IRJET- Intercell Interference Mitigation Techniques

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 10 | Oct 2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1277
Intercell Interference Mitigation Techniques
1M-Tech Student, Dept. of Electronics and Communication Engineering, Sri Sai College of Engineering and
Technology, Punjab, India
2Assistant Professor, Dept. of Electronics and Communication Engineering, Sri Sai College of Engineering and
Technology, Punjab,India
-----------------------------------------------------------------------***--------------------------------------------------------------------
Abstract :- To address the demands for high speed data
keeps on increasing, LTE systems face the potential issues
related to Intercell interference due to increased network
traffic density, thereby affecting the spectral efficiency.
Interference in cellular networks can be categorized as
Intracell Interference and Intercell Interference. The
orthogonality amongst the subcarriers diminishes the effect
of Intracell interference as LTE downlink systems employ
OFDMA technology. However, Intercell interference that is
produced as result of using the same frequency by the
serving and the neighboring cell greatly reduces the cell
throughput, hence reducing the spectral efficiency. Thistype
of interference is highly pronounced incaseofcelledgeusers
(CEU). Thus, in order to improve the efficiency oftheexisting
LTE systems Intercell interference mitigation is of
paramount importance. In this paper we discuss the
principle of orthogonality among the various adjacent
symbol streams. We also give a brief review about some of
the interference mitigation techniques.
Keywords: OFDMA, Inter-Cell Interference, Partial
Frequency Reuse, Fractional Frequency Reuse, Soft
Frequency Reuse, Soft Fractional FrequencyReuse,Spatial
Filtering (SF), User Equipment (UE).
LTE, a 4G wireless technology regulated by 3GPP (3G
Partnership Project) that is beingemployed bythetelecom
companies all-around the Globe to tackle the issues
encountered earlier with regards to speed andmultimedia
services. To enable the user’s access high speed network,
as the LTE network propagates, it augments the traffic
density, thus facing interference. As the spectrum is
limited, Interference is the major hurdle in achieving high
data rates. Though filters have been employed to mitigate
interference but the fact still remains that it cannot be
completely eliminated [3].
LTE-A or LTE Release 10 further puts an impetus on
increasing the data rate in a cost efficient manner with
increased capacity and improved spectral efficiency. To
achieve the objective of LTE-A, component upgrading is
required [11]. These components include Femtocells and
Pico cells that bring network closer to the users. A
Femtocell can be regarded as a low power base station
employed either in home or a small business
establishment. It provides coverage to the cell edge users
or indoors where service is otherwise unavailable. On the
other hand, to deal with the coverage issues of a dense
population or to extend coverage of a Macrocell, a Picocell
is used. It usually covers a small area as in buildings, trains
and now in aircrafts as well [3].
To further enhance the transmission efficiency and to
expand the coverage area of a base station (BS), LTE is
implemented as MIMO, Relay Station, and Carrier
Aggregation, CoMP [2]. LTE systems utilize OFDMA
technology that offers immunity against frequency fading
by bifurcating bandwidth among sub carriers [12]. Thus,
OFDMA is employed in LTE-A systems with the aim of
achieving high Throughput and Spectral Efficiency.
In order to increase the system capacity, Frequency Reuse
technique is used. In FRF-1, user can access the entire
bandwidth at once but must deal with interference caused
by neighboring cells [8] [13]. In FRF-3 scheme, bandwidth
is split into three sub channels so that the adjoining cells
use different frequencies. In FFR, bandwidth is split as
Majority Group and Minority Group; each provided a part
of bandwidth [14]. Majority groupcoverstheouterregions
surrounding the users in the inner region, thereby
increasing the throughput in the cell edges while as
throughput is reduced among cells center users than that
in FRF-1 scheme [15]. Another technique PFR also called
FFR with full Isolation isolates the external regions from
inner regions leading to reduced interference betweenthe
two regions [16]. In case of SFR, One third (1/3rd) of the
available bandwidth is allocated to cell edge users with
amplified power and the rest of the bandwidth is utilized
by the cell center users with low power [2]. This technique
proves to be efficient as the cell center users can utilizethe
entire bandwidth and the cell edge users can access only
the allocated sub band with higher priority.
