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Self-organized Dynamic FFR Resource Allocation
Scheme for LTE-Advanced Relay Based Networks
Ahmed S. Mohamed
1
•Mohammed Abd-Elnaby
1
•
Sami A. El-Dolil
1
Published online: 25 July 2016
Springer Science+Business Media New York 2016
Abstract Inter-Cell Interference (ICI) from neighboring cells is a major challenge that
severely degrade the performance of Orthogonal Frequency Division Multiple Access
based cellular mobile systems, particularly for cell-edge users. An efficient technique to
mitigate ICI is interference coordination. The most commonly Inter-Cell Interfere Coor-
dination technique is Fractional Frequency Reuse (FFR). Furthermore in order to effec-
tively improve cell-edge performance in terms of coverage extension and throughput, the
3rd Generation Partnership Project introduced the use of relays in Long Term Evolution-
Advanced (LTE-A) networks to achieve self-backhauling of radio signals between Evolved
NodeBs (eNBs) and UEs. This paper introduces a Self-Organized Dynamic FFR Resource
Allocation scheme (SODRA-FFR) which dynamically allocates frequency resources to cell
inner and outer regions in relay based LTE-A networks to improve cell edge performance
and maximize fairness among UEs. In this scheme, the downlink frequency resources are
dynamically allocated to cell inner and outer regions and the outer region frequency
resources are dynamically distributed between eNB and relay stations in each cell based on
coordination between neighboring eNBs and relay stations through a message passing
approach over LTE-X2 interfaces. The performance of the proposed SODRA-FFR
scheme without and with relays is evaluated using MATLAB simulations and compared
with different combinations of frequency resources allocation to cell inner and outer
regions as well as with other frequency reuse scheme (i.e., frequency reuse-1 and fre-
quency reuse-3). The results show that the proposed SODRA-FFR scheme improves cell-
edge performance and achieves high degree of fairness among UEs compared to reference
resource allocation schemes. The results also show that the proposed SODRA-FFR
&Mohammed Abd-Elnaby
moh_naby@yahoo.com
Ahmed S. Mohamed
Ahmed.abouhiba@te.eg
Sami A. El-Dolil
msel_dolil@yahoo.com
1
Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt
123
Wireless Pers Commun (2016) 91:933–955
DOI 10.1007/s11277-016-3506-3
scheme with RSs improves the fairness performance by 30 and 13 % compared to that of
frequency reuse-1 and frequency reuse-3 schemes, respectively. In addition, the proposed
SODRA-FFR scheme with RSs achieves 55 and 26 % increase in cell-edge throughput
compared to that of frequency reuse-1 and frequency reuse-3 schemes, respectively.
Keywords Long Term Evolution-Advanced (LTE-A) Resource allocation
Relay Station (RS) Orthogonal Frequency Division Multiple Access (OFDMA)
Inter-Cell Interference Coordination (ICIC)
1 Introduction
Transmission over wireless channels endures from fading phenomena and from co-channel
interference [1]. Orthogonal Frequency Division Multiple Access (OFDMA) has gained
increasing interest recently. Due to its ability to combat the Inter-Symbol Interference (ISI)
resulting from the frequency selective fading, OFDMA is regarded widely as a key
modulation and multiple access technique for various types of wireless communication
systems, including next-generation cellular mobile systems such as IEEE 802.16 m
Worldwide Interoperability for Microwave Access (WiMAX) [2,3], 3GPP Long Term
Evolution (LTE) of UMTS [4] and LTE-A [5]. OFDMA is a form of Orthogonal Frequency
Division Multiplexing (OFDM), which is the underlying technology. In OFDMA, the
frequency-selective wideband channel is divided into a number of non-frequency selective
parallel orthogonal narrowband sub-carriers. The orthogonally of the OFDMA narrowband
sub-subcarriers ensures that the intra-cell interference can be avoided. However, ICI or so-
called Co-Channel Interference (CCI) from neighboring cells considered as a major
challenge that degrade the performance of OFDMA based cellular mobile systems, par-
ticularly for cell edge users. For next generation cellular mobile systems, the effective
reuse of the available frequency resources can highly improve system capacity. With a
smaller Frequency Reuse Factor (FRF), more resources are available for each cell.
However, the usage of FRF-1 results in excessive ICI near the cell-edge and this degrade
the system performance in terms of system capacity and coverage. The conventional
method to deal with this problem is by increasing co-channel distance using higher cluster
size. However, increasing clusters size decreases the available radio frequency resources
for each cell the consequences of this are restricted data transmission rate and lower system
spectrum efficiency in general. In order to improve cell-edge performance while retaining
system spectrum efficiency of frequency reuse-1, several approaches for interference
mitigation are recommended by 3GPP-LTE standard [4], namely, ICI cancelation, ICI
randomization, Adaptive beam forming, and ICI avoidance/Coordination (ICIC) [6–13].
