research article a novel cooperative arq method for wireless...

Research ArticleA Novel Cooperative ARQ Method for Wireless Sensor Networks

Haiyong Wang,1,2 Geng Yang,2 Yiran Gu,1 Jian Xu,2 and Zhixin Sun1

1Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education,Nanjing University of Posts and Telecommunications, Nanjing 210003, China2School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Correspondence should be addressed to Haiyong Wang; [email protected]

Received 4 March 2015; Accepted 22 April 2015

Academic Editor: Fuwen Yang

Copyright © 2015 Haiyong Wang et al. 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, cooperative communication can combat the effects of channel fading by exploiting diversity gainachieved via cooperation communication among the relay nodes. A cooperative automatic retransmission request (ARQ) protocolbased on two-relay node selection was proposed in this paper. A novel discrete time Markov chain model in order to analyze thethroughput and energy efficiency was built, and system throughput and energy efficiency performance of proposed protocol andtraditional ARQ protocol were studied based on suchmodel.The numerical results reveal that the throughput and energy efficiencyof the proposed protocol could perform better when compared with the traditional ARQ protocol.

1. Introduction

Recently, wireless sensor networks (WSNs) are becoming afast-developing research area which is related to a wide rangeof applications, such as environment surveillance, military,and patient monitoring. WSNs are composed of a largeamount of sensor nodes which are typically powered by smallbatteries. Moreover, it is undesirable or impossible to replaceor recharge the sensor nodes inmany situations. Hence, thereis a great need for a reliable and energy-efficiency trans-mission strategy to improve the throughput and energy effi-ciency and prolong the network lifetime while satisfyingspecific quality of service requirements.

Cooperative communication among sensor nodes hasbeen considered to provide diversity in WSNs where fadingobviously affects point to point link, which can help combatfading effectively and enhance the reliability of the communi-cation significantly, so cooperative communication has beenstudied extensively. On the other hand, traditional automatic-retransmission-request protocol (TA) is an effective methodto improve transmission quality and combat poor channelscondition in a radio channel by retransmission of the datapacket which is incorrectly received in previous slot. Thus,cooperative ARQ (CARQ) mechanism, which combines the

cooperative communication and ARQ protocol, is receivingmore and more attention over the past decade or so [1–4].CARQ mechanism can increase the successful rate of datareceiving in destination node and combat channel attenua-tion simultaneously. As viewed from energy consumption,CARQ mechanism can achieve higher energy efficiencybecause itmakes thewireless communication between sourcenode and destination node more successful than that oftraditional ARQ protocol in data receiving rate and morereliable than normal cooperative communications.

In the past few years, cooperative communication hasestablished itself as an effective and energy conservingmethod for wireless sensor networks. One of the promisingtechniques is to use a relay to help source node communicatewith destination node, in which each node is equipped withonly one antenna. With the help of the relay node, a virtualMIMO antenna array system is formed, which can providespatial diversity withoutmultiple antennas per terminal node[5, 6].

The so-called single-relay cooperation is consideredwhere the data packet sent by the relay nodewas only receivedby the destination node [7, 8], but due to the broadcastnature of wireless channel, the signal can be received by thedestination node as well as the other relays. Departing from

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2015, Article ID 102326, 7 pageshttp://dx.doi.org/10.1155/2015/102326

2 International Journal of Distributed Sensor Networks

most previousworks in cooperative communication, an alter-native method to improve system throughput performance isapplying ARQ protocol at the data link layer [9, 10].

Energy efficiency of cooperative communication hasbeen studied in [11] which uses the model as hierarchicalcooperative clustering scheme and compared with cooper-ative multiple-input multiple-output (CMIMO) clusteringscheme and traditionalmultihop Single-Input-Single-Output(SISO) routing approach. Experimental results show increasein network lifetime and significant energy conservation isacquired. In two-dimensional WSNs [12], the energy effi-ciency of cooperative and noncooperative transmissions isstudied under the same end-to-end throughput and at acertain outage probability, the simulation results show thatthe energy efficiency advantage increases with the nodesdensity and distance.

