Communications and Network, 2013, 5, 333-337
http://dx.doi.org/10.4236/cn.2013.53B2061 Published Online September 2013 (http://www.scirp.org/journal/cn)
Performance of HARQ in Device-to-Device
Communication
Wenji Feng, Yafeng Wang, Lei Yang
Wireless Theory & Technology lab (WT&T), Beijing University of Posts and Telecommunications, Beijing, China
fwj10171017@sina.com, wangyf@bupt.edu.cn
Email: fwj10171017@sina.com, wangyf@bupt.edu.cn, yanglei5658@gmail.com
Received July, 2013
ABSTRACT
In this paper, we study D2D (Device-to-Device) communication underlying LTE-Advanced uplink system. Since D2D
communication reuses uplink resources with cellular communication in this scenario, it’s hard for D2D users to avoid
the interference from cellular users while cellular users are communication with eNB (evolved Node B). HARQ (Hy-
brid Automatic Repeat reQuest) is widely used in LTE-Advanced system in order to improve the accurate rate of cellu-
lar communication. Hence, we consider studying the integration of D2D with HARQ, so as to achieve the purpose of
improving the throughput of D2D communication and the performance of overall system. Synchronous HARQ is con-
sidered to introduce into D2D communicatio n procedures. What’s more, this idea will be taken into system-level simu-
lation. From the simulation results, we can see that the throughput of D2D communication gets a lot of gain and the
performance of overall system is improved as well. In addition, Synchronous HARQ technique can significantly de-
crease the BLER (Block Error Rate) of D2D communication, especially for which in a bad channel condition.
Keywords: D2D Communication; Synchronous HARQ; LTE-Advanced System; Uplink; BLER
1. Introduction
3GPP Long Term Evolution (LTE) technology has been
proved to have outstanding performance, especially in
the measures of spectral efficiency and throughput, cell
edge and peak values in a cellular, frequency reuse one
network [1,2]. Hence, major efforts have been spent on
the development of LTE. Currently the further evolu-tion
of such systems has been started under the scope of
IMT-Advanced [3-5].
The device-to-device communication (D2D) tech-
nol-ogy, also known as proximity-based services (ProSe),
is introduced to the LTE-Advanced system [6-7]. How-
ever, the D2D communication is sharing authorized fre-
quency band with cellular communication by the way of
or-thogonal method or multiplexing method. The intro-
duc-tion of D2D communication is to improve the
throughput of the whole cellular system. It contributes to
higher sys-tem spectrum efficiency as well. When D2D
users reuse cellular frequency resources, it is hard to
avoid the inter-ference from other cellular users in the
same cell. It may affect the performance of D2D com-
munication to some extent.
Hybrid automatic repeat request technology (HARQ)
is widely used in LTE-Advanced. HARQ can be divided
into synchronous HARQ and asynchronous HARQ in
accordance with the time of occurrence of the re-
trans-mission [8]. Synchronous HARQ means the trans-
mission of a HARQ process (retransmission) occurs at a
fixed moment. Asynchronous HARQ refers to a retrans-
mission that the HARQ process can occur at any time.
Synchro-nous HARQ is considered to introduce into
D2D com-munication procedures.
This paper focuses on studying the integration of D2D
with synchronous HARQ, and analysis the overall sys-
tem performance after joining the mechanism.
This paper is organized as follows: Section 2 describes
the simulation platform. Section 3 compares and analysis
the overall system performance with or without D2D
communication. Finally concluding remarks are made in
Section 4.
2. Procedures and Simulation Platform
We usually use HARQ to guarantee the accuracy of data
communication in LTE-Advanced system. Thus, we as
well consider adding HARQ into D2D communication to
guarantee the accuracy, and improve the performance of
overall system.
D2D communication reuses uplink resources of
LTE-Advanced in our simulation. It means that D2D
users only communicate during uplink slot. Figure 1
shows the procedures of the integration of D2D with
HARQ.
C
opyright © 2013 SciRes. CN
W. J. FENG ET AL.
334
Figure 1. Flow chart of synchronous HARQ for D2D.
Where CQI denotes Channel Quality Indicator, ACK
denotes Acknow ledgement, and NA CK denotes Negative
Acknowledgement.