Interference reduction using ICIC achieved by applying restrictions to resources allocation
in a coordinated way among network entities. Resources for coordination can be (time/
frequency and/or transmit power). The ICIC schemes can be broadly classified into two
main categories, static and dynamic ICIC. The static ICIC schemes rely on fractional reuse
concept in which each cell in the system is partitioned into two geographical regions inner
and outer regions with fixed resource allocation in each region. Dynamic ICIC schemes, on
the other hand, dynamically allocate resources to inner and outer regions based on dynamic
interference information from neighboring cells. In order to effectively mitigate the ICI,
the 3GPP introduced the use of FFR for cellular mobile systems. The FFR aims at
934 A. S. Mohamed et al.
123
effectively mitigating ICI by applying different FRFs to UEs situated in different regions in
each cell [14–17]. The FFR scheme statically partitioned each cell in the cellular mobile
system into inner region and outer region. The UEs situated in the inner region with higher
received signal quality are allowed to use a lower FRF compared to UEs situated in the
outer region with lower received signal quality. In order to effectively improve cell-edge
performance in terms of coverage extension and throughput, relays are used to achieve
self-backhauling of radio signals between base stations and mobile stations. For this rea-
son, relay technologies have been actively investigated and considered in the standard-
ization process of the next-generation mobile broadband wireless communication system.
As a next-generation 3GPP standard, LTE-A exclusively takes the relay technology into
account [18–22]. Self-Organizing Network (SON) is an automation technology introduced
to make the planning, configuration, optimization, management and healing of mobile
radio access networks simpler and faster. In order to increase the network performance and
reduce the capital expenditures (CAPEX) and operational expenditures (OPEX) for
operators, SON concepts have been introduced in the LTE (E-UTRAN) standards starting
from the first release of the technology (Release 8), and expanding in scope in subsequent
releases. 3GPP has defined a set of LTE SON use cases and associated SON functions.
Among the proposed SON use cases, the management of ICI is of utmost importance
[23–26]. ICIC schemes have been rather well investigated using system level simulations
and theoretical analysis. In [27], a theoretical capacity and outage rate analysis of an
OFDMA cellular system assuming FFR and proportional fair scheduling has been pre-
sented, where the users are classified as cell-center users and cell-edge users based on the
geographical location. The optimization of design parameter (SINR threshold or distance
threshold) of FFR has been investigated using graph theory in [28], and convex opti-
mization in [17]. It has been shown in [17] that the frequency reuse-3 scheme is the optimal
frequency reuse scheme for the cell-edge users. The average cell throughput in FFR system
is derived in [29] as a function of the distance threshold for both Maximum Signal to
Interference plus Noise Ratio (MSINR) and Round Robin (RR) scheduling schemes. The
authors in [30] configured the FFR scheme for the downlink of LTE cellular systems using
analytical optimization technique. In [31], the authors proposed a mechanism that selects
the optimal size of the inner and outer regions for each cell as well as the optimal
frequency resources allocation between these regions that either maximizes the user sat-
isfaction or the mean user throughput. Several Extensions of the standard FFR
scheme have been investigated in a number of recent articles. In [32], the authors intro-
duced an Incremental Frequency Reuse (IFR) scheme which relies on dynamic adaptation
of frequency resources allocation based on the cell load conditions. Similar schemes that
dynamically adapt sub-band allocation to user distributions and traffic load are introduced
in [33,34]. Comparative studies of FFR and other resources allocation schemes, in par-
ticular the Soft Frequency Reuse (SFR) scheme are given in [35,36]. The author in [37]
investigated the effect of the limitations of the standard FFR scheme on the performance of
the large-scale networks with irregular cell structure and introduced a Generalized FFR
(GFFR) scheme for flexible resources allocation. Their proposed GFFR scheme based on
optimization of resources allocation (sub-bands and power), the GFFR scheme dynami-
cally adapts the allocation of the radio spectrum and power resources to the level of the
interference of each cell-edge zone. For highly interfered cell-edge zones, interference is
minimized by power reduction or sub-band isolation, whereas for the other cell-edge zones
more radio spectrum is allocated.
The authors in [38] evaluated the downlink performance of FFR in LTE networks
employing a metric combining throughput and fairness. They considered different
Self-organized Dynamic FFR Resource Allocation Scheme for…935
123
scenarios combining FFR with two different scheduling algorithms (round robin and
proportional fair). Their results showed that if the fairness of the UE throughput distri-
bution is to be maintained, FFR offers no gain if proper scheduling is employed.
The authors in [39] proposed a dynamic mechanism that selects the optimal FFR
scheme based on a User Satisfaction (US) customized metric. Their proposed
scheme partitioned the cell into inner region and outer region and calculates the US metric
for successive combinations of the inner region radius and inner region frequency allo-
cation and then selects the optimal inner region radius and the optimal frequency resources
allocation between these regions with main target to maximize the user satisfaction metric.
