aware HO
skipping
scheme.
Improve the
UE average
throughput in
a two-tier
cellular
network
Estimating the
UE path is
challenging
41
LTE
Reducing the
early HO
scheme.
Reduce the
operational
expenses of
the mobile
operator,
high energy
efficiency. A
super relative
value to TTT
was provided
for an
unbiased
RLF and PPs
Increase the
computational
load
42
5G
Estimating
the state along
with DC
Reduce HO
interruption
time,
increase the
throughput
and decrease
HOFs
Correct tuning
of MSE is
required, DC
increases the
UE complexity
and resource
utilization

International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075,Volume-10, Issue-1, November 2020
41
Published By:
Blue Eyes Intelligence Engineering
and Sciences Publication
Retrieval Number: 100.1/ijitee.A80701110120
DOI: 10.35940/ijitee.A8070.1110120
43
5G
HetNet
Cashing
technique,
load
balancing,
and DC
Store the
future data
contents in
advance, to
use when
wireless
resources are
not
sufficient,
offload UEs
from heavily
loaded cells,
reduced HOF
and energy
consumption
Multi-cell
connectivity
increases the
complexity of
UE and
resources
utilizations
44
5G
Mobility
management
scheme based
on location
tracking
Eliminates
the HO
signaling
overheads,
provide
proactive and
seamless
Handovers
Increase the
computational
complexity
45
4G,5G
Hybrid HO
forecasting
mechanism
Reduce the
HOF and
PPS and
improve the
HO decision
mechanism
High
utilization of
resources
46
HetNet
Load
balancing
algorithm
releasing the
load from the
overloaded
cell and
shifting to
nearest
neighbor
cells
The number of
handovers is
increased
47
HetNet
SINR based
HOR analysis
The gap
between
SINR-free
and SINR-
based HOR
indicates the
effects of
interference
on HO
procedure
48
HetNet
Frequent HO
mitigation
algorithm.
Improve the
QoE of the
user, by
reducing the
HOs and
improve the
throughput
Increase the
computational
complexity
VI. SMALL CELLS MMWAVES:
Transferred data through optical fiber links provide
data rates of multigigabit per second, whereas the
deployment and cost are expensive in many applications.
contrarily, wireless links technology can provide alternative
effective cost to connect the areas that the fiber optics
cannot reach. However, the demand for high data rates
wireless applications and interconnecting the areas beyond
the rollout of fiber optic have been increased which posed a
massive challenge for 5G. To maximize the spectral
efficiency, MIMO and OFDM technologies are used in the
current generation 4G LTE advanced,despite theunexploited
gigantic bandwidth to deal with future multigigabit per
second imaging, multimedia, and mobile applications.
Millimeter waves aim to release the 30 – 300 GHz spectrum
with potential over 100 GHz of new fitting spectrum for
mobile broadband which will reduce the cost, latency, and
interference plus enabling mmwave backhauls and high
dense small cell. In mmwave bands, the signals can travel
only for a few kilometers and cannot penetrate the solid
materials. Unlike the 3GHz signals, which can travel for
many kilometers and able to penetrate the solid materials.
However, this could be an advantage for low interference
mmwaves communication with efficient spectrum reuse for
dense network links and enhancing the security and privacy
of the transmitters. For the commercial user, mmwave bands
are evidenced by IEEE802.3C and sub-bands by
IEEE802.11ad. [49]. The range frequency of microwaves
defined as (6 to 60) GHz), in this band, some frequencies
were reported as a common such as (10.5, 13, 15, 18, 23, 26,
32) GHz, which in many countries reported as congested
especially (13,15, 23) GHz. Accordingly, a higher frequency
is exploited, for instance, in the UK the bands (10, 28, 32,
and, 40) GHz are steered to face the microwave demands
[31]. New radio (NR) operates in the range of (1 GHz to
52.6 GHz ) including licensed and unlicensed spectrum; it
has key features such as spectrum flexibility, high-frequency
operation, forward compatibility, besides ultra-lean design.