Recently, cooperative communication has been proposedin connection with wireless sensor networks to improveenergy efficiency, throughput, and reliability in fading con-dition [13]. In [13], the authors propose a novel cooperativeARQ strategy where cooperative communication and ARQscheme is combined for clustering-based WSNs. Through ageneralized discrete time Markov chain model to analyze thethroughput and energy efficiency, simulation results showthat the proposed cooperative ARQ strategy is much betterthan the traditional ARQ scheme. The spectral efficiencyfor CARQ scheme in WSNs is investigated thoroughly butdoes not analyze the energy efficiency and throughput of theproposed system in [14].

The works all focus on no-relay or single-relay nodebetween source node and destination node with ARQ. Inthis paper we turn our attention to two-relay node network.Comparing with the volume of former research focusedon the single goal, such as energy conservation or spectralefficiency, we focus on the analysis of trade-offs in energy effi-ciency and throughput. Important questions include whereto place the relay nodes. Our aim here is to optimize energyconsumption per packet and throughput under differentnetwork geometry. This work bridges the current literaturegap by considering relay position, energy efficiency, andthroughput optimization.

The contribution of this paper is twofold.(1) First, we develop a new cooperative ARQ proto-

col of two relay nodes in wireless sensor network,called TRCAP (two-relay cooperative ARQprotocol),derived from two relays and CARQ that enhancessignificantly the network throughput and energyefficiency comparing to the traditional ARQprotocol.Furthermore, we have also introduced a retransmit-ting probabilities scheme, named RDFP (retransmitdata frame probabilities) based on the network envi-ronment and performance require.

(2) We propose a novel DTMC (discrete time Markovchain) model in order to analyze the throughputand energy efficiency of TRCAP in wireless sensornetworks.

The remainder of the paper is organized as follows. InSection 2, a description of the system model of two-relay

S

R1

R2

D

Figure 1: Simplified system model.

node and the corresponding model is introduced. The per-formance analysis of throughput and energy efficiency oftwo-relay node cooperative ARQ protocol is provided inSections 3 and 4, respectively. After that, in Section 5, thenumerical simulation is conducted. Finally, we summarizethe conclusions.

2. System Model and Operation Model

2.1. System Model. In this paper, we consider a typicalmodel of WSNs which consists of some sensor nodes anda sink node. When the network operates, some clusters areformed according to LEACH protocol, where CH is short forcluster head and CN is short for cluster node. There existtwo transmission phases: firstly, each CN transmits its dataframe to the corresponding CH according to some protocol;secondly, the CHS forwards the received data frame to thesink node according to a certain protocol.

That is to say, there are two different cooperative commu-nicationmodes: intracluster cooperative communication andintercluster cooperative communication, which means coop-erative communication between CN and CHS in the samecluster and cooperative between CHS and CHS or sink nodefrom different clusters, respectively. In this paper, we haveconsidered the Nakagami-m distribution, 𝑚 = 2 for line-of-sight (LOS) and𝑚 = 1 for non-line-of-sight (NLOS, Rayleighdistribution). Meanwhile we suppose that the channel is inlong-term quasi-static fading, which means that the channelremains constant for a long period and is correlated [15]. Thechannel gains of 𝑆-𝐷 channel, 𝑆-𝑅 channel, and 𝑅-𝐷 channelare supposed to be mutually independent and unchangedduring a data frame successful received period. Meanwhileall the channels are subjected to flat Rayleigh slow fadingand the channel does not change during the first period andretransmission period.The channel state information (CSI) iswell known by the corresponding receiver.

No matter in which cooperative communication mode,for simplicity, we consider that a two-relay node coopera-tive ARQ model is equivalent to a four-node system withone-source node (𝑆), two-relay nodes (𝑅

1, 𝑅2), and one-

destination node (𝐷), as shown in Figure 1. We considerthat the cooperative communication happens over a relaynetwork equipped with two relay nodes for assisting thecommunication between 𝑆 and𝐷.

