An Investigation on the Performance of Intra-site and Inter-site Coordinated Multipoint LTE-A Networks

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2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)
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978-0-7381-3289-1/21/$31.00 ©2021 IEEE
An Investigation on the Performance of Intra-site and
Inter-site Coordinated Multipoint LTE-A Networks
Sandeep Gulia
Department of Electronics and Communication Engineering
Faculty of Engineering and Technology
Jamia Millia Islamia,
New Delhi, India
sandeepgulia@gmail.com
Anwar Ahmad
Department of Electronics and Communication Engineering
Faculty of Engineering and Technology
Jamia Millia Islamia,
New Delhi, India
aahmad4@jmi.nic.in
Abstract— Coordinated multipoint (CoMP) is a novel
interference mitigating technique that can alleviate or even
exploit the inter-cell interference as a beneficial signal in the
homogenous and heterogeneous cellular mobile networks.
Coordinated scheduling/coordinated beamforming (CS/CB) is
one of the CoMP schemes that suppresses the inter-cell
interference within a set of coordinating cells, thereby
improving the performance of mobile users, particularly those
located at cell edges. This article aims to evaluate the cell
coordination benefits offered by CS/CB scheme in the
homogenous cellular networks. Specifically, we investigate the
throughput and spectral efficiency performance of CS/CB in the
intra-site and inter-site scenarios. Simulation results suggest
that CS/CB-CoMP scheme can bring noticeable performance
gains compared to the conventional non-coordination scheme.
Further, we observe that inter-site CoMP offers improved
performance than intra-site CoMP due to reduced inter-cluster
interference.
Keywords—coordinated multipoint, coordinated beamforming,
spectral efficiency, cell-edge throughput
I. INTRODUCTION
The soaring data demands in cellular networks have led to the
deployment of increasing dense cell networks in the fourth
and fifth generation (5G) mobile networks. This has resulted
in degraded performance for the cell-edge users due to large
inter-cell interference from the neighbor cells. Typically, the
signal to interference ratio (SINR) of cell-edge users remains
low relative to cell-center users owing to the low signal
strength from the desired base station and strong interfering
signals from the undesired nearby cells at the cell boundaries.
Therefore, imbalance of coverage and capacity remains a
prime concern at the cell-edge in the mobile networks. There
are several categories of techniques with diverse underlying
principles that have been developed to curb the interference
[1]. For instance, inter-cell interference coordination (ICIC),
enhanced ICIC (eICIC) and further enhanced ICIC (feICIC)
is one class of techniques wherein cell-coordination is
achieved via X2 interface by exchanging various types of
control messages [2]. These schemes control inter-cell
interference by segregating and scheduling radio resources
among coordinating cells in power, frequency and time
domains in a coordinated manner. However, these techniques
are semi-static in nature and may not be able to cope with
dynamically varying interference scenario in the adverse
radio environments [3]. Other major approaches include
successive interference cancellation (SIC), interference
alignment (IA), advanced receiver design with improved
signal processing algorithms such as interference rejection
combining (IRC) and network assisted interference
cancellation and suppression (NAICS) etc. To minimize
inter-user and inter-stream interference in the multiple-input-
multiple-output (MIMO) systems, several precoding
techniques [4]–[7], for instance —zero forcing (ZF),
minimum mean square error (MMSE), block diagonalization
(BD) and joint transmitter-receiver precoding etc. have been
developed and their extended versions by several works have
been explored further [7].
The coordinated multipoint technique was developed by third
generation partnership project (3GPP) for long term
evolution–advanced (LTE-A) networks with a relatively new
concept or notion which looks differently at inter-cell
interference [8], [9]. In one of the CoMP approaches, inter-
cell interference from other cells is not treated as an unwanted
signal and instead utilized as a useful signal which
constructively adds to increase the strength of the desired
signal. CoMP is a dynamic cooperation approach with fast
information exchange where base station cooperate to either
avoid interference or utilize it as an advantageous signal.
CoMP comprises multiple approaches with different
mechanisms to control interference. The CoMP schemes are
defined into three major categories- joint transmission-
CoMP (JT-CoMP), dynamic point selection (DPS) or
dynamic cell selection- CoMP (DCS-CoMP) and coordinated
scheduling/coordinated beamforming- CoMP (CS/CB-
CoMP). In the JT-CoMP, a group of cells- called cluster, can
simultaneously transmit to a target user equipment (UE) in a
coordinated manner. Since a mobile user device can receive
same signal data from multiple base station concurrently in
the same resource block and subframe, its signal strength and
hence SINR increases [10]. As a result, coverage and
throughput of mobile users improves to provide a consistent
user experience even at cell boundaries. In DCS-CoMP
schemes, a mobile user can switch its connection dynamically
to one of the most appropriate base station in cluster
according to the channel conditions. Since user data is
available at all the coordinating base stations, a UE can
receive desired signal from different base stations at different
time instants in order to achieve best performance in terms of
user throughput. This is a fast switching approach where UEs
can change connections on subframe basis depending upon