They compared the performance of the FFR scheme that is selected by their proposed
mechanism with frequency reuse- 1 and frequency reuse-3 schemes. The comparison
shows that the selected FFR scheme decreases the total cell throughput; however, their
results show that the selected FFR scheme achieved higher US values by allocating the
frequency resources between inner region and outer region in a more fair way.
In [40–42], Nortel proposed an adaptive FFR scheme which applied a proper FFR
pattern in order to react to different user distributions and adopted different transmission
power levels according to the amount of interference. In [43], the authors investigated the
problem of the downlink subcarrier scheduling in OFDMA based cellular networks. The
authors proposed a dynamic FFR cell architecture that partitions sub-carriers into two
groups: One group is reused in the whole cell area whereas the other group is partitioned
into sectors. Their proposed scheme achieved higher system throughput, however, the cell-
edge performance degraded compared to that of the static FFR scheme. In [44], the authors
proposed a downlink interference avoidance scheme for LTE networks that uses a dynamic
inter-cell coordination between neighboring eNBs using X2 interfaces connecting eNBs
together. They compared the performance of their proposed scheme with a number of
reference ICIC schemes; the results showed that their proposed scheme outperformed the
performance of reference ICIC schemes in terms of cell-edge and sector throughput. In
[45], the authors proposed a dynamic FFR scheme with combined Adaptive Modulation
and Coding (AMC) and random access sub-band techniques in order to improve
throughput and fairness in WiMAX system. In [46], an interference management and
dynamic frequency resources scheme in OFDMA based cellular communication system
has been introduced. The authors in [47] introduced a Dynamic FFR (DFFR) scheme using
Interference Avoidance Request (IAR) mechanism for downlink ICI suppression in
OFDMA based cellular networks. Their proposed scheme relies on dynamic control of the
Base Stations (BSs) transmitted power based on exchange of IAR messages between them.
They compared the performance of their proposed scheme with reference frequency reuse
schemes. The results show that their proposed DFFR with IAR scheme outperformed the
performance of reference frequency reuse schemes in terms of cell-edge throughput and
total cell throughput. An overview of radio resource allocation and management issues in
relay-enhanced OFDMA-based networks is introduced in [48,49]. In [50], authors studied
the performance of a multi-hop relay cellular system. They proposed a novel dynamic
frequency resources allocation and reuse scheme which based on the number of relay
stations, relay stations location distribution, traffic load and interference. The results
showed that with the appropriate relay station placement their proposed scheme improved
system capacity and spectral efficiency compared to that of existing frequency allocation
and reuse schemes used in fixed relay networks. In [51–53], the authors proposed ICIC
schemes for relay based cellular mobile networks. In [26], the authors introduced a self-
organized resource allocation scheme for Relay-Assisted Cellular Networks (RACN). They
compared the performance of their proposed scheme (with and without relays) with that of
936 A. S. Mohamed et al.
123
frequency reuse-1, frequency reuse-3 and SFR scheme. The comparison showed that their
proposed self-organized resources allocation scheme with relays outperformed all other
reference resource allocation schemes by providing higher SINR values for a large pro-
portion of cell-edge users without affecting the overall system performance.
In this paper, we present a SODRA-FFR scheme which dynamically allocates frequency
resources to cell inner and outer regions in relay based LTE-A networks. In this scheme we
partitioned the cell into inner region and outer region and then calculate the total cell
throughput and fairness index for successive values of the inner region radius and then
select the optimal inner region radius and the optimal frequency resources allocation
between these regions with main target to improve cell-edge performance and maximize
fairness among UEs. The performance of the proposed SODRA-FFR scheme without and
with relays is evaluated using MATLAB simulations and compared with different com-
binations of resource allocation to cell inner and outer regions as well as with other
frequency reused schemes (i.e., frequency reuse-1and frequency reuse-3). The performance
indicators used for comparison are cell throughput, SINR distribution and fairness
indicator.
The remainder of this paper is organized as follows: the system model of a multi-cell
OFDMA based LTE-A cellular mobile network is described in Sect. 2. Section 3presents
overview of resource allocation schemes that are related to our work. Details of the
proposed SODRA-FFR scheme are presented in Sect. 4. Simulation results are discussed in
Sect. 5, followed by conclusions in Sect. 6.
2 System Model
The network model considered in this paper is a tow-hop downlink cellular OFDMA layout
consisting of K-eNBs, where K¼0;1;2;...;k;...;18
fg
is the set of indices of the 19
eNBs in the model, a number of cell-edge Relay Stations (RSs), where R={1, 2, 3} is the
set on indices of the 3 RSs in the model as shown in Fig. 1. The reference cell of our
interest is cell 0 for which interference will be considered from all other eNBs and RSs
transmitting in the same Transmission Time Interval (TTI) as eNB and RSs in the reference
cell as shown in Fig. 1. We also considered a number of UEs Uthat are randomly
distributed through the layout, where U={1, 2, …,u,…,U} is the set of indices of UEs.