International Journal of Distributed Sensor Networks 3

2.2. Operation Model. In this paper, we use space timeencoding (STC) that means a data frame is encoded by acode book. A set of codewords is formed behind themappingof every 𝑛 bit. 𝑆 and two relay nodes transmit the first, thesecond, and the third row of the code book, respectively. Thesystem persists until the data frame is correctly received by𝐷.

The two-relay cooperative ARQ protocol is as follows.First, 𝑆 sends an information packet to both two-relay node(𝑅1, 𝑅2) and 𝐷. The receiver sends an ACK (acknowledge-

ment) message or a NACK (negative acknowledgement)message indicating success or failure of decoding the packet,respectively; that is,𝑅

1and𝑅

2feed back to 𝑆, and𝐷 feeds back

to both 𝑆 and two-relay node (𝑅1, 𝑅2). All the ACK/NACK

feedback messages are assumed to be received error-free andwith no latency at the source node and two-relay node.

If the data frame is correctly decoded at the destination𝐷, 𝐷 feeds back an ACK message to both 𝑆 and two-relaynode (𝑅

1, 𝑅2), and the next data frame is transmitted in the

following time slot.If 𝐷 incorrectly decodes the received data frame, it

sends back a NACK message to both 𝑆 and two-relay node(𝑅1, 𝑅2), wherein 𝑅

1and 𝑅

2will retransmit the data frame

with probabilities 𝑝𝑅1

and 𝑝𝑅2

, respectively, that has beencorrectly decoded in the former time slot. We assumed that Sretransmits data frame simultaneously with probability 𝑝

𝑆.

If neither two-relay node (𝑅1, 𝑅2) nor 𝐷 is able to

correctly decode the data frame, then 𝑆 will retransmit thedata frame with probability 𝑝0

𝑆.

Suppose path loss exponent is denoted by 𝛼, noisecomponents are additive white Gaussian noise (AWGN) withvariance𝑁

0, path loss exponent is represented by 𝛼, and the

transmit power is represented by 𝑃𝑡which is constant for all

nodes. The average SNR (𝜎𝑖,𝑗) can be expressed by

𝜎𝑖𝑗=

𝑃𝑡(𝑟𝑖𝑗)

−𝛼

𝑁0

,(1)

where 𝑟𝑖𝑗represents the distance between node 𝑖 and node

𝑗, and the instantaneous received SNR 𝛾 has an exponentialdistribution by the probability distribution function (PDF):

𝑓 (𝛾) =

1

𝜎𝑖𝑗

exp(−𝛾

𝜎𝑖𝑗

) . (2)

Assume the modulation is 16-QAM and the closed-formformula is given for the average bit error rate (BER) by [16]

BER𝑖𝑗≈

3

2

(1 − √

𝜎𝑖𝑗

10 + 𝜎𝑖𝑗

) . (3)

Having the instantaneous received SNR 𝛾 and BER, wecan calculate the packet error rate (PER):

PER𝑖𝑗= 1 − (1 − BER

𝑖𝑗)

𝐿

, (4)

where 𝐿 is the length of a packet. If 𝑘-bits error correctioncapacity is utilized to a block code, the PER(𝛾) can beexpressed as [17]

PER (𝛾) = 1 −𝑘

∑

𝑙=0

(

𝐿

𝑙

) (BER (𝛾))𝑙 (1 − BER (𝛾))𝐿−1 . (5)

Considering the above PER(𝛾) formulations are toocomplicated for analysis, we adapt the following formulationas approximate expression in the following analysis ([18], (5)):

PER (𝛾) ={

{

{

1 if 0 < 𝛾 < 𝛾𝑡

𝑎 exp (−𝑔𝛾) if 𝛾 ≥ 𝛾𝑡,

(6)

where (𝑎, 𝑔, 𝛾𝑡) can be calculated by uncoded or convolu-

tionally coded 𝑀𝑛–𝑎𝑟𝑦 rectangular or square QAM modes;

meanwhile threshold 𝛾𝑡is constrained by

𝑎 exp (−𝑔𝛾𝑡) = 1. (7)

3. Throughput Analysis

In order to analyze the throughput and energy efficiency ofthe TRCAPprotocol, wemodel the transmission process witha DTMC illustrated in Figure 2.