New services are enabled by NR forward compatibility; in
the future, it will introduce new technologies. Ultra-lean
design refers to the utilization of always-on transmissions
such as systems information broadcasting, always-on radio
signals for channel estimation, and signals for detecting base
station; to achieve high energy performance and data rates
of the network [50]. In mm-W bands, the propagation loss
increases, and to overcome such a problem, high gain is
required which achieves better coverage and high
availability. 5G mm-wave systems target small cells and use
beam-tracking technologies, which present soft mobility and
user tracking in the small cells. Latency and throughput
performance were experimented using 5G mm-w proof -of –
concept (PoC) (frequency = 73.5GHz, channel bandwidth =
1GHz) system for an outdoor LOS user device with speed
up to 20km/h. However, the result of that workshop with
interleaving frame structure confirmed a lower latency time
of 3ms round-trip for (70 to 80%) in the trail course and
over 1 Gb/s throughput achieved as well for 38% in the trail
course. Moreover, using mm-W PoC having a frequency
and (channel Bandwidth =2 GHz) with two-stream MIMO,
single carrier transmission, and dual-polarization, in the
mmW band, achieved higher data rates e.g. greater than
10Gb/s [8]. 5G mmwave cellular networks support multi-
connectivity, in [51] authors proposed a novel measurement
reporting system that allows macro basestation operates in
legecy band to collect many reportson the overall channel
propagation conditions periodically to make the right
decisions when a multiple control-plane features are
implemented ( handover or intial access). The authors argue
that the proposed method(based on uplink rather than
downlink signals) enables much more rapid and robust
tracking, enabling the use of digital beamforming
architecturesto reduce the measurement reporting delay
dramatically. Sending /receiving data between the core
network and end-user, and mutual information exchanging
through x2 interface between the small cells representing the
backhaul of the

The Impact of Heterogenous Ultra-dense Network Technologies on The Performance Of 4G and 5G Networks
42
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Retrieval Number: 100.1/ijitee.A80701110120
DOI: 10.35940/ijitee.A8070.1110120
5G small cells, which can be via wired or wireless links
depends on the requirement of the backhaul such as ( SBs
locations, the cost of backhaul, intensity of traffic loads.
Etc). The wired backhaul is high cost depends on the
distance and capacity, high data rates, and considered as
reliable connectivity. However, the backhaul could be using
mmwaves spectrum (60,70 to 80) GHz bands, microwaves
band (6 and 60) GHz and sub 6HGz, sub 6 GHz, satellite
technology, and TV white space (TVWS) which is selected
based the environment propagation and parameters of the
system (capacity, location, conditions of interference,
coverage, cost, and the availability of the spectrum). Sub-6
GHz: support nonline of sight (NLOS) propagation and
ubiquitous coverage through obstacles, as a result of features
of NLOS, point to multipoint, the connectivity of backhaul
is possible at the interference cost. The license of the sub-
6GHz spectrum responsible for interference management.
Furthermore, using sub-6GHz for backhaul links is highly
cost, traffic crowded, and vulnerable to interference. [31].
A. Mmwaves and Massive MIMO in 5G
Coverage and capacity of 5G network increased by MIMO
and the throughput of the cell becomes more unified and
faster as well. The studies showed that the median burst is
52mb/s when 4x4 MIMO is used, while it increases to 195
Mb/s when using 5G NR massive MIMO which is 3.8 times
faster. The cell edge burst rate is 27 Mb/s when 4x4 MIMO
is used, while it increases to 79mb/s when the massive
MIMO which is 29 times faster. According to Frankfort
simulation [24],[25], table (1) shows the gains of 5G over
4G in the 5G NR sub-6GHz non-standalone (NSA) network.
However, Tokyo simulation for 5G sub-6 GHz standalone
(SA) network showed that 5G downlink median burst rate
has increased 3.7 times over 4G (from 6 Mb/s to 122 Mb/s),
while the cell edge burst rate increased 3.8 times (from 45
Mb/s to 171 Mb/s). On the other hand, the uplink cell edge
burst rate increased 42.5 times (from 0.4 Mb/s to 17 Mb/s ).