For performance analysis of the proposed system model, it is important to accurately model
the effects of the radio propagation channel on the received signal, as these effects are very
often among the majority sources of system performance degradation. The propagation
model considered in this paper is Cost 231-Hata model, the path loss of user uat distance
d
u
from the serving eNB or RS can be written as [54,55]:
PLdB du
ðÞ¼46:3þ33:9 log f13:82 log hBah
m
ðÞþ44:96:55 log hB
½log duþCm
ð1Þ
where fis the carrier frequency in MHz, duis the distance between UE and the serving
eNB in km, hmis the UE antenna height above the ground level in meters and hBis the eNB
antenna height above the ground level in meters. The parameter C
m
is 0 dB for medium-
sized cities, and 3 dB for metropolitan areas. The parameter ah
m
ðÞis the UE antenna height
correction factor, for rural or suburban environments a(h
m
) is given by:
ah
m
ðÞ¼1:1 log f0:7ðÞhmð1:56 log f0:8Þð2Þ
Self-organized Dynamic FFR Resource Allocation Scheme for…937
123
In 3GPP LTE standard, the available radio frequency spectrum is partitioned into J
Resource Blocks (RBs) where each RB consists of 12 orthogonal subcarriers occupying a
total bandwidth of 180 kHz. Scheduling is performed by eNBs every 1 ms in order to
allocate the RBs to all UEs within the network; one or more RB can be allocated to a UE at
a time. The interference to UE within the reference cell coming from all other eNBs and
RSs transmitting in the same TTI as the eNB and RSs in the reference cell, the SINR of the
uth UE allocated to the jth subchannel in a cell serving by the kth base station is given by:
SINR j
u;k¼Pj
u;knj
u;k
N0DfþPm6¼kPj
u;mnj
u;m
ð3Þ
where Pj
u;kis the transmitting power allocated by kth base station to the jth subchannel to
serve the uth UE in the reference cell, Pj
u;mis the transmitting power allocated by mth
interfering base station to the jth subchannel to serve the uth UE in the interfering cell, N
0
is the power spectrum density of Additive White Gaussian Noise (AWGN), Dfis the
available bandwidth allocated to the uth UE, nj
u;kis the random channel gain in subchannel
jth between uth UE and the kth base station and n
u,m
j
is the random channel gain in
subchannel jth between uth UE and mth interfering base station, n
u,k
j
and n
u,m
j
can be given
as follows:
nj
u;k¼10
PL j
u;kdu;k
ðÞ
10 Hu;j
2ð4Þ
nj
u;m¼10PL j
u;mdu;m
ðÞ
10 Hu;j
2ð5Þ
where du;kand d
u,m
are the distance between uth UE and the serving kth base station and
between uth UE and the mth interfering base station respectively and |H
u,j
|
2
is the fading
Fig. 1 System model under investigation
938 A. S. Mohamed et al.
123
coefficient. Using the Shannon’s theorem, the throughput of uth UE on the jth subchannel
is given by [56]:
Cj
u;k¼Dflog21þSINR j
u;k
e
! ð6Þ
where eis the gap of SNR which measures the SNR loss from the theoretical maximum
channel capacity, eis a constant and expressed as a function of target BER as follows:
e¼ln 5BERðÞ
1:5ð7Þ
The total throughput of user uth UE in the serving kth cell can be given as follows:
Cu;k¼X
j
lu;jCj
u;kð8Þ
where, lu;jindicates the assignment of jth subchannel to the uth UE in the kth cell and
given by:
lu;j¼1;jth channel is assigned to the uth UE
0;otherwise
ð9Þ
3 Overview of Resource Allocation Schemes in OFDMA-Based Mobile
Networks
In cellular mobile networks, frequency reuse techniques are used to improve both network
capacity and coverage. The main idea of frequency reuse is that the whole available radio
frequency spectrum is partitioned into several narrower sub-bands, each of which is
assigned once to a cell of each cluster in the network which consists of several neighboring
cells. The main elements that determine the frequency reuse are the reuse distance and
FRF. The reuse distance is the distance at which the radio frequency resources can be
reused in a mobile cellular network and FRF is the cluster size. One of the main objectives
of OFDMA based mobile cellular networks is to achieve higher spectral efficiency; this can
be achieved using universal frequency reuse (frequency reuse-1). In frequency reuse-1 the
available radio frequency spectrum is reused in each cell resulting in the worst CCI
scenario. On the other hand in frequency reuse-3, the available radio frequency spectrum is
partitioned into 3 equal sub-bands and each cell is given a sub-band which is orthogonal to
neighboring cells sub-bands. The frequency reuse-3 scheme obviously reduced the CCI at
the expense of system spectral efficiency. The frequency reuse-1 and frequency reuse-3
schemes are shown in Fig. 2a, b respectively.