There are four states in the DTMC, as follows.

State 𝑆0represents that both 𝐷 and two-relay node

(𝑅1, 𝑅2) do not correctly decode the received data

frame.State 𝑆

1represents that 𝐷 does not correctly decode

the received data frame. Only one of two-relay nodescorrectly decodes the received data frame.State 𝑆

2represents that 𝐷 does not correctly decode

the received data frame. Both 𝑅1and 𝑅

2correctly

decode the data frame.State 𝑆

3represents that 𝐷 correctly decodes the

received data frame.

The state transition of the DTMCmodel can be seen fromFigure 2. What needs to be pointed is that the relay node willstore the correctly received data frame until the data frame iscorrectly decoded by𝐷.

On state 𝑆0, 𝑆 retransmits data frame simultaneously with

probability 𝑝0𝑠.

On state 𝑆1, 𝑅1retransmits data frame with probability

𝑝𝑅1

if data frame has been correctly decoded in the formertime slot. The same is to 𝑅

2with probability 𝑝

𝑅2

. Meanwhile𝑆 retransmits data frame with probability 𝑝

𝑆.

On state 𝑆2, 𝑅1and 𝑅

2will retransmit the data frame

with probabilities 𝑝𝑅1

and 𝑝𝑅2

, respectively. Meanwhile 𝑆retransmits data frame with probability 𝑝

𝑆.

On state 𝑆3, 𝑆 transmits next data frame.

By solving the state transition equations listed below,where 𝑝

𝑆𝐷and 𝑝

𝑆𝑅1

, 𝑝𝑆𝑅2

are defined as the outage probabili-ties on each link and 𝑝

𝑖𝑗stands for the transition probability

of state 𝑆𝑖to state 𝑆

𝑗((𝑖, 𝑗 ∈ {0, 1, 2, 3})),

𝑝00= 𝑝0

𝑠𝑝𝑆𝐷𝑝𝑆𝑅1

𝑝𝑆𝑅2

,

𝑝01= 𝑝0

𝑠𝑝𝑆𝐷((1 − 𝑝

𝑆𝑅1

) 𝑝𝑆𝑅2

+ 𝑝𝑆𝑅1

(1 − 𝑝𝑆𝑅2

)) ,

𝑝02= 𝑝0

𝑠𝑝𝑆𝐷(1 − 𝑝

𝑆𝑅1

) (1 − 𝑝𝑆𝑅2

) ,

𝑝03= 1 − 𝑝

00− 𝑝01− 𝑝02,


S0 S1

S3 S2

Figure 2: The state transition of the DTMCmodel.

𝑝11= 𝑝 (𝑝

𝑅1

𝑝𝑅1𝐷+ (1 − 𝑝

𝑅1

)) (𝑝𝑆𝑝𝑆𝐷𝑝𝑆𝑅2

+ (1 − 𝑝𝑆))

+ (1 − 𝑝) (𝑝𝑅2

𝑝𝑅2𝐷+ (1 − 𝑝

𝑅2

))

⋅ (𝑝𝑆𝑝𝑆𝐷𝑝𝑆𝑅1

+ (1 − 𝑝𝑆)) ,

𝑝12= 𝑝𝑝𝑆𝑝𝑆𝐷(1 − 𝑝

𝑆𝑅2

) 𝑝𝑅1

𝑝𝑅1𝐷+ (1 − 𝑝)

⋅ 𝑝𝑆𝑝𝑆𝐷(1 − 𝑝

𝑆𝑅1

) 𝑝𝑅2

𝑝𝑅2𝐷,

𝑝13= 1 − 𝑝

11− 𝑝12,

𝑝22= (𝑝𝑅1

𝑝𝑅1𝐷+ (1 − 𝑝

𝑅1

)) (𝑝𝑅2

𝑝𝑅2𝐷+ (1 − 𝑝

𝑅2

))

