Resource Allocation Method of Device-to-Device Communication

doi:10.4236/cn.2013.53B2062

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Communications and Network, 2013, 5, 338-343

http://dx.doi.org/10.4236/cn.2013.53B2062 Published Online September 2013 (http://www.scirp.org/journal/cn)

Resource Allocation Method of Device-to-Device

Communication

Wenji Feng, Yafeng Wang, Lei Yang

Wireless Theory & Technology lab (WT&T), Beijing University of Posts and Telecommunications, Beijing, China

Email: [email protected], wangyf@bupt.edu.cn, [email protected]

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 to avoid the inference

between D2D users and cellular users. If there is no restriction for D2D communication on using the whole uplink fre-

quency band, it will have a strong negative impact on cellular communication. In order to overcome this shortage, we

propose a resource allocation method that D2D users and cellular users use orthogonal frequency resources. This

method will effectively reduce the inference between both kinds of communication. However, an obvious disadvantage

of this method is no effective use of uplink resources. Based on this, we propose an optimized resource allocation

method that a specific cellular user will be chosen to reuse the RBs (Resource Block) of D2D users. These ideas will be

taken into system-level simulation, and from the results of simulation we can see that the optimized method has the

ability to improve overall syste m performance and limit inference for cell-edge users.

Keywords: Device-to-device Communication; LTE-Advanced System; Resource Allocation Method; up Link;

Cell-edge Users

1. Introduction

3GPP Long Term Evolution (LTE) technology has been

proved to have outstanding performance, especially in

the measures of spectral efficiency and the average

throughput, cell-edge and peak values in a cellular, fre-

quency reuse one network [1,2]. Hence, major efforts

have been spent on the development of LTE. Currently

the further evolution of such systems has been started

under the scope of LTE-Advanced [3-5].

The device-to-device communication (D2D) technol-

ogy, also known as proximity-based services (ProSe), is

introduced into LTE-Advanced system [6-7]. However,

D2D communication is sharing authorized frequency

band with cellular communication by the way of or-

thogonal method or multiplexing method. The introduc-

tion of D2D communication is to improve the throughput

of overall cellular system. It contributes to higher fre-

quency resource utilization as well. When D2D users

reuse cellular frequency resources, it is hard to avoid the

interference of other cellular users in cell. It may affect

the D2D user's communication quality to some extent. If

there are no restrictions for D2D communication on us-

ing the whole frequency band, it will have a strong n ega-

tive impact on cellular communication.

As mentioned above, appropriative resource allocation

methods of D2D communication may improve this situa-

tion. Because of frequency reusing with cellular commu-

nication, D2D communication should choose a better

resource allocation method to avoid inference against

each other. Hence, we hope to find out simulation sce-

narios of different resource allocation methods so that we

can choose an appropriative allocation method for D2D

communication.

This paper is organized as follows: Section 2 describes

the simulation platform. Section 3 shows different kinds

of D2D communication resource allocation methods, and

the performance will be analyzed in this section. Ac-

cording to section 3, we propose some optimization

method of D2D resource allocation method in section 4.

Finally concluding remarks are made in Section 5.

2. Simulation Platform

Assume that the D2D communication underlying LTE-

Advanced network only reuse uplink frequency resource.

The simulation platform consists of 7 eNB (21 sectors).

We distribute one pair of D2D UEs into one cell amount

to 21 pairs of D2D UEs. In our simulation platform, we

consider that there is one transmitter and one receiver in

a pair of D2D UEs, which are working only during up-

link slot. The distribution of eNB (evolved node B) and

D2D UEs is shown in Figure 1.

W. J. FENG ET AL. 339

-1000 -500 0500 1000

-800

-600

-400

-200

200

400

600

800

X(m)

Y(m)

D2DTx

D2DRx

Figure 1. Distribution of eNB and D2D.

The radius of each cell is 500 m. The distance be-

tween transmitter and receiver is 10 m to 20 m. D2D

communication reuses uplink resources of LTE-Ad-

vanced, which contains 46 RB. The transmission power

[8,9] of D2D transmitter is 20 dBm. The system band-

width is 10 MHz and the carrier frequency is 2 GHz. We

distribute 210 cellular UEs into overall system so that

there are 8 to 12 cellular UEs in each cell. The per-ma-

nent 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 [10], where it can be further categorized as

Line-of-sigh t (LOS) and Non-line-of-sight (NLOS).

LOS:

10 10

16.9log ([])46.820log ([]/5.0)

PLd mfGHz

(1)

NLOS:

10 10

40log ([])30log ([])49

PLd kmfMHz  (2)

The probability of LOS is as follow:

=exp((4) /3),460

0, 60

LOS

Pdd





 







，

(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 1.

