Improving network performance by mitigating ICI and allocating resources for next
generation wireless networks
1
Surabhi Sharma, 2J.Jayanthi, 3S.Jagannathan
1
Student, Department of Electronics and Communication Engineering, R.V.C.E., Bangalore
Scientist-F, Department of ALD, NAL, Bangalore, India
3
Professor, Department of Electronics and Communication Engineering, R.V.C.E., Bangalore
2
1
sharma90surabhi@gmail.com, 2jayanthi@nal.res.in, 3jagannathans@rvce.edu.in
Abstract— Given the fact that radio spectrum is
becoming a scarce resource in wireless
communications, the orthogonal frequency division
multiple access (OFDMA) has been proposed as a
state of the air interface technology to enable high
spectrum efficiency and effectively combat
frequency-selective fading. In order to realize the
flexibility on access of radio resources, OFDMA
poses a new challenge for radio resource
management (RRM).
A very low-complexity heuristic algorithm is
proposed to achieve the radio resource allocation,
where graph-based framework and fine physical
resource block (PRB) assignment are performed to
mitigate major ICI and hence improve the network
performance. Simulation results indicate that our
proposed scheme can achieve significantly balanced
performance i.e. around 90%
improvement
between cell-edge and cell-center users in multi-cell
networks compared with other schemes, and
therefore realize the goal of future wireless
networks in terms of providing high performance to
anyone from anywhere.
Keywords— Next generation wireless networks,
OFDMA, interference management, resource
allocation.
In order to realize the flexibility on access of radio
resources, OFDMA poses a new challenge for radio
resource management (RRM) [1]. A good RRM
scheme, including subcarrier allocation, scheduling
and power control, is crucial to guarantee high
system performance for OFDMA-based networks.
On traditional design of RRM, most published work
concentrate on the single-cell scenario where
resources are allocated to deliver a local
performance optimization. In future wireless
networks, however, denser cellular deployment
with a lower frequency reuse factor (FRF) [2] is
demanded.
A cellular network or mobile network is a wireless
network distributed over land areas called cells,
each served by at least one fixed-location
transceiver, known as a cell site or base station. In a
cellular network, each cell uses a different set of
frequencies from neighbouring cells, to avoid
interference and provide guaranteed bandwidth
within each cell.
When joined together these cells provide radio
coverage over a wide geographic area. This enables
a large number of portable transceivers (e.g.,
mobile phones, pagers, etc.) to communicate with
each other and with fixed transceivers and
I INTRODUCTION
telephones anywhere in the network, via base
The next generation wireless networks target stations, even if some of the transceivers are
ubiquitous high data rates, efficient resource (e.g., moving through more than one cell during
spectrum and power) usage and economical transmission.
network deployment. Due to its promising features, Cellular networks offer a number of desirable
OFDMA [1]-[5] is adopted in many emerging features cellular systems such as the Long Term Evolution 1) More capacity than a single large transmitter,
(LTE) [2] and IEEE 802.16m [3] for achieving since the same frequency can be used for multiple
those ambitious objectives of next generation links as long as they are in different cells.
networks.
2) Mobile devices use less power than with a single
transmitter or satellite since the cell towers are
closer.

Anyone may transmit, as long as they
respect certain transmission power and other
limits: open spectrum bands such as the
unlicensed ISM bands and the unlicensed
ultra-wideband band, and the somewhat
more regulated amateur radio frequency
allocations. Often users use a "listen before
talk" contention-based protocol.

Only the licensed user of that band may
transmit: the licensing body may give the
same frequency to several users as a form of
frequency reuse if they cannot interfere
because their coverage map areas never
overlap.