⋅ (𝑝𝑆𝑝𝑆𝐷+ (1 − 𝑝

𝑆)) ,

𝑝23= 1 − 𝑝

22,

𝑝30= 𝑝𝑆𝐷𝑝𝑆𝑅1

𝑝𝑆𝑅2

,

𝑝31= 𝑝𝑆𝐷((1 − 𝑝

𝑆𝑅1

) 𝑝𝑆𝑅2

+ 𝑝𝑆𝑅1

(1 − 𝑝𝑆𝑅2

)) ,

𝑝32= 𝑝𝑆𝐷(1 − 𝑝

𝑆𝑅1

) (1 − 𝑝𝑆𝑅2

) ,

𝑝33= 1 − 𝑝

𝑆𝐷,

𝑝10= 𝑝20= 𝑝21= 0,

(8)

where 𝑝 = 1 with correct frame reception at node 𝑅1;

otherwise 𝑝 = 0 on state 𝑆1. And 𝑝0

𝑆= 1 owing to a mech-

anism which is adopted to inform 𝑆 of previous data framewhich is not correctly received at both𝐷 and two-relay node(𝑅1, 𝑅2); otherwise 𝑝0

𝑆= 𝑝𝑆.

Suppose the transition probability matrix 𝑃 of the DTMCis initiated from state 𝑆

0, and let 𝜋 = (𝜋

0, 𝜋1, 𝜋2, 𝜋3) be the

steady state distribution of the DTMC; then 𝜋3is the steady

probability of state 𝑆3.

In this paper, the throughput is defined as the averagenumber of data frames received successfully by destinationnode 𝐷 per time slot and can be computed as the averagenumber of time slots that theDTMC spends in state 𝑆

3, which

equals the probability of steady state 𝑆3. So the throughput

can be acquired by solving the following formula:

𝜋𝑃 = 𝜋,

3

∑

𝑖=0

𝜋𝑖= 1,

(9)

where 𝜋3is the throughput and 𝑃 is the transition probability

matrix whose elements are given by (8).Comparing the throughput of TRCAP and CA ([19],

(18)), we can easily calculate the throughput gain as follows:

𝐺 =

𝑇TRCAP𝑇CA

, (10)

where𝑇TRCAP and𝑇CA are the throughput of TRCAP andCA,respectively.

4. Analysis of Energy Efficiency

The power consumption of the internal RF circuitry and thepower amplifier is themain energy consumption of the sensornode [20]. Assume that the total energy consumption of thesystem is composed of the power consumption of the poweramplifier and circuit blocks of the nodes. Let 𝑃PA denote thepower consumption of the power amplifier, and 𝑃

𝑡and 𝑃

𝑟

represent the power consumption of the internal RF circuitryof the transmitting and receiving:

𝑃PA = 𝑃𝑖 (1 + 𝜀) , (11)

where 𝑃𝑖denotes the transmit power of node 𝑖, 𝜀 denotes the

loss factor of the power amplifier, 𝜀 = (𝜉/𝜂 − 1) with 𝜉 =3((√𝑀−1)/(√𝑀+1)) is the peak-to-average ratio (PAR) foran M-QAM modulation, and 𝜂 is the drain efficiency of theamplifier.

Considering that the total packet is composed of theheader, payload, and the trailer, the energy efficiency can beexpressed as follows:

𝜌 =

(1 − PER) 𝐿𝑃

, (12)

where PER denotes the average packet error rate with TA andTRCAP, 𝐿 denotes the length of the payload in a data packet,and𝑃denotes the energy consumption of the communicationsystem.Thus the energy efficiency is expressed by the ratio ofthe number of packet bits received successfully to the totalenergy consumption.

(1) Traditional ARQ:

𝑃TA=

{

{

{

𝑃𝑖(1 + 𝜀) + 𝑃

𝑡+ 𝑃𝑟

(1 − 𝑃𝑆𝐷)

2𝑃𝑖(1 + 𝜀) + 2𝑃

𝑡+ 2𝑃𝑟𝑃𝑆𝐷.