3. Resource Allocation Method

3.1. Resource Allocation Method of D2D

In order to analysis the performance of different methods

of D2D resource allocation, first of all we assume Case

Basic, which is a LTE-Advanced uplink network without

D2D communication. In this simulation scenario, we set

D2D transmission power to fixed 20 dBm, and the MCS

will be the highest one. On this basis, we propose another

3 cases of D2D resource allocation method, which are

described below:

a) Case Basic:

This case is LTE-Advanced uplink system without

D2D communication.

b) Case All_RB_Reuse:

As Figure 2 shows, D2D communication reuses all

uplink frequency resource with cellular system.

c) Case 10_RB_Reuse:

As Figure 3 shows, D2D communication reuses 10

RB of cellular uplink frequency resource. Cellular UEs

still use all uplink frequency resource.

d) Case 10_RB_Sep:

As Figure 4 shows, D2D communication uses 10 RB

of uplink frequency resources. Cellular UEs only use

another 36 RB of uplink frequency resource. It means

that the RB of D2D and cellular is orthogonal.

Table 1. List of simulation parameters.

Parameters Value

Number of eNB 7 eNB (21 sectors)

Radius of cell 500 m

Distance of D2D

communication 10 m to 20m

System resources Uplink

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 12 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

RB 1 to 46

Cellular and D2D

Figure 2. Caes All_RB_Reuse.

RB 1 to 36 RB 37 to 46

Cellular

D2D

Figure 3. Case 10_RB_Reuse.

RB 1 to 36 RB 37 to 46

Cellular

D2D

Figure 4. Case 10_RB_Sep.

W. J. FENG ET AL.

340

3.2. Performance Analysis

We compare the simulation results of previous 4 cases

including average throughput of eNB, throughput of

cell-edge users, throughput of D2D communication,

throughput of overall system and BLER (Block Error

Rate) of D2D communication. Figure 5 illustrates the

simulation results of 4 cases.

From Figure 5, we recognize that if D2D communica-

tion reuses all resource with cellular communication, the

throughput of overall system gets a very large increase.

However, on the other hand, D2D communication brings

a lot of interference against cellular communication so

that cell-edge users almost unable to transmit data cor-

rectly. At the same time, because of interference from

D2D communication, the throughput of cell centre users

drop sharply. Therefore, if there are no restrictions for

D2D communication on using the whole frequency band,

it will have a strong negative impact on cellular commu-

nication [11,12], which is not appropriate in the practical

communication system.

In the view of this, D2D communication only use part

of uplink frequency resource. In Case 10_RB_Reuse,

D2D communication only reuses 10 RB with cellular

system, and the all 46 RB is still used by cellular. In this

simulation case, comparing with Case All_RB_Reuse,

cellular system throughput gets a large increase, but the

throughput of cell-edge UEs is still very low so that cell-

edge users cannot communicate normally.

At the same time, we consider Case 10_RB_Sep,

which D2D commun icatio n uses 10 RB of cellular up link

frequency resource, and cellular UEs only use the other

36 RB of uplink frequency resource. From the results of

simulation, the performance of Case 10_RB_Sep is the

most equilibrium. What’s more, comparing with Case

Basic the throughpu t gets a lot of gain, and the BLER of

D2D is the lowest.

AverageThroughputofeNB

5887.64

1281.07

4680.12 4607.12

1000

2000

3000

4000

5000

6000

7000

BasicAll_RB_Reuse10_RB_Reuse10_RB_Sep

Throughput(kbps)

ThroughputofCell‐edgeUEs

259.01

0.09 4.42

206.67

100

150

200

250

300

BasicAll_RB_Reuse 10_RB_Reuse10_RB_Sep

Throughput(kbps)

ThroughputofD2D

8863.94

2350.36 2460.53

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

BasicAll_RB_Reuse10_RB_Reuse10_RB_Sep

Throughput(kbps)

Thro ughputofoveral lsystem

5887.64

10145.01

7030.48 7067.65

2000

4000

6000

8000

10000

12000

BasicAll_RB_Reuse 10_RB_Reuse10_RB_Sep

Throughput(kbps)

BLE RofD2DCommunication

34.92%

21.54% 17.87%

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

BasicAll_RB_Reuse 10_RB_Reuse10_RB_Sep

BLER

Figure 5. Results of four simulation cases.

W. J. FENG ET AL. 341

Figure 6 shows the cellular users SINR of 4 cases.