3) Larger coverage area than a single terrestrial
transmitter, since additional cell towers can be
added indefinitely and are not limited by the
horizon
2. SPECTRUM ALLOCATION
The radio spectrum [4] is the range of frequencies
used for wireless applications such as broadcast
television and radio, cell phones, satellite radio and
TV, wireless computer networks, Bluetooth, GPS,
police dispatch, and countless other general and
specialized applications that we use every day. For
the most part, it’s difficult for these applications to
utilize the same frequencies at same time. For
example, if a local broadcast TV station used the
same frequency as your cell phone, our cell phone
would not work very well due to interference from
the TV station, or your TV picture would be fuzzy
due to interference from your cell phone, or perhaps
both. To help avoid such conflicts, radio spectrum
is carved up into different portions, and each
portion is allocated to one or more services that,
generally speaking, may be able to co-exist with
each other.
A number of forums and standards bodies work on
standards for frequency allocation [6], including:
International Telecommunication Union (ITU),
European
Conference
of
Postal
and
Telecommunications Administrations (CEPT),
European Telecommunications Standards Institute
(ETSI) and International Special Committee on
Radio Interference (Comité international spécial des
perturbations radioélectriques - CISPR)
High-demand sections of the electromagnetic
spectrum [7] may sometimes be allocated
through auctions. Every day, users rely on
allocation of frequencies for efficient use of
such devices as: cell phone, cordless phone,
garage door opener, car key remote control,
broadcast television and audio, Standard time
broadcast, vehicle-speed radar, air traffic radar,
weather radar, mobile radio, Global Positioning
System (GPS) [3] navigation, satellite TV
broadcast reception; also backend signal
dissemination, Microwave oven, Bluetooth, WiFi, Zigbee, RFID devices [3] such as active
badges, passports, wireless gasoline token, nocontact credit-cards, and product tags toll-road
payment vehicle transponders, Citizens band
radio and Family Radio Service, Radio control,
including Radio-controlled model aircraft and
vehicles, wireless microphones and musical
instrument links.
2.1 FREQUENCY REUSE FACTOR (FRF)
These standards bodies have assigned frequency
The frequency reuse factor (FRF) [2]-[9] is the rate
bands in three types of allocation:
at which the same frequency can be used in the
 No one may transmit: frequencies reserved network. Frequency reuse is a key characteristic in
for radio astronomy to avoid interference at cellular networks. The whole available bandwidth
for a system is divided into several narrower
radio telescopes
subbands, each of which is assigned once to a cell
of each cluster consisting of several adjacent cells.
The number of subbands should equal the size of
cell-cluster, termed as Frequency Reuse Factor
(FRF). This way, all directly neighboring cells in
the system use different subbands to avoid heavy
CCI [1] among them; and the entire available
system bandwidth can be reused in all cell-clusters
distributed over the network covered area so that
the utilization of valuable spectrum resources can
be ensured to some extent. Thus, the next question
is how to determine the value of FRF δ, which is
another essential parameter in radio network
planning.
With a bigger FRF value, the distance between
inter-interfered cells becomes larger. And
consequently, the CCI can be significantly reduced,
and better cell/system coverage can be attained.
However, on the other hand, since the available
system bandwidth must be shared by a cell-cluster
(i.e., among every δ adjacent cells), each cell within
the cell-cluster is assigned a smaller number of
channels and therefore can carry less traffic limiting
the number of User Terminals (UTs) [8] that can be
served. This may lead to an unfavorable spectral
efficiency.
When a smaller FRF value is used, more bandwidth
is available per cell. Since the same frequency
resources are then reused within a short distance,
the CCI in the system is increased limiting the
number of UTs that can be served. The question is
to answer what FRF value would be the best choice
to gain the maximum cell capacity.
Fig 1 Cellular network with FRF 1/4
Common values for the frequency reuse factor are
1/3, 1/4, 1/7, 1/9 and 1/12 (or 3, 4, 7, 9 and 12
depending on notation). And in the figure 1 the
frequency reuse factor is taken as ¼.
3. DESIGN METHODOLOGY
In this work a downlink cellular network [1]
consisting of a set of BSs denoted by 𝕁 = {1, . . . , 𝐽},
where J is the total number of cells in the network is
considered. The total number of users in cell 𝑗 is
denoted by 𝑀𝑗 , while the number of available
PRBs that can be scheduled for downlink data
transmission in each TTI is denoted by N. Note that
each BS is allowed to use all 𝑁 PRBs as the
frequency reuse-1 deployment is applied in the
network.
