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Hindawi Publishing CorporationEURASIP Journal on Wireless Communications and NetworkingVolume 2010, Article ID 162326, 8 pagesdoi:10.1155/2010/162326

Research ArticleEnergy EfficiencyOptimization of Cooperative CommunicationinWireless SensorNetworks

ShaoqingWang and JingnanNie

Department of Wireless Communication, Institute of Communications Engineering, PLA University of Science and Technology,Nanjing Jiangsu 210007, China

Correspondence should be addressed to Shaoqing Wang, [email protected]

Received 29 October 2009; Revised 8 March 2010; Accepted 25 April 2010

Academic Editor: Xinbing Wang

Copyright 2010 S. Wang and J. Nie. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In wireless sensor networks (WSNs), cooperative communication represents a potential candidate to combat the effects of channelfading by exploiting diversity gain achieved via cooperation among the relays nodes. However, for the energy-constrained WSN,to what extent cooperative communication can save energy consumption for a successful packet transmission is still unknown.Energy efficiency of cooperation and direct transmission schemes in WSN is studied and compared in this paper. The expressionsof energy efficiency of the two schemes are derived, respectively. The numerical results reveal that for the small distance separationbetween the source and destination nodes, the direct transmission scheme is more energy efficient than cooperation and the relaylocation, packet size, and modulation level have important effects on energy efficiency. At last, energy efficiency maximization forthe cooperative communication system is achieved by optimizing both the packet size and modulation level jointly.

1. Introduction

Wireless sensor networks (WSNs) are composed of nodestypically powered by batteries, for which replacement orrecharging is very difficult [1]. With finite energy, we canonly transmit a finite amount of information. Therefore,minimizing the energy consumption for data transmissionbecomes one of the most important design considerationsfor WSN. Unfortunately, the channel fading has a greateffect on the reliability of data transmission and energy

consumption in WSN. Cooperative diversity represents apotential candidate to combat the effects of channel fadingby exploiting diversity gain achieved via cooperation amongthe relays nodes [24].

Various cooperative schemes have been developed andproved to be highly effective in terms of throughput orcapacity compared with the noncooperative scheme [513].Multi-node cooperative schemes have been investigated in[57]. Distributed space-time coding for cooperative systemshas been proposed in [5, 6], where a number of nodestransmit the different columns of a space-time coding matrixsimultaneously to the destination. Distributed beamformingschemes have been also proposed in [7], which require all

cooperators to be synchronized and cophased such that thesignals from the cooperators can be combined constructivelyat the destination. Single-relay selective cooperative schemeshave been investigated recently in [810], where only oneout of a set of potential candidates is chosen to aid thecommunication process, and the relay selection can be basedon instantaneous channel gains. Compared with multinodecooperative schemes, the single-relay selective cooperativescheme is easy to implement and incur less cooperationoverhead since it requires neither distributed space-time

coding nor cooperative beamforming. Moreover, it canpotentially achieve the same diversity-multiplexing tradeoffas that of multinode cooperative schemes [9, 10]. Hence, thesingle-relay selective cooperative strategy is practically moreappealing.

Compared with the noncooperative scheme named as thedirect transmission (DT) scheme in this paper, the single-relay cooperative transmission (CT) scheme can mitigatethe required transmission energy for the successful datatransmission. However, a successful packet transmission inthe single-relay CT scheme involves two transmitting nodes,the source and the relay node, transmitting an identicaldata packet to the destination node via relaying way, which

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2 EURASIP Journal on Wireless Communications and Networking

might increase energy consumption. Therefore, comparedwith DT, to what extent the single-relay CT can save energyconsumption for a successful packet transmission in WSNis still unknown. For the energy-constrained WSN, it isdesired that the proper design of CT scheme can conductminimum energy consumption for the successful packet

transmission between the source and the destination. Fur-thermore, designing energy efficient single-relay CT schemessuitable for WSN is still an open problem.