Gerald Kelechi etal; in [3] makes use of heterogeneous
networks (HetNets) and the technical issues faced by
employing themsoastomitigateinterference.Interference
is one of the chief issues faced by LTE operators’ and
implementing solution techniques at terminal end can
prove to be effective. The work has primarily relied on
eICIC techniques for mitigation. V.Rekha in [2] has
emphasized on the concept of frequency reuse and
simulated a numberoftechniquesamongstwhichSFFRhas
provided the highest throughput in comparison withother
schemes. Basically it’s based on power allocation and
different categories of FFR schedulers.However,thefuture
scope of FFR, that is; EFFR and DFFR have not been
1. INTRODUCTION
2. RELATED WORK
1 2Aamir Nazir Beigh , Prabhjot Kaur

discussed. A. Daeinabi etal in [3] has compared a number
of algorithms governingIntercell InterferenceMitigation in
terms of throughput in LTE Downlink Networks. The
results obtained reveal thatintercell coordinationschemes
have higher throughput as resources are allocated as per
the information exchanged between the eNodeB’s. Since
dynamic schemes adjust instantaneously to the network
changes, they display a better result in terms of cell
throughput. However, they create new challenges to the
system that impact the efficiencyforimplementationinthe
real world. Thus it suggests selecting an algorithm that
may be suitable for achieving a particular goal rather that
providing a general solution for mitigating interference.
Muhammad Umair Ghori in [1] focuses onsynchronization
between the base stationsusingDynamic CooperativeBase
Station selection (DCBS). Here, SINR and Capacity of the
system are evaluated when coordination is applied
between the Cells. Three different situations; Coordinated
Multipoint Transmission and Reception (COMP), Non-
COMP and DCBS have been compared.
3.1 Inter-Cell Interference Coordination Technique
The basic frequency reuse schemes for OFDMA-based
cellular systems with the diverse frequency reuse factor
(FRF), signified by K. The FRF is characterized as the
number of adjacent cells which cannot utilize the same
frequencies for transmission. Its converse, 1/K, compares
to the rate at which the same frequency can be utilized in
the network or we can say 1/K is a factor to indicate how
proficiently the bandwidth is utilized in the cellular
framework. At the point when K=1, the whole bandwidth
available for transmission is utilizedinall cells.Inthiscase,
the clients near the cell center will encounter high Signal-
to-Interference and Noise Ratio(SINR)becauseofthelarge
path loss from adjacent cells[3][7]. Notwithstanding, the
clients at the cell boundary will experience the ill effects of
a small SINR, which may increase an outage rate at the cell
boundary [6]. With the end goal to enhance the SINR all
through the cell coverage area while diminishing the
outage rate at the cell boundary, the entire bandwidth can
be separated into three channels or subbands, each of
which is allocated to adjacent cells in an orthogonal
manner. It compares to K=3 and diminishes the usable
bandwidth for each cell. Be that as it may, the clients at the
cell boundary will encounter high SINR, diminishing inter-
cell interference. Note that a subband is a subset of
subcarriers, or, in other words whole subcarriers of each
channel in the OFDM framework [14]. Unlike the multi-
channel case of a solitary channel is partitioned into three
subbands to be assigned to each cell regardless of whether
the two cases compare to K=3. To enhance the
performance at the cell boundary, an idea of fractional
frequency reuse (FFR) has been proposed for the OFDMA
cellular framework. By definition,FFR isa subcarrierreuse
plan to allocate just a part of the total bandwidth, that is, a
subset of subcarriers, to each cell with the end goal that 1
<K < 3. In FFR schemes, the entire bandwidth is separated
into subbands, some of which are allocated to an alternate
location in the cell [19]. Another sort of FFR conspire
where an alternate frequency reuse is utilized, contingent
upon the area in the cell [2]. Since the clients close to the
cell center experience a high SINR, K=1 can be kept up for
them. With the end goal to maintain a strategic distance
from interference in any case, the higher frequency reuse
factor should be utilized at the cell boundary. K=1 and K=3
are utilized at the inner locale and boundary, separately
[14]. For this situation, the entire transmission capacity is
separated into four diverse subbands, among which
subband 0 is utilized by all cells (i.e., K=1), while whatever
remains of them are orthogonally doled out to various
cells, that is, K=3. The equivalent thought can be stretched
out to various arrangements, for instance, K=1 for the
inner area (center) and K=3/2 for the outer locale
(boundary) [6]. With the true objective to upgrade the
information transmission efficiencyoftheFFRdesignsK=1
can be so far acknowledged while decreasing the inter-cell
interference in OFDMA cellular frameworks. Toward this
end, we distribute unmistakable levels of power to the
subbands, dependent upon the customer region. High
power is dispensed to the subbands for the customers at
the cell boundary, and low power is distributed to all
unique subbands for the customers in the center (inner
region), while orthogonally orchestrating the subband for
those at the cell boundary of the adjacent cells as in FFR.