5G NR mmwaves have proven the wrong skeptic that the
mobile can never use mmwaves as stated in the table (2)
(Real-world user experiences with standalone 5G NR, JUN
26, 2018). Dense small cells using mmwaves with spatial
reuse for around range (150m to 200m). to deploy 5G NR,
spectrum aggregation is essential to address the gaps of
mmwaves coverage. Carrier aggregation (CA) is used across
spectrum bands (sub-6GHz), FDD and TDD bands for better
coverage and capacity, and used for spectrum types as well
such as (licensed and non-licensed) bands. 5G (NSA) using
dual connectivity that combines enhanced mobile broadband
(eMBB) and 5GNR together, whereas 5G (SA) using
dynamic spectrum sharing and carrier aggregation. Table (3)
illustrates the difference between NSA and SA networks
[45].
Table II. Burst rates of 4G &5G devices in different
networks
Burst
Rates
4G device
in 4G
network
4G device
after4G
network
5G device
in 4G
network
Median
56 Mb/s
102 Mb/s
493 Mb/s
Cell edge
20
39 Mb/s
184 Mb/s
Mb/s
Table III. Mmwaves proved limits
Table IV. Non-Standalone 5G NR vs. Standalone 5G
NR
VII. CONCLUSION
heterogenous ultra-dense networks (HUDNs) refers to the
connection of different cells such as Macro, Micro, Small,
and Pico cells together in order to improve the network`s
performance, increase the capacity and coverage, and face
the user`s risen demands that can be achieved by increasing
the nodes on licensed and non-licensed bands. The closeness
of small cells of each other produces interference.
FFRmanages the radio resource to address the cross-
interference. D2D communications used to alleviate the load
pressure by sending a content to a user, the same content can
be shared to the rest users to improve the QoS and
reliability. D2D communications is an ideal method for
network traffic offloading. DAS is used to provide more
coverage by transmitting a common signal from one source
that delivered to multiple RRHs simultaneously. C-RAN
decouples BBU processing from RRHs to centralize the
process of BBU and RRHs information of small cells.
Configuring, planning, optimizing, healing and managing
the network foritself by modifying various parameters by
roll back algorithmscalling SON in order to enhance the
network performance easily and faster. We pointed out for
many proposals introduced to improve the power
consumption of small cells. However, we presented a
literature review of HO and mobility of small cells to reduce
HO failure (HOF), and ping pong (PPs) and improve the
small cell load balance. Enabling mmwaves aims to reduce
the cost, latency, and interference. In the other hand,
enabling high dense small cells with multi connectivity and
mmwaves backhauls. Spectrum flexibility, high-frequency
operation, forward compatibility and ultra-lean design are
features of NR. 5G coverage and capacity increased by
MIMO and throughput becomes faster, and more unified.
Studies showed the median burst is 3.8x faster when using
5G NR massive MIMO than using 4x4 MIMO.
skeptics
Proven
Costly and limited coverage
Signified coverage with co-siting
Used for line-of-sight (LOS)
Operated in NLOS
Lacking large form factor
Commercializing smartphones
Non-standalone 5GNR
Standalone 5GNR
Controlled by enhanced packet
core (EPC).
Controlled by 5G next-
generation core (NGC).
4G radio network.
5G sub-6GHz radio network
Control and data over LTE link.
Control and data over 5G NR
link.
RAT using 5G mmwaves and/or
sub-6GHz .
RAT using mmwaves.

International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075,Volume-10, Issue-1, November 2020
43
Published By:
Blue Eyes Intelligence Engineering
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Retrieval Number: 100.1/ijitee.A80701110120
DOI: 10.35940/ijitee.A8070.1110120
The median burst is changed based on the device technology
(4G or 5G) and the infrastructure of the network its self (4G
or 5G) network. Mmwaves proved it can operate in NLOS,
signify coverage with co-sitting and commercialize
smartphones.
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AUTHORS PROFILE
Abdullah Mohammed Abdullah Al – Amodi is
working towards his Ph.D. degree in School of
Electronic Engineering of KIIT deemed to be
University, India. His research interests include
small cell load balance and handoff decision, in
heterogeneous networks.
Dr. Amlan Dattaisa Professor and Associate
Dean, School of Electronics Engineering, KIIT,
deemed to be university. India. He has completed
his B. Tech in Electronics and Electrical
Communication. M. Tech in Microwave and Radar
Engineering and Ph. D in Electronics from IIT
Kharagpur in the year 1987, 1989 and 1992,
respectively.