Motivated by previous researches, in order to minimizethe energy consumption for the successful packet trans-mission in the single-relay cooperative system, the optimalincremental relaying (IR) cooperation strategy is investigatedin this paper. Energy efficiency is a fair and appropriatemetric to performance evaluation and comparison betweenthe DT and CT, which can be defined as a ratio of thenumber of packet bits transmitted successfully to energyconsumption. Specifically, the energy efficiency expressionsof DT and CT are firstly derived, respectively. Then, the

eff

ects of the locations of relay nodes, the packet size,and modulation level on energy efficiency are discusseddetailedly. At last, energy efficiency maximization for thesingle-relay cooperative communication system is achievedby optimizing both the packet size and modulation leveljointly, and the performance of the optimal IR cooperativescheme is compared with that of the traditional IR coopera-tive scheme and the DT scheme.

2. RelatedWork andPaperContributions

There is a large amount of previous works focusing on theenergy efficiency optimization problem of communicationin WSN. Energy efficiency based packet size optimizationin WSN was investigated firstly in [14]. Energy efficiencyof large-scale proactive and reactive WSN for applicationsinvolving data-centric and location-centric queries wasevaluated in [15]. In [16], the authors studied the jointoptimization problem of transmit power time and bit energyefficiency in CDMA WSN. Optimal transmission range forwireless sensor networks based on energy efficiency wasconducted in [17, 18]. However, all the aforementionedpapers focused on the energy efficiency problem of nonco-operative communication scheme in WSN. Different fromresearch of these works, energy efficiency of the multinodecooperative transmission exploiting distributed space-time

codes was studied in [1922], where cooperation was utilizedfor data transmission between clusters of nodes in WSN.Besides, several energy efficient transmission strategies forWSN were analyzed assuming the presence of powerfulmobile agents equipped with antenna arrays and complexprocessors in [23]. However, few attempts have been doneon the energy efficiency of the single-relay CT. In our work,we consider a single-relay CT which is more bandwidthefficient compared with multinode CT exploiting distributedspace-time codes. Moreover, it is easier to implement thanthe multinode CT exploiting distributed space-time codes,as the later requires synchronization between the spatiallyseparated relays performing the distributed space-time code.

Specially speaking, the CT scheme studied in this paperis different from the multihop relay transmission essentially.Due to the limited transmission ranges of nodes, the datapacket of the source node needs to be relayed to the sinknode via the multihop fashion, which is the final receivingnode for the data packet. In this paper, the data transmission

via each hop is named as the direct transmission (DT)which does not exploit the cooperative nodes. During theeach-hop transmission from the transmitting node to thereceiving node, due to the broadcast nature of the wirelessmedium, the neighbor node of the transmitting node mayoverhear the data packet. Then, the neighbor node can beexploited to retransmit the data packet to the receiving node,which is the so-called cooperative transmission. So, in CT,the receiving node can receive the two same data packets,with which cooperative diversity can be achieved. But, in themultihop relay transmission scheme, the receiving node canonly receive one data packet from the previous transmittingnode during the each-hop transmission.

Furthermore, our study is concentrated on the energyefficiency analysis and optimization of cooperative commu-nication in two-hop fashion. Essentially speaking, multihopcooperative communication is a cooperative routing prob-lem, which is not the solved issue in this paper. In future, ourwork will be generalized to multihop cooperative fashion.

We can summarize the contributions of our workas follows. The analysis approach of energy efficiency ofthe single-relay IR cooperative communication in WSN isproposed in this paper and expressions of energy efficiencyfor DT and CT are derived, respectively. The numericalresults reveal that for the small distance separation betweenthe source and the destination, DT is more energy efficientthan CT. Moreover, the effect of the locations of relaynodes on energy efficiency in cooperation communication isevaluated, which can provide guidelines for relay selectionalgorithms in the large-scale WSN. At last, the optimal IRcooperative scheme is conducted by optimizing both thepacket size and modulation level jointly. The results showthat energy efficiency of the optimal IR cooperative schemeoutperforms that of the traditional IR cooperative scheme.In summary, we provide important guidelines for WSNdesigners to decide when and how to apply the cooperativecommunication scheme.