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the radio environment [10], [11]. Since both JT-CoMP and
DPS-CoMP schemes jointly process and exchange both user
data and channel state information (CSI), they are termed as
joint processing (JP) schemes. In CS/CB-CoMP approach,
unlike JP schemes, neither the user data is available at all
coordinating cells simultaneously, nor a mobile user is
allowed to receive simultaneously (or switched dynamically
as in DCS) from multiple cells. Instead, each cell in the
cluster user data processes the user data separately and
transmits to its associated users only. However, scheduling
and beamforming actions are performed in coordination by
cluster cells in order to reduce the inter-cell interference. We
discuss in detail about CS/CB in the next section.
In principle, JP schemes offer better throughput gains than
CS/CB but involve more complexity [10]. Both schemes
require tight synchronization and are highly sensitive to the
backhaul delays. Therefore, practical implementation of
these schemes necessitates high capacity backhaul for desired
performance in the real environments [11]. On the other hand,
CS/CB has relatively less relaxed synchronization and
backhaul capacity requirements, however, throughput gains
provided by CS/CB are also comparatively small.
Nevertheless, CS/CB is a preferred candidate in high
interference cellular networks with constrained backhaul
capacity [12]. In this article, we evaluate the throughput and
spectral performance of CS/CB-CoMP scheme and analyze
the performance gains offered comparative to the non-
coordination single cell transmission schemes.
II. COORDINATED SCHEDULING AND
BEAMFORMING
In this section, we provide a detailed overview of CS/CB-
CoMP scheme. Firstly, basic mechanism involved in the
CS/CB process is presented and then related mathematical
equations are discussed.
A. CS/CB-CoMP—Principle Mechanism
The CS/CB is a cell-coordination technique which aims to
avoid inter-cell interference by coordinated scheduling of
radio resources and coordinated antenna beamforming by
cluster cells in a radio environment. Fig. 1 illustrates the
fundamental operation of CS/CB scheme where three
adjacent sectors are coordinately transmitting to the three
cell-edge users, denoted as UE1, UE2 and UE3. Each cell site
consists of three sectors (or cells) where each cell is
implemented with an evolved node B (eNB). In CoMP
terminology, an eNB or base station is referred to as
transmission point (TP) and each cell or sector may comprise
one or more TPs [8]. However, for the sake of simplicity, we
consider only one TP per cell. TP is a low power base station
configured with a set of transmit and receive antennas and has
relatively low coverage. When two or more TPs
corresponding to same physical cell site coordinate, this is
termed as intra-site CoMP [13]. On the other hand, if the
cooperating TPs relate to different cell site, the cooperation is
called inter-site. Since TPs in case of intra-site CoMP are
collocated, no additional backhaul link is required for
interconnections. However, in case of inter-site CoMP, TPs
are located at a distance, therefore high capacity backhaul
links are required for inter-communication [14]. The CoMP
scenario depicted in Fig. 1 is an example of inter-site CoMP,
where cooperating TPs belong to different sites and are
connected to a central entity, called central unit (CU), via
high capacity backhaul links. CU controls and manages the
overall coordination process of the CoMP system. Each TP
serves and processes data separately for its associated users
only, as indicated. However, scheduling and beamforming
decisions are performed in coordination by three TPs. Each
UE estimates and feedbacks local channel parameters (local
CSI) to its serving point, which forwards it to the CU. The
CU computes joint or global CSI by exploiting information
from the local CSI collected from each TP and shares it
concurrently among all coordinating TPs. Since global CSI
contains scheduling and beamforming information about all
coordinating TPs, each TP takes it into account when
designing beamforming coefficients and scheduling radio
resources for its cell users [15]. Thus, under the control of
CU, scheduling of radio resources and antenna beamforming
with the cooperation area of coordinating TPs is performed in
such way a minimum inter-cell interference is radiated
towards unintended users. For instance, in Fig. 1, TP1 designs
narrow antenna beam and points towards intended user UE1
and mutes its beam towards unintended users (UE2 and UE3).
Similarly, TP2 and TP3 direct their beams towards target users
—UE2 and UE3 respectively only and silence their beams
elsewhere. In addition, coordinated TPs schedule frequency
resources to their respective UEs such that same frequency
resources are not allocated to nearby cell-edge users in order
to avoid interference further. For example, while TP1 assigns
f1 resource to UE1, TP2 and TP3 allocate f2 and f3 resources to
UE2 and UE3 respectively. Note that coordinated scheduling
and coordinated beamforming are two separate processes as
described above, however, both are usually implemented in
conjunction to maximally alleviate inter-cell interference and
to achieve optimal performance in interference-dominated
environments [16]. Consequently, received signal quality of
interference prone UEs is improved, resulting in enhanced
throughputs and spectral performance [10].
Fig. 1. Illustration of CS/CB-CoMP scheme