FFR or Reuse Partitioning (RUP) is a static ICIC scheme which effectively mitigates
ICI by applying different reuse factors in different regions in each cell. In FFR scheme the
available radio frequency spectrum is divided into two groups, inner group with frequency
reuse-1 to serve Cell Center Users (CCUs) and outer group with higher frequency reuse to
serve Cell Edge Users (CEUs) so that effective reuse is greater than 1. Figure 2c shows the
basic FFR scheme. Considered that the available radio frequency spectrum is bwhich is
partitioned into inner and outer groups b
FR-1
and 3.b
FR-3
, respectively. The inner band b
FR-
1
is used with frequency reuse-1 and the outer band 3.b
FR-3
is used with frequency reuse-3.
Self-organized Dynamic FFR Resource Allocation Scheme for…939
123
In this case the available frequency spectrum in each cell will be (b
FR-1
?b
FR-3
) and the
effective reuse factor is given by b=bFR-1þbFR-3
ðÞwhich is always greater than 1. In
static FFR, no power adaptation mechanism is considered for regions with different reuse
factors. All transmissions in the system are applied with equal transmission power. In DL,
each eNB evenly distribute total power over the available sub-bands (inner and outer
bands) of its cell.
4 A Self-organized Dynamic Fractional Frequency Reuse Resource
Allocation Scheme in LTE-Advanced Relay Based Networks
In order to effectively improve the cell-edge performance of LTE-A networks in terms of
coverage extension and throughput, relays are used to achieve self-backhauling of radio
signals between eNBs and UEs. This manuscript proposes a novel Self-Organized
Dynamic Resource Allocation scheme using FFR (SODRA-FFR) which dynamically
allocates frequency resources to cell inner and outer regions in relay based LTE-A net-
works with main target to improve cell edge performance and maximize fairness among
UEs. In this scheme, the downlink frequency resources allocation for CCUs and CEUs
(bFR-1and bFR-3)and the outer regions frequency resources allocation between eNB and
RSs in each cell are dynamically allocated based on coordination between neighboring
eNBs and RSs through a message passing approach over LTE-X2 interfaces [57]. We
.−
β
−
−
(a)
Frequency Reuse-1
Cell 2
Cell 1
Cell 0
1
2
0
(b)
Frequency Reuse-3
(c)
Fractional Frequency Reuse (FFR)
Cell 2
Cell 0
Cell 1
Cell 2
Cell 1
Cell 0
Fig. 2 Resource allocation Schemes. aFrequency Reuse-1. bFrequency Reuse-3. cFractional Frequency
Reuse (FFR)
940 A. S. Mohamed et al.
123
considered that, users are randomly distributed through the network layout. In order to
classify users in each cell (CCU, CEU served by eNB and CEU served by RSs), we use
users’ wideband SINR measurements over reference signals to identify CEUs because
reference signals are relatively stable over time and give a good indication of the inter-
ference conditions that a user suffers from. Thus, if user’s wideband SINR is below a
given SINR threshold, the user is considered as a CEU belongs to either eNB or RSs;
otherwise, the user is considered as a CCU. The SINR threshold is a design parameter. The
proposed scheme in this manuscript is a distributed ICIC scheme which relies on one or
more central eNBs, which exchange information potentially with all other eNBs and RSs
in the network. The central eNBs thereby collect state information and distribute infor-
mation relevant for coordination to all eNBs and RSs in the network. Coordinated Multi-
Point transmission/reception (CoMP) as standardized in 3GPP LTE-A is an example [58].
The main idea of the proposed SODRA-FFR scheme is that, in each TTI, each UE
measures the downlink SINR on each RB based on the reference signals received from the
serving base station (eNB or RS) and then feedback the SINR measurement reports to the
serving base station through Channel Quality Indicator (CQI) messages. The eNBs and
RSs in the network will use the SINR measurement reports to classify the users into CCUs,
CEUs served by eNBs and CEUs served by RSs. In order to classify users in each cell we
define two SINR thresholds, gTheNB and gThRS at which the classification based on the
following criteria:
Where SINR
u,k-eNB
j
is the downlink SINR of the uth UE allocated to the jth subchannel
in a cell serving by the kth eNB and SINR j
u;i-RS is the downlink SINR of the uth UE
allocated to the jth subchannel in a cell serving by the ith RS. After the classification
process each eNB and RS then counts the total number of CCUs, CEUs and total number of
CEUs served by RS respectively and then sends these numbers to the central eNB. The
central eNB counts the total number of CCUs (N
CCU-Total
), CEUs (N
CEU-Total
) and total
number of CEUs served by ith RSs (N
CEU-RSs,i
) which is a part of NCEUTotal as follows:
NCEU-Total ¼X
K
k¼1
NCEU;kð10Þ
NCCU-Total ¼X
K
k¼1
NCCU;kð11Þ
NCEU-RSs;i¼X
K
k¼1
NCEU;i;kð12Þ
where
Self-organized Dynamic FFR Resource Allocation Scheme for…941
123
N
CEU,k
: is the total number of CEUs served by the kth eNB, N
CCU,k
: is the total number
of CCUs served by the kth eNB, NCEU;i;k: is the total number of CEUs served by the ith RS
in kth cell
The central eNB will use these values to calculate the optimal frequency resources
allocation ratio ato cell inner and outer regions as follows:
a¼NCEU-Total
NCCU-Total
¼bFR-3
bFR-1
¼bbFR-1
ðÞ=3ðÞ
bFR-1
ð13Þ
bFR1¼b
3:aþ1ð14Þ
bFR-3¼bbFR-1
3ð15Þ
The central eNB will send the frequency resources allocation ratio ato all other eNBs in
the network which will be used for optimal frequency resources allocation
(bFR1and bFR3) for CCUs and CEUs in the next TTI, the flowchart of the SODRA-FFR
scheme is given in Fig. 3.