The remainder of this paper is organized as follows.Section 3 introduces the system models and discusses thedifferent aspects of the two considered communication

architectures, namely direct and cooperative transmission.Energy efficiency expressions of DT and CT are derived,respectively, in Section 4. Some numerical results are givenand a discrete optimization algorithm for energy efficiencymaximization is proposed in Section 5. Finally, some conclu-sions are drawn in Section 6.

3. SystemModel

Consider three relevant nodes in WSN, represented, respec-tively, by S (source node), R (relay node), and D (destinationnode), and assume that S wants to send the packet to D, as

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EURASIP Journal on Wireless Communications and Networking 3

R

S

Phase 1 Phase 2

Phase 1D

Figure 1: A typical scenario model in WSN.

illustrated in Figure 1. In the DT scheme, S just transmitsthe packet to node D directly, thus, the energy should beconsumed for supporting the required SNR in node D forthe successful packet transmission.

In the incremental relaying CT scheme, we considera two-phase cooperation protocol. In the first phase, Stransmits a data packet to D, and due to the broadcast natureof the wireless medium, R can overhear this data packet. If Dreceives the packet in this phase correctly, then it sends backan acknowledgment (ACK) and R just idles. On the other

hand, if D cannot decode the received packet correctly, then itsends back a negative acknowledgment (NACK). In this case,if R was able to receive the data packet correctly in the firstphase, then it forwards it to D. Otherwise, this packet will bedropped.

Compared with DT, CT can mitigate the required trans-mission energy of S for the successful packet transmission.However, a successful packet transmission in CT involves twotransmitting nodes, S and R, transmitting an identical datapacket to D via relaying way, which might increase energyconsumption. Therefore, compared with DT, to what extentCT can save energy consumption for a successful packettransmission is still unknown. For the energy-constrained

WSN, it is desired that the proper design of CT scheme canconduct minimum energy consumption for the successfulpacket transmission between the source and the destination.

Next, the wireless channel and the packet error rate(PER) models of DT and CT are described. Consider thatthe wireless channel between any two nodes is subjectto flat Rayleigh fading and channel gains for differentlinks are assumed to be statistically mutually independentand unchanged during the time period of a data packet.Assuming that the transmit power is constant for all nodes,denoted by Pt, path loss exponent is represented by ,and the noise components are modeled as additional whiteGaussian noise (AWGN) with variance N0, we can obtain the

description of received SNR for a link by the probabilitydistribution function (PDF),

fij

=

1

i jexp

i j

i j= (sd), (rd), (sr)

, (1)

where (i j) denotes the different links and i j is the averageSNR and can be expressed by

i j =Pt

ri j

N0, (2)

where ri j denotes the distance of a link with nodes i and jbeing transmitter and receiver, respectively.

Assume that uncoded M-QAM is adapted with themodulation level b = log2Mbit/symbol, the closed-formexpression for the average symbol error rate (SER) of a linkis given by [24]

SERi j

2

1

2

b/21 3i j

2(2b 1) + 3i j

(b

2).(3)

So, the PER of a link can be obtained as

PERi j = 1

1 SERi jL/b

, (4)

where L is the length of the data packet.Apparently, the PER of DT equals to the PER of the S-D

link and can be written as

PERD = PERsd = 1 (1 SERsd)L/b . (5)

Having the PER of all the links given by ( 4), the PER ofCT can be evaluated by

PERC= PERsdPERsr + PERsd(1 PERsr)PERrd. (6)

Equation (6) shows that the successful packet transmis-sion from node S to node D can be carried out through thepath of S-D or S-R-D, and the corresponding PER might bereduced by Rs retransmission.

Noting that the entire data packet is composed of thepacket header, payload and trailer, energy efficiency of thesystem can be expressed by

= Lp(1 PER)

E, (7)

where Lp is the payload length of a data packet, PERdenotes the packet error rate of DT or CT, and E is energyconsumption of transporting a data packet with the DT orCT scheme. Therefore, energy efficiency represents theratio of the number of packet bits transmitted successfullyto energy consumption.