From Figure 6, we can still have the conclusions as

above. In Case All_RB_Reuse, the SINR of cellular UEs

is sharply decreased. It causes the exacerbation of overall

system. In Case 10_RB_Reuse, the effects of SINR are

more embodied at cell-edge users. The throughput of

cell-edge UEs is still very low so that cell-edge users

cannot communicate normally in this case. In Case

10_RB_Sep, the performance of SINR is almost the same

as Case Basic.

4. Optimization Scheme

4.1. Optimization Simulation Scenarios

We describe Case 10_RB_Sep in section 3, which has

the best performance of all 4 cases. However, in Case

10_RB_Sep, cellular communication gives up 10 RB to

assure the excellent performance of both cell-edge users

and D2D communication. The 10 RB, which are given

up by cellular communication and only used by D2D

communication, still negatively affect the performance of

overall system. Hence, we hope to find a possible way to

overcome the shortage. On the basis of Case 10_RB_Sep,

we consider choosing one cellular UE to reuse 10 RB

with D2D UEs. The simulation scenarios are described as

follow:

a) Case 10_RB_Sep:

This case is described in section 3.

b) Case Random_UE:

We choose a random cellular UE from current cell to

reuse 10 RB with D2D communication. The rest of cel-

lular users still use the other 36 RB.

c) Case Worst_UE:

We choose a cellular UE from current cell, which has

the slowest transmission rate currently, to reuse 10 RB

with D2D communication. The rest of cellular users still

use the other 36 RB.

d) Case Best_UE:

We choose a cellular UE from current cell, which has

the highest transmission rate currently, to reuse 10 RB

with D2D communication. The rest of cellular users still

use the other 36 RB.

4.2. Performance Analysis

We propose 3 cases to compare with Case 10_RB_Sep,

the results of performance are shown in Figure 7.

-40 -30 -20 -10010 20 30 40

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

SINR(dB)

C D F

Basic

AllRBResue

10RBResue

10RBSep

Figure 6. Cellular UEs SINR.

AverageThroughputofeNB

4607.12

4528.54

4795.63

4571.52

4350

4400

4450

4500

4550

4600

4650

4700

4750

4800

4850

10_RB_Sep Random_UEWorst_UEBest_UE

Throughput(kbps)

ThroughputofCell‐edgeUEs

206.67 187.18

3.97

221.21

100

150

200

250

10_RB_Sep Random_UEWorst_UEBest_UE

Throughput(kbps)

ThroughputofD2D

2576.15

2537.96

2450.88

2532.05

2380

2400

2420

2440

2460

2480

2500

2520

2540

2560

2580

2600

10_RB_Sep Random_UEWorst_UEBest_UE

Throughput(kbps)

Throughputofoverallsystem

7066.51

7246.51

7103.58

7183.27

6950

7000

7050

7100

7150

7200

7250

7300

10_RB_Sep Random_UEWorst_UEBest_UE

Throughput(kbps)

Figure 7. Results of optimized simulation cases.

W. J. FENG ET AL.

342

From Figure 7, we can draw the following conclu-

sions:

In Case Random_UE, the throughput of eNB, D2D

and overall system is all lower than Case 10_RB_Sep,

and the throughput of cell-edge users also lower than

Case 10_RB_Sep. So Case Random_UE is not an appro-

priate case to further optimize the performance.

In Case Worst_UE, th e throughput of eNB and over all

system increases a lot, but the throughput of D2D com-

munication fall sharply. And worst yet, the throughput of

cell-edge UEs is the lowest so that cell-edge users canno t

communicate normally. So Case Worst_UE is still not an

appropriate case to further optimize the performance.

In Case Best_UE, comparing with Case 10_RB_Sep,

the average throughput of eNB is reduced by 0.8%, and

the overall system throughput is reduced by 1.1%. At the

same time, the throughput o f cell-edge users is increased

by 7.1%. So in this case, we giv e up a little th roughp ut of

eNB and overall system, for the purpose of cell-edge

users’ throughput improvement. Case Best_UE is an ap-

propriate case to further optimize the performance.

Figure 8 shows the cellular UEs SINR of 4 optimized

cases.

From this figure, we can obviously see that the cellular

UEs of Case Worst_UE has the worst SINR. In Case

Best_UE, due to choosing the highest transmission rate

in current slot, the SINR is not as good as Case 10_

RB_Sep. But the improvement of cell-edge users’

throughput is what we want.