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B. Beamforming Equations
Let us assume a cellular mobile system where cells are
grouped into C non-overlapped static clusters without any
coordination among the cluster cells. Consider each cluster
has B number of cells with N number of users per cell. The
number of base station transmitter antennas are assumed to
be Nt and each UE receiver is considered to be equipped with
Nr antennas. Consider nth user being served in the bth cell in
the cth cluster, where n ∈ {1, 2, …, K}, b ∈ {1, 2, …, B} and
c ∈ {1, 2, …, C}. The received signal vector,
1
r
N
n
y

for
the nth user with no coordination in the non-CoMP clustered
cellular system can be expressed as
'
, , , , , ,
1, 1
''
, ' ', ' ', '
' 1 ' 1
' ' ,
'
c
c
c
m
BN
m m b m b m b m i p i p i
bi i b p
i p m
BN
m b p b p b
bp
b p m p
cc
n
y H w x H w x
H w x
   
 

 





(1)
where Ψc represents the cth cluster. Since there is no cell
coordination assumed, first term in (1) is the desired signal
quantity and rest of the received signal terms are interference
for intended user m. However, interference is represented in
separate terms in (1) to distinguish different type of
interference as intercepted by user m. Accordingly, second
term refers to the aggregate of interfering signal vectors
intended for users of other cells in the cth cluster. The third
term represents inter-cluster interference experienced by the
mth user. We ignore the multi-user and inter-stream
interference within a cell in (1). In the first term,
, rt
mb N BN
H

,
,tr
BN N
mb
w

and
1
,t
BN
mb
x

represent complex channel matrix, global precoding matrix
and the data symbol vector respectively from serving cell b
corresponding to user m. Without loss of generality, it is
assumed that
 
2
,1
mb
Ex 
where E{∙} denotes the statistical
expectation.
, mb
H
takes the form
12
[]
T T T T
N
H h h h 
where
1t
BN
m
h

is the channel to mth user from all the base
stations in cluster c. The channel matrix can be represented
as
, , ,
.
LS
m b m b m b
H g H
(2)
where
,
L
mb
g
denotes the large-scale fading gain and
,
S
mb
H
represents small-scale Rayleigh fading channel matrix with
distribution
 
0, 1
whose elements are identically and
independently distributed (i.i.d.) cyclic symmetric complex
Gaussian. We assume equal power distribution from each
base station with maximal power being unity. The last term
1
r
N
m
n

denotes additive white Gaussian noise with zero
mean and variance σ2. The SINR corresponding to received
signal vector in (1) is given by
'
2
,,
''
2 2 2
, , , ' ', '
1, 1 ' 1 ' 1
' ' ,
'
|| ||
|| |||| ||
cc
m b m b
B N B N
m i p i m b p b
i i b p b p
i p m b p m p
cc
m
SINR Hw
H w H w

    
   



   
(3)
Next, we consider the cluster cells to be coordinating using
the CS/CB-CoMP scheme in the above mentioned scenario.
In this case, inter-cell interference within the cluster is
alleviated and therefore second term in (1) vanishes. Further,
ignoring the inter-cluster interference (interference from
outside the cth cluster), (1) and (2) reduce respectively to
, , ,
c
mm m b m b m b
b
ny H w x