In the next section, we will evaluate energy efficiency ofDT and CT.

4. PerformanceAnalysis

In this section, we characterize the system performance interms of energy efficiency for the direct and cooperativescenarios to quantify the energy savings, if any, gained byapplying cooperative transmission.

Assume that the total energy consumption of the systemis composed of the power consumption of the poweramplifiers and all other circuit blocks of the nodes. Let denotes the loss factor of the power amplifier (0 < < 1)and Pct and Pcr represent the power consumption of circuitblocks of transmitter and receiver, respectively. Moreover, thesymbol rate Rs is assumed to be constant, and then, the bitrate is given byRs b.

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4.1. Direct Transmission. The total consumed energy oftransmitting one data packet with the DT scheme can beexpressed by

ED =

Pt

1 +

+ Pct + Pcr L

Rb. (8)

Substituting (5) and (8) into (7), energy effi

ciency of DTis given by

D =Lp

1 PERD

ED. (9)

4.2. Cooperative Transmission. Different from DT, the totalconsumed power for CT to transmit one packet is a discreterandom variable and can be statistically described as follows,

PCtotal =

Pt

1 +

+ Pct + 2Pcr, (1 PERsd),

Pt

1 +

+ Pct + 2Pcr, (PERsdPERsr),

2Pt

1 +

+ 2Pct + 3Pcr, (PERsd(1

PERsr)).(10)

In the first term of the above expression, when thepacket transmission over the S-D link is successful with theprobability (1 PERsd), the consumed power is composedof the consumed power in node S (Pt(1 + ) + Pct) and thereceiving power of the D and R 2Pcr. Similarly, (PERsdPERsr)denotes the failure probability of both the transmissions overthe S-D and the S-R links, and so the consumed power isstill (Pt(1 +) + Pct + 2Pcr). The last term corresponds to theevent indicating the Rs retransmission while the failure oftransmission is over the S-D link.

So the total consumed energy of transmitting one data

packet with CT is written as

EC=(1 PERsd)

Pt

1 +

+ Pct + 2Pcr

L

Rb

+PERsdPERsr

Pt

1 +

+ Pct + 2Pcr

L

Rb

+PERsd(1 PERsr)

2Pt

1 +

+ 2Pct + 3Pcr

L

Rb.

(11)

Substituting (6) a nd (11)into(7), energy efficiency of CTis given by

C=Lp1 PERC

EC . (12)

We have derived energy efficiency expressions of DT andCT. So, the energy efficiency gain can be defined as the ratioof energy efficiency of CT to that of DT and can be obtainedas

G =C

D. (13)

When this ratio is smaller than one, this indicates thatDT is more energy efficient and that the extra energyconsumption induced by cooperation overweighs its gains indecreasing the packet error rate of the system.

5. Numerical Results

There are different system parameters such as the linkdistance, the packet size, and modulation level, whichhave important effects on energy efficiency. In order tounderstand the effect of each of these parameters, we willstudy the performance of CT and DT in Matlab 7.0.1 whenvarying one of these parameters and fixing the rest.

Without the loss of the generality, we assume that the S,R, and D nodes lie along a straight line and the R-D distanceis rrd = q rsd (0 < q < 1).

In all of the numerical simulations, the system parame-ters take the following values when considered fixed: = 4,

= 0.3, Pt = 0.001 w, Pct = 104 w, Pcr = 5 10

5 w,Rs = 10

4 symbol/s, N0 = 1013.5, q = 0.5, Lp = 40 bit,

L = 56 bit, and b = 4. The values of , , Pt, Pct, and Pcrare taken from the specifications of Mica2 motes [25].

5.1. Effects of the S-D Distance and the Relay Locations onEnergy Efficiency. Firstly, we study the effects of the S-Ddistance and the relay locations on energy efficiency.