3.1 Resource allocations: For a cell 𝑗 where 𝑗 ∈ 𝕁,
𝑗
𝑗
𝑗
𝑗
let 𝐴𝑀𝑗 ×𝑁 = [𝑎𝑚𝑛 ] and 𝑃𝑀𝑗 ×𝑁 = [𝑝𝑚𝑛 ] be PRB
and power allocation matrices [5], respectively,
𝑗
𝑗
with elements 𝑎𝑚𝑛 and 𝑝𝑚𝑛 defined as
𝑗
𝛼𝑚𝑛 = {
1 , 𝑖𝑓 𝑃𝑅𝐵 𝑛 𝑖𝑠 𝑎𝑙𝑙𝑜𝑐𝑎𝑡𝑒𝑑 𝑡𝑜 𝑢𝑠𝑒𝑟 𝑚
(1)
0,
𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
And
𝑗
𝑝𝑚𝑛 = {
𝑗
𝑝 € (0, 𝑃𝑚𝑎𝑥 ], 𝑖𝑓 𝑎𝑚𝑛 = 1
0,
𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
(2)
Where 𝑃𝑚𝑎𝑥 denotes the maximum transmission
power [10] of each BS. Since the same PRB will
not be assigned to more than one user at the same
𝑗
𝑗
time in each cell, we have ∑𝑀
𝑚=1 𝑎𝑚𝑛 = 1.
3.2 Interference evaluation: The performance of
multi-cell networks [9] with ICI can be evaluated
using SINR [1] instead of SNR for interferencelimited networks. The instantaneous SINR for user
𝑗
𝑚 using PRB 𝑛 in cell 𝑗 is denoted by 𝛾𝑚𝑛 and it
can be expressed as
(𝑗→𝑚)
𝑗
𝑗
𝑎𝑚𝑛 𝑝𝑚𝑛 𝑔𝑛
𝐿 (𝑑(𝑗→𝑚) )
𝑗
𝛾𝑚𝑛 =
(𝑗∗→𝑚)
𝑗∗
∑𝑗∗€ 𝐽,𝑗∗ ≠𝑗 𝑝𝑚∗𝑛
𝑔𝑛
𝐿(𝑑 (𝑗∗→𝑚) ) + 𝑁𝑜
Eqn. (3)
where 𝑗 ∗ represents the 𝑛eighbouring cell in which
𝑗∗
user 𝑚∗ is allocated with the PRB 𝑛 (𝑎𝑚∗𝑛 = 1),
𝑗→𝑚
𝑗 ∗ →𝑚
𝑔𝑛
and 𝑔𝑛
denote the channel gains from
BSs of cell 𝑗 and neighbouring cell 𝑗 ∗ for user m on
∗
PRB n, respectively, 𝐿 (𝑑(𝑗→𝑚) ) and 𝐿 ( 𝑑(𝑗 →𝑚) )
denote
the
distance-dependent
path
loss
(independent of 𝑛) from BSs of the serving cell and
interfering cells to user m, respectively, and 𝑁0 is
the thermal noise variance.
Subsequently, the data rate achieved by user 𝑚 of
cell 𝑗 can be calculated by Shannon’s formula and
expressed as
Figure 2 represents hexagonal structure of 7 cells
with base station (BS) at the centre. There are 5
users assigned for each cell out of which some act
as central users n some as edge users. The circle
(red in color) shown at the centre of every cell
depicts the range of the central user. Also inter cell
interference between 2 cells can be seen (red lines
drawn shows interference).
𝑁
𝑗
𝑅𝑚
𝑗
= ∑ 𝐵 . 𝑙𝑜𝑔2 (1 + 𝛾𝑚𝑛 ) [𝑏𝑖𝑡𝑠/𝑠𝑒𝑐]
𝑛=1
Eqn. (4)
Where 𝐵 is the bandwidth of a PRB.