Synchronous HARQ is introduced into simulation
platform. Different HARQ process ID is recorded by
system. In the same process, when the transmission oc-
curs, eNB merges SINR (Signal-to-Interference plus
Noise Ratio), and then determine whether to retransmit.
If there is no SINR data in the process, eNB can use cur-
rent SINR without merging. After deciding whether
needs to retransmit, there will be two branches:
1) Retransmit:
a) If system calls retransmission, the number of re-
transmission (ReTxNUM) will be recorded. The current
SINR, MCS and RB (Resource Block) ID will be re-
corded as well, which are merging data for next retrans-
mission.
b) If system calls retransmission, and current ReTx-
NUM is greater than Max-ReTxNUM, clear all data of
current process. System gives up transmitting this packet.
2) Non retransmit:
If the packet is successful transmitted, system clear all
data of current process.
The flow chart of synchronous HARQ for D2D simu-
lation platform is given in Figure 2.
The generation of retransmission probability in sys-
tem-level simulation is based on the mapping relation-
ship of SINR and BLER. Also the MCS and the size of
RB will affect this mapping relationship. In our HARQ
process the MCS is set to 28, and the size of RB is 10.
Table 1 shows the mapping relationship of SINR and
BLER.
The simulation platform consists of 7 base stations (21
sectors). The radius of each cell is 500 m. The distance
between transmitter and receiver is 10 m to 20 m. D2D
communication reuses UL resources of LTE-Advanced,
which contains 46 RB. The transmission power of D2D
transmitter is 20 dBm [9,10]. The system bandwidth is 10
MHz and the carrier frequency is 2 GHz. We distribute
210 cellular UEs into overall system so that there are 8 to
10 cellular UEs in each cell. Also we distribute one pair
Figure 2. Flow chart of synchronous HARQ for D2D.
of D2D UEs into one cell amount to 21 pairs of D2D
UEs. The permanent MCS of D2D communication is 28.
The path loss model and corresponding shadow fading
model of D2D communication are referred as model of
Urban Macro(UMa) in [11]where it can be further
categorized as Line-of-sight (LOS) and Non-line-of-sight
(NLOS).
Copyright © 2013 SciRes. CN
W. J. FENG ET AL. 335
Table 1. Mapping relationship of SINR and B LER.
MCS=28
SIZE OF RB=10
SINR BLER
17.2 1
17.4 0.96
17.6 0.864271
17.8 0.41018
18 0.103235
18.2 0.020804
18.4 0.00529
LOS:
10 10
16.9log ([])46.820log ([]/5.0)
c
PLd mfGHz (1)
NLOS:
10 10
40log([ ])30log([])49
c
PLd kmfMHz  (2)
The probability of LOS is as follow:
14
=exp((4) / 3),460
0, 60
LOS
d
Pdd
d
 
(3)
Where PL denotes the path loss, d is the distance be-
tween D2D users, fc is carrier frequency, and PLOS is the
probability of LOS.
The parameters of simulation are listed in Table 2.
3. Results and Analyses
Due to the introduction of synchronous HARQ for D2D
communication, the overall system throughput may have
been affected. We consider two different simulation sce-
narios:
a) Case BASIC:
This case will be the one that there is no HARQ in
D2D communication. This is a case used as the standard
of comparison system performance.
b) Case HARQ:
This case will be the one that joining HARQ into D2D
communication.
Both of these two simulation scenarios set the D2D
transmission power to 20 dBm. The scheduling mode of
D2D is the same and D2D communication reuse 10 RB
of cellular communication.
Figure 3 shows the results of two simulation cases.
As Figure 3 shows, the eNB throughput of both cases
is the same. It means that the integration of D2D with
HARQ does not affect the average throughput of eNB.
Since both cases’ throughput of cell-edge users are the
same as well, we can draw a conclusion that HARQ for
D2D communication does not affect the average
throughput either. Th e reasons are as follows:
In our simulation, the interference against eNB and
cellular UE is associated with D2D communication. As is
in both Case BASIC and Case HARQ, the interference
from D2D communication is just the same, th e results of
eNB throughput and cell edge user throughpu t turn ou t to
be the same.