Figure 2 depicts energy efficiency of CT and DT, whichare expressed by C and D, respectively, and Figure 3depicts the energy efficiency gain for different relay locations,respectively. At S-D distances below 80 m, DT is moreenergy efficient than CT. This is because the extra energyconsumption of the relay node induced by cooperationoutweighs its gain in decreasing the packet error rate ofthe system. However, at S-D distances above 80 m, CT ismore energy efficient than DT as shown in Figures 2 and 3.Because the PER of DT deteriorates more seriously as the S-D distance increases endlessly. However, due to the benefit ofcooperation, the PER of CT can keep much lower than that

of DT. The analytical and numerical results reveal a distancethreshold behavior that separates regions where DT is betterfrom regions where CT prevails.

Moreover, when q equals 0.5, which means that the S-Rdistance equals the R-D distance, the energy efficiency gainis best among all of relay locations as shown in Figure 3.When the S-D distance is below 80 m, the relay locationhardly affects energy efficiency gain. The effect of relaylocations on the energy efficiency can provide guidelines forrelay selection algorithms in the large-scale wireless sensornetworks.

5.2. Effects of the Packet Size and Modulation Level on

Energy Efficiency. Secondly, the effects of the packet sizeand modulation level on energy efficiency are discusseddetailedly.

Based on the theoretical analysis in Sections 3 and4, Figure 4 shows the joint effects of the packet size andmodulation level on energy efficiency of CT at rsd = 140. Itcan be seen that the energy efficiency plane is smooth, whichindicates a good match between the local maximum and theglobal maximum of energy efficiency. We have conductedextensive simulation for the DT system and found thatthe energy efficiency plane of it is also smooth. So, energyefficiency can be maximized by optimizing the packet sizeand modulation level jointly.

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0

0.5

1

1.5

2

20 50 80 110 140 170 200

C, q = 0.1

C, q = 0.3C, q = 0.5

C, q = 0.7

C, q = 0.9D

107

Energyefficiency(bit/J)

The distance of S-D link (m)

Figure 2: Energy efficiency versus the S-D distance for differentrelay locations.

101

100

101

102

20 50 80 110 140 170 200

q = 0.1

q = 0.3

q = 0.5

q = 0.7

q = 0.9

Energyefficie

ncygain


Figure 3: Energy efficiency gain versus the S-D distance fordifferent relay locations.

5.3. Discrete Optimization Algorithm for Energy EfficiencyMaximization. As discussed in Section 5.2, energy efficiencyclearly depends on two important parameters: the packetlength L and the modulation level b. As we know, a smallpacket length indicates that the packet transmission is notsusceptible to errors but at the cost of a large packet overhead.A large L implies that the packet is more susceptible to errors,which may decrease energy efficiency. As for the modulation

320

5

10

64

96

128

160

192 2

4

6

8

b

L

106

Energyefficiency(bit/J)

Figure 4: Energy efficiency versus the packet size and modulationlevel for the cooperation scenario (rsd = 140).

level b, a packet with a low modulation level is more robustbut may result in inefficient use of the channel and energy.On the other hand, a packet with a high modulation levelis more liable to error but carries more information persymbol. Therefore, the joint optimal L and b are desired soas to maximize energy efficiency. Noting that both the packetsize L and modulation level b are discrete, we propose atwo-dimensional discrete optimization algorithm to find themaximum of energy efficiency for the CT and DT systems byoptimizing both L and b jointly.

Let (L, b) represents energy efficiency with a packetlength L and a modulation level b and denotes the optimalenergy efficiency. Assume the minimum of L equals 32 bits,the incremental step value of L equals 1 byte (8 bits), andthe maximum value ofb equals 8. The discrete optimizationalgorithm is described as shown in Algorithm 1.

In the optimization algorithm, we start searching theoptimal packet size Lopt with a fixed b = 2, and foreach incremental b, we compute the maximum of energyefficiency by optimizing L. The whole process will terminatewhen energy efficiency begins to fall. This is based on theobservation that the local energy efficiency and the globalenergy efficiency always match perfectly when b varies and Lis fixed or L varies and b is fixed as shown in Figure 4. It can

be seen that with discrete optimization algorithm, the jointoptimization ofL and b is decoupled so that the complexitycan be reduced dramatically.