(4)
2
,,
2
|| ||
m b m b
m
SINR Hw


(5)
It can be observed by comparing (1) and (2) respectively with
(4) and (5) that signal quality and SINR of intended user m
improves markedly. Note that whereas inter-cell interference
from other cells within a cluster is suppressed in CS/CB,
inter-user interference within a cell still may exist in multi-
user MIMO (MU-MIMO) systems [17]. In that case, received
signal vector and corresponding SINR can be expressed as
'
, , , , , ,
1,
''
, ' ', ' ', '
' 1 ' 1
' ' ,
'
MU
c
c
m
N
m m b m b m b m b p b p b
bp p m
BN
m b p b p b
bp
b p m p
cc
n
y H w x H w x
H w x
 

 





(6)
'
2
,,
''
2 2 2
, , , ' ', '
1 ' 1 ' 1
' ' ,
'
|| ||
|| |||| ||
c
MU m b m b
N B N
m b p b m b p b
p b p
p m b p m p
cc
m
SINR Hw
H w H w

  
  




  
(7)
The second term in (6) represents intra-cell or multi-user
interference and the third term corresponds to aggregate of
multi-user interference from other clusters. From the above
discussion, it can be noted that multi-user interference in
CS/CB scheme depends only on other users within the same
cell and not on the users of other cells in the same cluster. The
intra-cell interference can be reduced by applying suitable
precoding scheme and therefore second term in (6) may
become non-existent [18].
In CS/CB scheme, the achievable rate for user m can be
expressed as
 
2,,
log 1
m b m b
R


(8)

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where
,mb

denotes SINR of the mth user in bth cell.
Correspondingly, the sum rate of the bth cell in the cth cluster
can be defined as
 
, 2 ,
1
log (1 )
N
c
S b m b
m
R




(9)
where N is the total number of active users in the bth cell. The
average sum rate of cth cluster with size B and N number of
active users per cell is given by
 
, 2 ,
11
log (1 )
BN
S C m b
bm
RE




(10)
III. RESULTS AND DISCUSSION
We consider a downlink CoMP system model, similar to the
one visualized in Fig. 1. The simulation is carried out using
Vienna LTE-A simulator which is freely available under
academic usage license [19], [20]. The cluster size is taken as
B = 3 with three active single antenna users per cell (or sector)
distributed in a uniform random fashion represented by red
crosses. The geometry of system layout is presented in Fig. 2
where 7 hexagonal cell sites are shown designated as A, B,
C, D, E, F, and G, assumed to be connected to CU via ideal
backhaul links. The inter-site distance considered is 500 m.
Each cell site is partitioned into three sectors, each equipped
with directional antennas as indicated by blue arrows. The
sectors associated with cell-site A are labelled as A1, A2 and
A3. Similarly, cells of site B are designated as B1, B2, B3,
and so on. We consider distance-dependent path loss
propagation model with a decay factor of 3.76. The
shadowing effect follows log normal distribution with a
standard deviation of 8 dB. Major simulation parameters
assumptions are listed in Table 1. The transmit antenna gain
pattern employed in the simulation is given by
2
3
( ) min 12 ,
dB
dB
m
AA



 





(11)
where θ ∈ [-1800, 1800] is the angle between antenna azimuth
and user device, θ3dB (=700) is the half power beamwidth of
antenna main lobe and Am (=20dB) is the maximum
attenuation.
Table I – Simulation Parameters
Parameter
Value
Cellular layout
Hexagonal grid, 7 eNBs sites, 3
sectors per site, wraparound
Inter-site distance
500 m
Number of antennas at each TP/UE
1
UE load per sector
3
Carrier frequency
2 GHz
System bandwidth
20MHz
UE speed
30 Km/h
Scheduling
Proportional fair
Precoding
Zero forcing
Receiver algorithm
MMSE
Pathloss model
128.1 + 37.6·log10 (d) dB
(d in Kms)
Simulation length
50 TTI
Fast fading model
Typical urban (TU)
Traffic model
Full buffer
Scheduling
Round robin/CoMP
Shadowing standard deviation
8dB
Shadowing correlation between cells
0.5 (inter-site)/1.0 (intra-site)
Penetration loss
20dB
Cell-edge SINR
5 dB
eNB /UE transmit power
46dBm/23dBm
eNB/UE Antenna gain
14dBi/0dBi
eNB/UE antenna height
20m/1.5m
Noise power spectral density
-174 dBm/Hz
Modulation schemes
QPSK, 16-QAM, 64-QAM
Network synchronization
Synchronized
The simulation layout in Fig. 2 represents an intra-site CoMP
framework wherein cells A1, A2 and A3, corresponding to
site A are shown coordinating and the cooperation area is
represented by shaded area. Fig. 3 illustrates inter-site CoMP
operation where all cell-sites are shown contributing in the
coordination process. However, whereas all sectors
corresponding to site A are involved in the inter-site CoMP
process, only those sectors of rest of the sites are coordinating
which are located in the first tier of site A.
Fig. 2. Intra-site CoMP layout
Fig. 3. Inter-site CoMP layout