For dynamic frequency resources allocation in the outer region between eNB and RSs in
each cell, the central eNB calculates the outer region resource allocation ratio a
Ri
which is
given by:
aRi ¼NCEU-RSs;i
NCEU-Total
ð16Þ
The central eNB will send the ratio a
Ri
to the eNBs and their associated ith RSs which
will be used for dynamic resource allocation in the outer regions as follows:
bRi-k¼aRixBFR-3ð17Þ
bCEU-k¼bFR-3X
3
i¼1
BRi ð18Þ
where b
Ri-k
is the resources allocated to CEUs served by ith RS in kth cell and b
CEU-k
is the
resources allocated to CEUs served by the kth eNB. The SINR of the uth CEU allocated to
the jth subchannel in a cell serving by the ith RS in kth cell is given by:
SINR j
CEU-u;i;k¼Pj
CEU-U;i;knj
CEU-U;i;k
N0DfþPm6¼kPj
CEU-u;i;mnj
CEU-u;i;m
ð19Þ
where P
CEU-U,i,k
j
is the downlink power allocation of the uth CEU allocated to the jth
subchannel in a cell serving by the ith RS in kth cell which is equal to:
Pj
CEU-U;i;k¼PRS;i;k
bRi-k
ð20Þ
where P
RS,i,k
is the total power used by ith RS in kth cell for transmission of downlink
streams. Figures 4and 5show the dynamic frequency resources allocation in outer region
between eNB and RSs in the reference cell. For performance evaluation of the proposed
SODRA-FFR scheme, an important performance evaluation indicator known as the Jain’s
Fairness Index (FI) is used [59,60], the FI is given by:
942 A. S. Mohamed et al.
123
Fig. 3 Flowchart of self-organized dynamic FFR resource allocation scheme
Self-organized Dynamic FFR Resource Allocation Scheme for…943
123
Fig. 4 Flowchart of reference cell outer region dynamic frequency resources allocation between eNB and
RSs
944 A. S. Mohamed et al.
123
FI ¼PU
u¼1Cu;k
2
UPU
u¼1ðCu;kÞ2ð21Þ
where Cu;kis the throughput of the uth UE in the kth serving cell and given in Eq. (8).
The FI is in the range between 0 and 1. The FI equals 1 (ideal value) when the allocated
resources are equally distributed between UEs in a given cell and it decreases when the
allocated resources are not equally distributed between UEs in a given cell.
5 Simulation Results
In this section, the performance of the proposed SODRA-FFR scheme without and with
relays is evaluated using MATLAB simulations and compared with that of different
combinations of frequency resources allocation to cell inner and outer regions given in
Table 1as well as with that of other frequency reused schemes (i.e., frequency reuse-1and
frequency reuse-3). The performance indicators used for comparison are cell throughput,
SINR distribution and fairness. The simulation parameters and their values are given in
Table 2. Figure 6presents the frequency resources allocated to inner and outer regions
(bFR-1&bFR-3)of the proposed SODRA-FFR versus inner region radius. From the figure we
can observe that the proposed scheme tracks the variation of the distribution of CCUs and
−−
−
Fig. 5 Reference cell outer region dynamic frequency resources allocation between eNB and RSs
Table 1 Different fixed resource allocations for inner and outer regions
RA_Index Outer region
RBs (bFR-3)
Inner region
RBs (bFR-1)
Effective
reuse factor
1 1 22 1.087
2 2 19 1.19
3 3 16 1.31
4 4 13 1.47
5 5 10 1.66
6 6 7 1.92
7 7 4 2.27
8 8 1 2.78
Self-organized Dynamic FFR Resource Allocation Scheme for…945
123
Table 2 Simulation parameters and their values
Parameter Value
Channel bandwidth & carrier frequency 5 MHz & 2 GHz
Number of RBs 25
Location of UEs Randomly distributed on the cell surface
Pass loss model Cost 231-Hata model
eNB & RS transmit power 43 dBm & 30dBm
eNB antenna gain Omni directional (11 dBi)
eNB & RS & UE antenna heights 30 m & 12 m & 1.5 m
eNB Shadow fading standard deviation 8 dB
eNB & RS cable and connector losses 2.5 dB & 1 dB
eNB cell radius 1 km
RS cell radius 0.3 km
g
Th-RS
8.58 dB
RS antenna gain Omni directional (6 dBi)
RS Shadow fading standard deviation 6 dB
Number of users per layout & Cell load 350 & 100 %
UE antenna gain Omni directional (0 dBi)
Df&N
015 kHz & -174 dBm/Hz
Grid layout 19 cells & 3 RSs in each cell
Average number of UEs per cell 19
C_m& Target BER 0 dB & 10
-6
Fig. 6 SODRA-FFR inner and outer regions frequency resources versus inner region radius