This particular thought is insinuated as the soft frequency
reuse (SFR).
3.2 Inter-Cell Interference Coordination Technique
As long as intra-cell and inter-cell synchronization can be
maintained in the OFDM-based cellular systems, each sub
channel can be considered autonomous because of the
orthogonality among subcarriers. In any case, the
interferences from adjacent cells may cause significant
performancedegradation;thereforetheinterferencesignal
can be randomized for enabling the averaging effect of the
inter-cell interference. More specifically, a Cell-Specific
Scrambling code or Cell-Specific Interleavercanbeutilized
for randomizing the interference signal [6]. Let X(m)[k}and
C(m)[k] indicate the transmitted signal and a scrambling
code of the mth cell for subcarrier k, m = 0; 1; 2; . ....;M-1.
The received OFDM signal in the frequency-domain is
given as;
Here, H[k] is the gain of channel, Z[k] is additive noise of
the subcarier k. If m=0 denotes the serving cell, equation
can be decomposed in manner as;
Y[k] ≈H(0)[k]C(0)[k]X(0)[k] +
Received signal Y[k] can be descrambled by the code as;
Y(0)[k] ≈ (C(0)[k]) * Y[k]
3. INTER-CELL INTERFERENCE MITIGATION
TECHNIQUES

Thus, interferences from neighboring cells can been
whitened utilizing scrambling codes.
A cell-specific interleaving technique is often alluded to as
Interleaved Division MultipleAccess(IDMA)technique[6].
The IDMA technique is like the cell-specific scrambling
technique for the case of single-user detection, where it
whitens the interferences from contiguouscells.Itwhitens
the inter-cell interference by utilizinga specific Interleaver
at every cell, while the cell-specific scrambling technique
performs a similar activity by utilizing a specific
scrambling code. Particularly when the multi-user
detection technique is utilized in IDMA, it can decrease
inter-cell interference more adequately than the cell-
specific scrambling technique by canceling interference
iteratively with multiuser locator [6].
3.3 Inter-Cell Interference Cancellation Technique
To mitigate interferences from the adjacent cells, we have
to distinguish the interfering signals first, so that we can
remove them from the received signal. It is generally hard
to identify the interfering signals from adjacent cells in
practical circumstances. However Spatial Characteristics
(SC) can be utilized to mitigate interference whenmultiple
antennas are accessible at the receiver. One technique is
the Interference Rejection Combining (IRC) technique,
which exploits the interference statistics retrieved at
various antennas. The IRC technique can be seen as a
speculation of the Maximum Ratio Combining (MRC)
technique that fuses the SC of the received signal for IRC at
the receiver. In IRT, IDMA technique for a single user,
interference at the receiver is viewed as noise. However
with multi-user receivers, the execution is enhanced by
demodulating the interfering signals and the desired
signal, and thereby detecting iteratively with a Posterior
Probability Decoder (PPD).
Fig. 3.1 IRC Technique
As shown in Figure 3.1, Consider the receiver with M
antennas subjected to the neighboring cell Interference as
well as Noise[6]. Let Hi[k] and Zi[k] denote the channel
Gain and Additive noise Interference for the kth subcarrier
of the ith antenna in the receiver, respectively (i = 1; 2; . . .
;M. For the transmitted signal X[k] the obtained signal at
the ith Antenna is given by;
Yi[k]=Hi[k]X[k] + Zi[k] , I = 1,2,..,M
In Vector form,
Y[k] = H[k]X[k] + Z[k]
Interference Cancellation methodologyiscenteredaround
Spatial filtering (SF) [7] and it requires the services of
multiple antennas User Equipment (UE). Intercell
interference Coordination method capitalizes on efficient
radio resource management modusoperanditocoordinate
the channel allocation in nearby cells and minimize the
interference level. Conclusively, Interference
Randomization procedure spreads the user’stransmission
over a dispersed set of subcarriers with the end goal to
randomize the interference situation and accomplish
frequency diversity gain.