Using the discrete optimization algorithm, the curves ofenergy efficiency for the optimal CT and DT systems, whichare expressed by Optimal C and Optimal D, respectively,are plotted in Figure 5. For comparison, the energy efficiencycurves for CT and DT systems with fixed L = 56 and b = 4are also given in Figure 5. The corresponding optimal valuesof packet size L and modulation level b are drawn in Figures6 and 7, respectively.

It can be seen from Figure 5 that the optimal CT schemeexhibits the best performance and energy efficiency of the

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Initialization: b = 2, k = 2; = 0;while (b < 9) %Performing condition of the algorithm

Lm = 32; %The minimum of packet size 32 bitsLt= Lm + 8; %Increasing the packet size with 8 bits

%Comparing energy efficiency for different L{while ((Lm, b) < (Lt, b))

Lm = Lt;Lt= Lt + 8; %Increasing the packet size with 8 bits

end while}

%Saving the temporary value of energy efficiencykbk = b;Lk = Lm;k = (Lk, bk);{if (k > )

= k ;b = bk ;L = Lk;

elseopt = ; %The optimal value of energy efficiencybopt = b

; %The optimal value of packet size

Lopt = L

; %The optimal value of modulation levelstop; %Terminating the whole loopend if}

b = b + 1; %Increasing the modulation level with 1k = k + 1; %Performing the next loop

end while

Algorithm 1

optimal DT scheme is much less than that of the optimalCT scheme, especially when the S-D distance becomes longerand longer. In addition, energy efficiency of the optimal CT

scheme is better than that of the traditional CT scheme withfixed L and b.Moreover, when the S-D distance is above 160 m, energy

efficiency of the optimal CT scheme equals that of thetraditional CT scheme with fixed L = 56 and b = 4. Because,at the S-D distances above 160, the optimal packet size andmodulation level for the optimal CT scheme are also 56 and4, respectively, as shown in Figures 6 and 7.

At last, specially speaking, the optimal cooperativecommunication scheme should use the large packet size andhigh modulation level when the S-D distance is shorter andadopt the small packet size and low modulation level whenthe S-D distance is longer, as shown in Figures 6 and 7.

6. Conclusions and FutureWork

In this paper, energy efficiency of the cooperative and directtransmission schemes in WSN is studied and compared. Thenumerical results reveal that for small distance separationbetween the source and destination, direct transmissionis more energy efficient than cooperation and, above thethreshold distance, cooperation gains can be achieved.Moreover, when the S-R distance equals the R-D distance,energy efficiency gain is the best among all of the differentrelay locations. This conclusion can provide guidelines forrelay selection algorithms in the large-scale wireless sensor

0

2

4

6

20 50 80 110 140 170 200

Optical C

C (L = 56, b = 4)

Optical D

D (L = 56, b = 4)

107

Energyefficiency(b

it/J)


Figure 5: Energy efficiency versus the S-D distance for optimal andnonoptimal scenarios.

0

100

200

300

400

500

20 80 140 200

Optical C

Optical D

Optimalpac

ketsize(bit)


Figure 6: Optimal packet size versus the S-D distance for coopera-tion and direct transmission scenarios.

networks. At last, a two-dimensional discrete optimizationalgorithm is proposed to find the maximum of energy effi-ciency for cooperative communication system by optimizingboth the packet size and modulation level jointly. Energyefficiency of the optimal cooperative scheme is better thanthat of the traditional cooperative scheme with fixed L andb. In summary, we provide important guidelines for WSNdesigners to decide when and how to apply the cooperativecommunication scheme.

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0

4

6

8

20 80 140 200

Optical C

Optical D

Optimalmodulationlevel


Figure 7: Optimal modulation level versus the S-D distance forcooperation and direct transmission scenarios.

We present the performance analysis of cooperative com-munication in two-hop fashion, which will be generalizedto multihop cooperative fashion. Moreover, the constanttransmit power is adopted at all the nodes in this paper. Infuture, the power control scheme can be integrated into ourresearch.

AcknowledgmentThe authors wish to thank the anonymous reviewers for theirvery helpful suggestions and comments.

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