2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)
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Fig. 4 and Fig. 5 depict respectively the cumulative
distribution function (CDF) of average user throughput and
average user spectral efficiency for intra-site and inter-site
CoMP schemes. For comparison and reference, non-
coordinated (non-CoMP) scheme with identical simulation
parameters is used as baseline. As expected, cell-coordination
schemes provide improved throughput as compared to non-
CoMP scheme. Further, it can be observed that inter-site
CoMP offers superior performance than intra-site scheme.
The prime factor behind the improvement in the inter-site
case is the more effective suppression of interference due to
elimination of inter-cluster interference from neighbor
clusters. In the intra-site coordination, cell users which are
located well within the cluster cells remain unaffected from
the inter-cell interference from outside the cluster [13].
However, cell-edge users experience high inter-cell
interference from neighbor cells of hand, inter-cluster
interference from other cell-sites is well the surrounding
clusters. This leads to degraded performance contained in the
inter-site CoMP due to coordinated scheduling such users and
hence cell-edge throughput falls. On the other of frequency
resources as well as coordinated beamforming process among
different cluster cell-sites [15]. Further, since resources are
more efficiently utilized due to inter-cluster coordination in
the inter-site case, it offers improved users spectral
efficiency.
Fig. 4 CDF of average user throughput
Fig. 5. CDF of average UE spectral efficiency
The performance of average user throughput and average user
spectral efficiency as a function of SINR is displayed in Fig.
6 and Fig. 7 respectively. Note that cell-edge mobile users
belong to bottom area in the graphs. We observe that non-
CoMP scheme performs poorly in low SINR regime due to
high inter-cell interference. However, performance improves
as the SINR grows in the upper region. The intra-site scheme
provides marginal improvement in the lower region and tends
to follow non-coordination scheme in the high SINR regimes.
We can observe that inter-site CoMP provides significant
performance gains, particularly in low to medium SINR
regions. The performance gains corresponding to all the
schemes are summarized in Table 2. It can be observed that
inter-site CoMP yields best performance and offers better
peak user throughput, average user throughput and edge user
throughput as compared to both non-CoMP as well as intra-
site CoMP. The average cell throughput and user spectral
efficiency are also enhanced in inter-site case. Further, the
fairness index of both intra-site and inter-site improves,
however, average resource block (RB) per transmission time
interval (TTI) per UE and RB occupancy is reduced slightly
for both the schemes.
Fig. 6. Average user throughput vs SINR performance
Fig. 7. Average user spectral efficiency vs SINR
performance

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Table II – Performance of CoMP and Non-CoMP Schemes
Scheme
Peak/Average/
Edge UE
throughput
(Mbps)
Average cell
throughput
(Mbps)
Average UE
spectral
efficiency
(bits/s/Hz)
Fairness
index
Average
RBs/TTI/UE
RB
occupancy
Non-CoMP
4.49/2.14/0.69
6.43
0.38
0.744
33.33
100.00%
Intra-site CoMP
5.38/2.76/1.08
8.27
0.57
0.759
29.25
88.01%
Inter-site CoMP
6.79/3.70/1.40
11.11
1.18
0.810
19.19
58.39%
IV. CONCLUSION
In this article, first we introduced coordinated multipoint
process technique and discussed its merits relative to the
conventional interference mitigation techniques in the
cellular networks. We described the key mechanisms of
fundamental CoMP schemes and explored in detail the
operation and mathematical modelling of CS/CB technique
in particular. Further, we evaluated and analyzed the
performance of CS/CB scheme in the intra-site and inter-site
scenarios. This is validated through simulation results that
CS/CB provides improved average user throughput and
spectral efficiency comparative to the non-coordination
schemes. Further, this is observed that performance of inter-
site CoMP excels as compared to the intra-site CoMP due to
reduced inter-cluster interference and more efficient
utilization of system radio resources.
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