946 A. S. Mohamed et al.
123
Fig. 7 Fairness index and total cell throughput of the proposed SODRA-FFR versus inner region radius
Fig. 8 SINR CDF of all UEs: proposed SODRA-FFR scheme without and with RSs, inner region radius
0.5 km
Self-organized Dynamic FFR Resource Allocation Scheme for…947
123
CEUs through the network layout with the change of the inner region radius and
dynamically allocated frequency resources to inner and outer regions based on coordina-
tion between neighboring eNBs. Figure 7shows how the FI and total cell throughput of the
proposed SODRA-FFR scheme change with the increase of inner region radius. As it is
seen in this figure, the FI increases as inner region radius increases and reached its max-
imum value 0.661 at inner region radius of 0.5 km which is selected as the optimal inner
region radius. According to Eqs. (1,3,4and 5), the optimal inner region radius of 0.5 km
is corresponding to gTh-eNB of 5.98 dB. From Figs. 6and 7we can also observe that, as the
inner region radius increases after the optimal point (0.5 km) the frequency resources (b
FR-3
)
allocated to CEUs in the outer region decrease and sthe frequency resources (b
FR-1
) allocated
to CCUs in the inner region increases and in this case the FI decreases and the proposed
scheme tended to be a frequency reuse-1 scheme with the lowest FI value of 0.47 at inner
region radius of 1 km. Figures 8and 9show the SINR distribution performance of the
proposed SODRA-FFR scheme without and with RSs for all UEs and CEUs, respectively.
From these figures we can observe that, increasing the number of RSs improve the SINR
performance of the proposed SODRA-FFR scheme for all UEs and CEUs.
The SINR distribution for all UEs in the cell is plotted in Fig. 10 for frequency reuse-1,
frequency reuse-3 and proposed SODRA-FFR scheme without and with 3RSs. From the
figure we can observe that, the proposed SODRA-FFR scheme with 3RSs outperforms all
other reference frequency reused schemes in terms of SINR distribution for all UES.
Fig. 9 SINR CDF of CEUs: proposed SODRA-FFR scheme without and with RSs, inner region radius
0.5 km
948 A. S. Mohamed et al.
123
The SINR distribution for CEUs is plotted in Fig. 11 for frequency reuse-1, frequency
reuse-3 and proposed SODRA-FFR scheme without and with 3RSs. From the figure we can
observe that, the proposed SODRA-FFR scheme with 3RSs achieves better SINR distri-
bution for CEUs as compared to that of reference frequency reused schemes. The results
also show that, frequency reuse-3 scheme achieves a significant reduction in interference
compared to frequency reuse-1 and the proposed SODRA-FFR without RSs.
In Fig. 12, we compare the cell-edge throughput and total cell throughput of the pro-
posed SODRA-FFR scheme (without and with 3RSs) with that of the reference resources
allocation schemes. From the figure we can observe that, the proposed SODRA-FFR
scheme with 3RSs and frequency reuse-3 scheme outperform all other resource allocation
schemes in terms of cell-edge throughput (2.18 Mbps and 1.6 Mbps respectively) due to
their high SINR distributions as shown in Fig. 11. The results also show that the proposed
SODRA-FFR scheme with 3RSs achieved a total cell throughput value of 7.46 Mbps which
is higher than that of frequency reuse-1, frequency reuse-3 and the proposed SODRA-FFR
without RSs. The results also show that, the proposed SODRA-FFR scheme without RSs
which has the same frequency resources allocated to inner and outer regions as the RA-7
FFR as shown in Fig. 6achieved higher cell-edge throughput and total cell throughput
compared to RA-7 FFR scheme due to dynamic allocation of frequency resources to cell
inner and outer regions based on the coordination between eNBs. The results also show
Fig. 10 Comparison of the SINR CDF of all UEs: frequency reuse-1, frequency reuse-3 and the proposed
SODRA-FFR scheme without and with 3RSs, inner region radius 0.5 km
Self-organized Dynamic FFR Resource Allocation Scheme for…949
123
Fig. 11 Comparison of the SINR CDF of cell edge UEs: frequency reuse-1, frequency reuse-3 and the
proposed SODRA-FFR scheme without and with 3RSs, inner region radius 0.5 km
Fig. 12 Cell-edge throughput and total cell throughput of different resources allocation schemes, inner