(13)


In the first term of the above expression, when the dataframe is received successfully by 𝐷 with the probability (1 −𝑃𝑆𝐷), the energy consumption is composed of the consumed

power in node 𝑆 (𝑃𝑡(1 + 𝜀) + 𝑃

𝑡) and receiving power in node

𝐷 𝑃𝑟. The second term expresses the energy consumption of

the system when node 𝐷 has received the packet incorrectlyand the node 𝑆’s retransmission.

So the total energy consumption of transmitting thepacket in traditional strategy with ARQ is expressed asfollows:

𝐸TA= (𝑃𝑖(1 + 𝜀) + 𝑃

𝑡+ 2𝑃𝑟) (1 − 𝑃

𝑆𝐷)

+ (2𝑃𝑖(1 + 𝜀) + 2𝑃

𝑡+ 2𝑃𝑟) 𝑃𝑆𝐷

= (𝑃𝑖(1 + 𝜀) + 𝑃

𝑡+ 𝑃𝑟) (1 + 𝑃

𝑆𝐷) .

(14)

Energy efficiency of traditional strategy with ARQ can beobtained by substituting (6) and (13) into (12):

𝜌TA=

𝐿 (1 − PER (𝛾))𝐸TA . (15)

(2) Two-relay node cooperative ARQ protocol:

𝑃CA

=

{{{{{{{{{{

{{{{{{{{{{

{

𝑃𝑖(1 + 𝜀) + 𝑃

𝑡+ 3𝑃𝑟

(1 − 𝑃𝑆𝐷) ,

2𝑃𝑖(1 + 𝜀) + 2𝑃

𝑡+ 4𝑃𝑟𝑃𝑆𝐷(1 − 𝑃

𝑆𝑅1

) 𝑃𝑆𝑅2

,

2𝑃𝑖(1 + 𝜀) + 2𝑃

𝑡+ 4𝑃𝑟𝑃𝑆𝐷𝑃𝑆𝑅1

(1 − 𝑃𝑆𝑅2

) ,

3𝑃𝑖(1 + 𝜀) + 3𝑃

𝑡+ 4𝑃𝑟𝑃𝑆𝐷(1 − 𝑃

𝑆𝑅1

) (1 − 𝑃𝑆𝑅2

) ,

2𝑃𝑖(1 + 𝜀) + 2𝑃

𝑡+ 6𝑃𝑟𝑃𝑆𝐷𝑃𝑆𝑅1

𝑃𝑆𝑅2

,

(16)

𝐸total =𝜋0𝐸𝜋0

+ 𝜋1𝐸𝜋1

+ 𝜋2𝐸𝜋2

+ 𝐸𝜋3

𝜋3

. (17)

In the first term in (16), when the data frame is correctlyreceived by 𝐷 with the probability (1 − 𝑃

𝑆𝐷), the energy

consumption consists of the consumed power in node 𝑆(𝑃𝑖(1+𝜀)+𝑃

𝑡) and receiving power in node𝐷 is𝑃

𝑟and in node

𝑅1, 𝑅2is 2𝑃𝑟. The second and third term express the energy

consumption when either 𝑅1or 𝑅2has received the packet

successfully and𝐷 has failed to receive the packet.The fourthterm expresses the energy consumption when node 𝐷 hasfailed to receive the packet and both 𝑅

1and 𝑅

2have correctly

received the packet simultaneously. The last term representsthe energy consumption of system when all three nodes havefailed to receive the packet simultaneously.

In the above expression, the probability of different stateis represented by the steady state (𝜋

0, 𝜋1, 𝜋2, 𝜋3) distribution

of the DTMC.The total energy consumption of successfully transmit-

ting a packet from 𝑆 to 𝐷 using TRCAP can be derived fromour Markov model as follows:

𝐸total = (2𝑃𝑖 (1 + 𝜀) + 2𝑃𝑡 + 6𝑃𝑟) 𝜋0

+ (2𝑃𝑖(1 + 𝜀) + 2𝑃

𝑡+ 4𝑃𝑟) 𝜋1

+ (3𝑃𝑖(1 + 𝜀) + 3𝑃

𝑡+ 4𝑃𝑟) 𝜋2

+ (𝑃𝑖(1 + 𝜀) + 𝑃

𝑡+ 3𝑃𝑟) 𝜋3.