Figure 3 also shows that the integration of D2D with
HARQ increases 5.6% D2D communication throughput
gain. What’s more, the overall system gets 1.9% throughput
gain. In view of this, after joining the HARQ into D2D
communication, the performance of D2D communication
and overall system has certain promotion. In addition,
BLER of case HARQ is 20% smaller than that of case
BASIC. Thus it can be seen that the accuracy of D2D
communication gets e nhanced after using HARQ.
Table 2. List of simulation parameters.
Parameters Value
Number of eNB 7 base stations (21 sectors)
Radius of cell 500 m
Distance of D2D
communication 10 m to 20 m
System resources Uplink/D2D and cellular
communication reuse 46 RB
Transmission power of D2D 20 dBm
System bandwidth 10 MHz
Carrier freque nc y 2 GHz
Number of cellular U E 210
Number of D2D pairs 21
Distribution 8 to 10 cellular UEs in each cell;
one pair of D2D-U E into one cell
MCS of D2D 28
Thermal noise density 174 dBm/Hz
Scheduling algorithm Proportional Fai r
AverageThroughputofeNB
4680.1173
(kbps)
4680.1173
(kbps)
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
BASIC HARQ
ThroughputofCelledgeUsers
4.452
(kbps )
4.452
kbps
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
BASIC HARQ
ThroughputofD2D
2350.3585
(kbps)
2481.864
(kbps)
2250
2300
2350
2400
2450
2500
BASIC HARQ
Throughputofoverallsystem
7030.4758
(kbps)
7161.9813
(kbps)
6950
7000
7050
7100
7150
7200
BASIC HARQ
BLER
0.2154
0.1715
0
0.05
0.1
0.15
0.2
0.25
BASIC HARQ
Figure 3. Results of two simulation case s.
Copyright © 2013 SciRes. CN
W. J. FENG ET AL.
336
Figure 4 refers to the throughput CDF curves of both
case BASIC and case HARQ.
In Figure 4, the performance of D2D communication
throughput, which enables HARQ technique, is better
than the one without HARQ technique. The D2D UEs,
whose throughput is less than 1000 kbps, of case HARQ
are obviously less than those of case BASIC. It shows
that HARQ technique can increase the throughput of
low-throughput D2D UEs.
Since all parameters in both Case BASIC and Case
HARQ are the same, we consider comparing the
throughput of each D2D UE from different cases. Figure
5 shows the throughput difference between Case BASIC
and Case HARQ.
From Figure 5 we can find that after using HARQ
about 50% D2D UEs do not get any throughput gain,
because we set the transmission power to 20 dBm, which
is the maximal power for UE. At the same time, about
40% D2D UEs increase 0 to 500 kbps throughput gain.
What’s more, 10% D2D UEs after using HARQ get 500
to 1200 kbps throughput gain. We can assume that if
lower transmission power is set for D2D UEs, which
means D2D communication get lower SINR in the same
channel conditio n, the gain from HARQ will be greater.
0500 1000 15002000 25003000
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Av er age R a t e ( kbps )
C D F
HARQ
BASIC
Figure 4. The throughput CDF curves.
0200 4006008001000 1200
0
0. 1
0. 2
0. 3
0. 4
0. 5
0. 6
0. 7
0. 8
0. 9
1
T he Differ ence Bet w een BASI C an d H AR Q ( kbps)
C D F
Figure 5. Throughput difference CDF curves.
4. Conclusions
In this paper we introduce synchronous HARQ into D2D
communication, and we have Case BASIC and Case
HARQ for simulation. Case BASIC is the case used as
the standard of comparison system performance. In the
simulation of Case HARQ, the throughput of eNB and
cellular communication is not affected. At the same time,
the throughput of D2D communication g ets a lot of gain.
Due to the gain of D2D communication, the throughput
of overall system gets gain as well. What’s more, HARQ
technique can improve the accurate rate of D2D commu-
nication, espe cially for which in a bad channel condition .
Hence, the introduction of HARQ for D2D communica-
tion is viable and necessary. For further study, we should
further optimize HARQ of D2D communication, so that
we can make the overall system gain maximization.
5. Acknowledgements
This paper is supported by National Key Technology
R&D Program of China under grant No.
2012ZX03003011.
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