The investigation has discovered that interference
Coordination is powerful for moderate traffic load since
coordination permits total Interference Rejection (IR).
While as, the Interference Randomization demonstrates
proficient execution in the event of heavily loadedsystems
since the random subcarriers scrambling stimulates
fluctuations in the interference situation accordingly
prompting a robust frequency Diversity Gain. Interference
Cancellation method is based on SF and it employs a
number of multiple antennas UE.
REFERENCES
1. Muhammad Umair Ghori etal, (2017),
“Comparative Analysis of Intercell Interference
Mitigation Techniques in LTE-A Network”.
2. V. Rekha, (2016),”Inter-Cell Interference
Mitigation Techniques in Long Term Evolution
Networks: A Survey”.
3. Ijemaru Gerald Kelechi etal,(2014) “Inter-Cell
Interference Mitigation Techniques in a
Heterogeneous LTE-Advanced Access Network”.
4. A. Daeinabi etal,(2012) “Survey of Intercell
Interference Mitigation Techniques in LTE
Downlink Networks”.
5. Frederic Lehmann,(2012),”Iterative Mitigation of
Intercell Interference in Cellular Networks Based
on Gaussian Belief Propagation”.
6. “MIMO-OFDM Wireless Communications with
MATLAB; Intercell Interference Mitigation
Techniques” Volume 2, Chapter 8.R.BosisioandU.
Spagnolini,(2008),”Interference Coordination vs.
4. CONCLUSION

InterferenceRandomization inMulticell 3GPPLTE
System”.
7. MohamedA.Aboul Hassan,(2015),”Classification
and Comparative Analysis of Inter-Cell
Interference Coordination Techniques in LTE
Networks”.
8. Ijemaru, G.K., Udunwa, A., Ngharamike, E., and
Oleka, E. (2014)“EvaluatingtheChallengingIssues
in the Security of Wireless Communication
Networks in Nigeria.” International Journal of
Innovative TechnologyandExploringEngineering
(IJITEE).Vol. 3.
9. Jinfei, S. (2009) “Mitigating Interference between
LTE and 2G/3GNetwork.” [online] available from
http://www.huawei.com/en/static/HW-
079472.pdf
10. Kummithe, R. (2012), “Interference Mitigation in
4G LTE-A Heterogeneous Network”. University of
Texas
11. Debbabi N, Kammoun I, Siala M. “Performance
Optimization of Amplify- and-Forward Relaying
Schemes for Uplink OFDMA Communications.
Third International Conference on
Communications and Networking, Hammamet”.
2012. p. 1–7.
12. Afroz F, Sandrasegaran K, Kim H A. “Interference
Management InLte Downlink Networks”
International Journal of Wireless and Mobile
Networks (IJWMN). 2015; 7(1):91–106.
13. Novlan TD, Ganti RK, Andrews JG, Ghosh A.
“Comparison of Fractional Frequency Reuse
Approaches in the OFDMA Cellular Downlink”
Conference: Global Telecommunications. 2011
Jan. p. 1–5.
14. 4G++“Advanced Performance Boosting
Techniques in 4th Generation Wireless Systems”
Available from: http://4gpp-
project.net/attachments/section/4/WP4_ICIC_v3.
pdf.
15. Kwan R, Leung C. A Survey of Scheduling and
Interference MitigationinLTEJournal ofElectrical
and Computer Engineering. Journal of Electrical
and Computer Engineering.
16. Selim MM, Khamy ME, Sharkawy ME. “Enhanced
Frequency Reuse Schemes for Interference
Management in LTE Femtocell Networks”
International Symposium on Wireless
Communication Systems (ISWCS), Paris. 2012.
17. M. C. Necker. InterferenceCoordinationinCellular
OFDMA Networks. IEEE Network 22(6):12,
December 2008.
18. S. Shukry, K. Elsayed,A.Elmoghazy,andA.Nassar.”
Adaptive Fractional Frequency Reuse (AFFR)
scheme for multi-cell” IEEE 802.16 systems. In
Proceedings of IEEE HONET,December 2009.

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