(18)

Energy efficiency of TRCAP can be obtained by (9) and(18) into (12):

𝜌 =

𝐿 (1 − 𝜋3)

𝐸total. (19)

5. Numerical Results

In this section we numerically evaluate the throughputand energy efficiency of the presented protocol comparedwith that of traditional TA and TRCAP. Throughout thissimulation we assume that the length of a packet is set tobe 1024 bits and the system parameters take the followingvalues: 𝛼 = 4, 𝜀 = 0.3, 𝑃

𝑖= 10−3W, 𝑃

𝑡= 10−4W, 𝑃

𝑟=

5 × 10−5W, 𝐿 = 1024 bits,𝑁

0= 10−13.5, (𝑎, 𝑔, 𝛾

𝑡) = (58.7332,

0.1641, 13.9470). The values of 𝛼, 𝜀, 𝑃𝑖, 𝑃𝑡, and 𝑃

𝑟are taken

from the specifications of Mica2 motes. MATLAB is selectedas the simulation tool and 16-QAM modulation is used. Weconsider the 𝑆-𝐷 distance varies from 100m to 300m forthroughput and energy efficiency analysis.

We assume that the connections of the relays 𝑅1and 𝑅

2

are perpendicular to the connecting line of the source node𝑆 and the destination node 𝐷, and the vertical cross point is𝑂. We also assume the 𝑆-𝑅

1distance is 𝐷

𝑆𝑅1

= 𝑞𝑆𝑅1

× 𝐷𝑆𝐷

(0 < 𝑞𝑆𝑅1

< 1), the same as 𝑞𝑆𝑅2

and 𝑞𝑅1𝐷, 𝑞𝑅2𝐷.

Figure 3 depicts the throughput performances of differentARQ protocols versus the 𝑆-𝐷 distance with different 𝑞

𝑆𝑅1

and 𝑞𝑆𝑅2

, 𝑞𝑅1𝐷, 𝑞𝑅2𝐷. From Figure 3, we can see that the

throughput efficiency decreases when 𝐷𝑆𝐷

increases nomatter what ARQ protocol is adopted in this paper becausethe SNR at the receiver reduces as the distance increases.It can be seen from the figure that TRCAP outperformsthe traditional ARQ protocol for any 𝑆-𝐷 distance, and thethroughput performances will become better when relaynodes are close to the middle location between the sourcenode and the destination node 𝐷. The simulation resultsare very close to the theoretical results, which verifiedthe performance analysis in Section 3. Through the aboveanalytical and simulation results, we can see TRCAP cansignificantly improve the throughput performance of systemwhen the communication distance is rather long.

Figure 4 depicts the throughput gain of TRCAP com-pared with TA under different relay locations, respectively.From the figures, we can see that the throughput gain isthe best when relay nodes are close to the middle locationbetween the source node and the destination node 𝐷. Andthe value of throughput gain will become more and more bigalong with the distance increases.

Figure 5 depicts the energy efficiency of the system versusthe distance between the source node 𝑆 and the destinationnode𝐷 with different ARQ protocols. The simulation resultsare very close to the theoretical result, which verified theenergy efficiency performance analysis in Section 5. FromFigure 5, we can see that the value of energy efficiency


100 120 140 160 180 200 220 240 260 280 3000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Distance between S and D (m)

Thro

ughp

ut effi

cien

cy

TATRCAP

TRCAPTRCAP

qSR1 = 0.6, qR1D = 0.5

qSR2 = 0.5, qR2D = 0.6

qSR1 = 0.7, qR1D = 0.4

qSR2 = 0.4, qR2D = 0.7

qSR1 = 0.8, qR1D = 0.3

qSR2 = 0.3, qR2D = 0.8

Figure 3:The throughput performances of different ARQprotocols.