4 SIMULATION RESULTS
The simulation parameters used are as follows:Figure 3 Average throughput of network for cell
Number of cells -7, Cell radius – 500m, bandwidth centre user.
– 5MHz, Carrier frequency – 2GHz, Cell-edge area
ratio – 1/3 of the total cell area, Total number of
PRBs – 24, Frequency spacing of a PRB -180Khz,
Total transmission power per cell -43dbm, LOS
path loss model -103.4 +24.2 log10(d) dB, d in km,
NLOS path loss model - 131.1 +42.8 log10(d) dB, d
in km, Shadowing standard deviation -8db, Channel
Model - Rayleigh multipath model, Thermal noise -174 dbm/Hz.
The results obtained from the research work are
shown below:-
Figure 2 Graphical representation of LTE with ICI
Figure 4 Average throughput of network for cell
centre user
Figure 3 and 4 represents network performance of
cell edge user and cell centre user. As number of
users increase, average throughput decreases. But
then we have taken 3 different values for weighting
factor i.e. 3, 4 and 5, and as the values of weighting
factor goes from 3 to 5, there is an increase in
average throughput of the edge users when
compared to the reference cell-edge users. On the
other hand the average throughput of centre users
remains quite constant for both reference and
network cell-centre users; with the constant
weighting factor i.e. 1 and a balance between the
average throughput of edge and centre users can be
seen at weighting factor 4. This observation also
indicates that our scheme can provide not only
consistent performance improvement to cell-edge
users but also better performance protection for
cell-center users especially when high ICI is
experienced in the network.
Figure 6 is clearly depicting interference
connections between all the users of the network.
There are 4 users in each cell which gives a total of
28 users. The interference connections (blue lines)
are shown between the x-coordinate points of cell
user and the y-coordinate points of cell users.
Figure 7 Spectrum distributions for available
subcarriers (4 users/cell).
Figure 5 User connection pattern for 4 users/cell.
Figure 5 represents a user connection pattern
between the 7 cells. As there are 4 users / cell, that
means there will be a total of 28 users in 7 cells.
The diagonal shape users are depicting intraconnections between the 7 cells whereas the rest
represents inter cell connections of 7 cells. X-axis
shows the user connection pattern whereas Y-axis
tells us about the number of users which are 28.
Figure 7 represents the spectrum distribution for
available subcarriers. Total number of subbands
available is 24 i.e. total numbers of PRBs is 24
which also specify that after these 24 subbands are
used; frequency is reused for other users present.
And here also we have considered 4 users/cell.
Cross (blue color) depicts spectrum distribution for
available subcarriers for given number of users.
After the 24 subbands are being used for 14 users
i.e. 2 users/ cell concept after that the frequency
subbands are reused for 4 users/ cell i.e. for 28
users.
5
CONCLUSION
In this project, a comprehensive resource allocation
scheme was proposed for downlink multi-cell
OFDMA networks. The scheme included radio
resource and power allocations, which were
implemented separately to address the formulated
problem with reduced complexity.
Figure 6 Interference graph/connection between all
the users of the network i.e. 4 users/cell.
For radio resource allocation, the graph-based
framework combined with fine-scale PRB
assignment algorithms was proposed to effectively
manage ICI and improve performance of the
network in a centralized manner.
Given the solution of radio resource allocation, the
optimal power allocation was performed
independently in each cell to maximize network
throughput by maximizing the performance of its
own cell-edge users under the condition that
performance of cell-center users of adjacent cells
are not degraded much. The optimal solution was
obtained.
Simulation results showed that the proposed
scheme
achieved
significant
performance
improvement for cell-edge user’s i.e.
1. Average throughput for weighting factor 3 in
case of reference cell-edge users was 1.5 Mbps and
jumped to 1.9Mbps for network cell-edge users
2. Average throughput for weighting factor 5 in
case of reference cell-edge users was 4.5 Mbps and
jumped to 4.9Mbps for network cell-edge users
3. A desirable performance for cell-center users was
achieved i.e. for both the reference and network
cell-centre users it was qite balanced i.e. 1.9Mbps.
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