5. Conclusions

Based on the simulation and analysis above, we can rec-

ognize that after introducing D2D communication into

LTE-Advanced uplink system, the performance of over-

all system gains dramatically increase and it also im-

prove the system spectrum efficiency. At the same time,

when D2D communication reuses frequency resource

-40 -30 -20 -10010 2030

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

SINR(dB)

CDF

Last10Sep

OneBestMS

OneRanMS

OneWorstMS

Figure 8. Cellular UEs SINR of optimized cases.

with cellular users, cellular UEs will be interfered

strongly. It leads to the unable transmission of cell-edge

users. Therefore, proposing an appropriate resource allo-

cation method for D2D communication is a key factor to

improve the performance of the overall system. This pa-

per firstly consider different kinds of D2D communica-

tion resource allocation methods and choose the case that

D2D communication uses 10 RB of uplink frequency

resource and the cellular UEs only use another 36 RB of

uplink frequency resource, which has the best perform-

ance. On the basis of Case 10_RB_Sep, we consider

choosing one cellular UE, which has the highest trans-

mission rate in current slot, to reuse 10 RB with D2D

UEs. This optimized simulation case sacrifice a little

throughput of overall system in order to improve the

performance of cell-edge users. After verification and

analysis, Case Best_UE has the ability to improve overall

system performance and limit inference for cellular

communication, especially for cell-edge cellular users.

6. Acknowledgements

This paper is supported by National Key Technology

R&D Program of China under grant No.

2012ZX03003011.

REFERENCES

[1] H. Ekstrom, A. Furusk¨ar, J. Karlsson, M. Meyer, S.

Parkvall, J. Torsner and M. Wahlqvist, “Solutions for the

3G Long-term Evolution,” IEEE Communications Maga-

zine, Vol. 44, No. 3, 2006, pp. 2432-2455.

doi:10.1109/MCOM.2006.1607864

[2] ITU, “ITU-R; Recommendation M. 1645 Framework and

Overall Objectives of the Future Development of

IMT-2000 and Systems Beyond IMT-2000,” 2003.

[3] “Estimated Spectrum Bandwidth Requirements for the

Future Development of IMT-2000 and IMT-Advanced,”

ITU.

[4] D. C. Lee and Y. H. Kwon, “Performance Benefits of

Uplink Packet Relay Protocols for Cellular-Like Systems:

Quantitative Analysis,” IEEE Transactions Wireless

Communications, Vol. 5, No. 7, 2006, pp. 1569-1574.

doi:10.1109/TWC.2006.1673062

[5] S. Haykin, “Cognitive Radio: Brain-empowered Wireless

Communications,” IEEE Journal on Selected Areas in

Communications, Vol. 23, No. 2, 2005, pp. 201-220.

doi:10.1109/JSAC.2004.839380

[6] H.-Y. Hsieh and R. Sivakumar, “On Using Peer-to-peer

Communication in Cellular Wireless Data Networks,”

IEEE Transactions on Mobile Computing, Vol. 3, No. 1,

2004, pp. 57-72. doi:10.1109/TMC.2004.1261817

[7] P. J¨anis, Y. Chia-Hao, K. Doppler, C. Ribeiro, C. Wi-

jting, K. Hugl, O. Tirkkonen and V. Koivunen, “De-

vice-to-device Communication Underlaying Cellular

Communications Systems,” Submitted to: International

W. J. FENG ET AL. 343

Journal of Communications, Network and System Sci-

ences (IJCNS).

[8] V. Chandrasekhar and Z. Shen, “Optimal Uplink Power

Control in Twocell Systems with Rise-over-thermal Con-

straints,” IEEE communications letters, Vol. 12, No. 3,

2008, pp. 173-175. doi:10.1109/LCOMM.2008.071697

[9] C.-H. Yu, K. Doppler, C. Ribeiro and O. Tirkkonen,

“Power Optimization of Device-to-device Communica-

tion Underlaying Cellular Communication Systems,” in

Proc. of IEEE International Conference on Communica-

tions, June 2009.

[10] Rep. ITU-R M.2135, “Guidelines for Evaluation of Radio

Interface Technologies for IMT-Advanced,” Revision 1

to Document 5D/TEMP/90-E, 1st July 2008.

[11] C.-H. Yu, K. Doppler, C. B. Ribeiro and O. Tirkkonen,

“Resource Sharing Optimization for Device-to-Device

Communication Underlaying Cellular Networks. Wireless

Communications,” IEEE Transactions on. 8. 2011, pp.

2752-2763.

[12] M. Zulhasnine, C. C. Huang and A. Srinivasan, “Efficient

Resource Allocation for Device-to-Device Communica-

tion Underlaying Lte Network,” in Wireless and Mobile

Computing, Networking and Communications (WiMob),

2010 IEEE 6th International Conference on, 2010), pp.

368-75.