region radius 0.5 km
950 A. S. Mohamed et al.
123
that, for FFR scheme, as the resource allocation index (RA-Index) increases the cell-edge
throughput increases and the total cell throughput decreases where more frequency
resources (b
FR-3
) allocated to outer region and less frequency resources ðbFR-1Þallocated to
the inner region as given in Table 1.
Figure 13, introduces the FI of the proposed SODRA-FFR scheme (without and with
3RSs) compared to that of the reference resources allocation schemes. The results show
that, the proposed scheme (without and with 3RSs) achieved the highest FI compared to
that of all other resources allocation schemes. The results also show that, for FFR
scheme as the resource allocation index (RA-Index) increases the FI increases and the RA-
1 achieved FI closer to that of frequency reuse-1.
6 Conclusions
In this paper, we present a Self-Organized Dynamic FFR Resource Allocation
scheme (SODRA-FFR) for LTE-A relay based networks which dynamically allocates
frequency resources to cell inner and outer regions in relay based LTE-A networks. In this
scheme, the downlink frequency resources are dynamically allocated to CCUs and CEUs
and the outer region frequency resources are dynamically distributed between eNB and
RSs in each cell based on coordination between neighboring eNBs and RSs through a
message passing approach over LTE-X2 interfaces. In this scheme we partitioned each cell
in the network layout into inner region and outer region and calculate the total cell
Fig. 13 Fairness Index (FI) of different resources allocation schemes, inner region radius 0.5 km
Self-organized Dynamic FFR Resource Allocation Scheme for…951
123
throughput and fairness index for successive values of the inner region radius and then
select the optimal inner region radius and the optimal frequency resources allocation
between these regions with main target to improve cell-edge performance and maximize
fairness between UEs using MATLAB simulations.
The results show that the optimal inner region radius is 0.5 km at which the FI is
maximum and at this optimal inner region radius the optimal frequency resources are
bFR1=4, bFR3=7.
The performance of the proposed SODRA-FFR scheme (without and with relays) is
investigated using MATLAB simulations and compared with that of different combina-
tions of resource allocation to cell inner and outer regions as well as with that of other
frequency reused schemes (i.e., frequency reuse-1 and frequency reuse-3). The simulation
results show that as the number of RSs increases the proposed SODRA-FFR
scheme achieves high SINR distribution for CEUs and all UEs in the cell. The results also
show that the proposed SODRA-FFR with 3RSs outperforms frequency reuse-1 and fre-
quency reuse-3 schemes in terms of SINR distribution, cell-edge throughput, total cell
throughput and fairness performance.
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Ahmed S. Mohamed received the B.Sc. and M.Sc. degrees in Electronic Engineering from Faculty of
Electronic Engineering, Menoufia University, Menouf, Egypt in 2000 and 2007, respectively. Currently, he
is working as RF planning and optimization manager at Telecom Egypt, Cairo, Egypt. He is currently
working towards the Ph.D. degree in Communications Engineering from Faculty of Electronic Engineering,
Menoufia University. His research interests include wireless networks, HetNET, 3G, LTE, small cells, IBS,
and cooperative communication.
954 A. S. Mohamed et al.
123
Mohammed Abd-Elnaby received the B.S., M.S., and Ph.D. degrees
in electronic engineering from Menoufia University, Menouf, Egypt in
2000, 2004 and 2010, respectively. Currently, he is working as lecturer
at the Department of Electronics and Electrical Communication,
Faculty of Electronic Engineering, Menoufia University, Menouf,
Egypt. His research interests include wireless networks, wireless
resource management, MAC protocols, cognitive radio, and coopera-
tive communication.
Sami A. El-Dolil received the B. Sc. and M. Sc. degrees in electronic
engineering from Menoufia University, Menouf, Egypt, in 1977 and
1981, respectively. In 1986 he joined the Communication Research
Group at Southampton University, Southampton, England, as a
research student doing research on teletraffic analysis for mobile radio
communication. He received the Ph.D. degree from Menoufia
University, Menouf, Egypt, in 1989. He was a Post Doctor Research
Fellow at the Department of Electronics and Computer Science,
University of Southampton, 1991–1993. Since 2008 he is working as a
Professor at the Department of Electronics and Electrical Communi-
cation, Faculty of Electronic Engineering, Menoufia University,
Menouf, Egypt. His current research interests are in High-capacity
digital mobile system and multimedia networks.
Self-organized Dynamic FFR Resource Allocation Scheme for…955
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