100 120 140 160 180 200 220 240 260 280 3000

1

2

3

4

5

6

7

8

9

10


Thro

ughp

ut effi

cien

cy g

ain

TRCAPTRCAP

TRCAP

qSR1 = 0.6, qR1D = 0.5

qSR2 = 0.5, qR2D = 0.6

qSR1 = 0.7, qR1D = 0.4

qSR2 = 0.4, qR2D = 0.7

qSR1 = 0.8, qR1D = 0.3

qSR2 = 0.3, qR2D = 0.8

Figure 4:The throughput efficiency gain of TRCAP compared withTA.

becomesmore andmore small first because the PER increaseswith the 𝑆-𝐷 distance increases. The energy efficiency ofTRCAP has a better performance than TAwhen 𝑆-𝐷 distanceis above 120m. At 𝑆-𝐷 distance below 120m, TA has a betterperformance than TRCAP, because node 𝐷 will correctlyreceive the packet from source nodewhen destination node isnear to source node. The probability of cooperative retrans-mission will become bigger and bigger along with the 𝑆-𝐷distance increases.

Figure 6 depicts the energy efficiency gain of TRCAPcompared with TA under different relay locations, respec-tively.We can find that the biggest gain is acquired when relaynodes are close to the middle location between the sourcenode and the destination node 𝐷. The energy efficiency gainis almost the same when destination node is near to sourcenode.

100 120 140 160 180 200 220 240 260 280 3000

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2×107


TATRCAP

TRCAPTRCAP

Ener

gy effi

cien

cy (b

it/J)

qSR1 = 0.6, qR1D = 0.5

qSR2 = 0.5, qR2D = 0.6

qSR2 = 0.4, qR2D = 0.7

qSR1 = 0.8, qR1D = 0.3

qSR2 = 0.3, qR2D = 0.8

qSR1 = 0.7, qR1D = 0.4

Figure 5: The energy efficiency of different ARQ protocols.

100 120 140 160 180 200 220 240 260 280 300


Ener

gy effi

cien

cy g

ain

TRCAPTRCAP

TRCAP

100

101

102

qSR1 = 0.6, qR1D = 0.5

qSR2 = 0.5, qR2D = 0.6

qSR2 = 0.4, qR2D = 0.7

qSR1 = 0.8, qR1D = 0.3

qSR2 = 0.3, qR2D = 0.8

qSR1 = 0.7, qR1D = 0.4

Figure 6: The energy efficiency gain of TRCAP compared with TA.

6. Conclusions

In this paper, the throughput and energy efficiency of theTRCAP and TA protocol in WSN are studied and compared.The theoretical analysis and numerical results prove thatwhen the distance of source and destination is above thethreshold distance, the TRCAP has larger throughput andmore energy efficiency than TA and two-relay node gains canbe achieved. Moreover, when 𝐷

𝑆𝑅1

is approximately equal to𝐷𝑅1𝐷and 𝐷

𝑆𝑅2

is approximately equal to 𝐷𝑅2𝐷meanwhile,

throughput gain and energy efficiency gain are the bestamong all of the different relay locations.

So far, we have only considered a simple four-nodewireless network. In the future, we will study the morecomplicated and the practical wireless sensor networks.However, the focus and the contribution of our work are the


theoretical analysis of the throughput and energy efficiency ofproposed two-relay node cooperative ARQprotocol inWSNswhich is based on a novel DTMCmodel.

Conflict of Interests

The authors declare no conflict of interests.

Authors’ Contribution

In this work, the general conception has been developed byHaiyong Wang, Geng Yang, and Yiran Gu, while the test hasbeen developed by Haiyong Wang and Jian Xu. Moreover,Haiyong Wang has prepared the final draft and Zhixin Sunhas guaranteed the critical reading.

Acknowledgments

Thanks are given to referees whose comments and suggestionwere very helpful for revising the authors’ paper.This researchis supported by the National Natural Science Foundation ofChina under Grant nos. 61272084, 61202004, the SpecializedResearch Fund for the Doctoral Program of Higher Edu-cation under Grant nos. 20113223110003, 20093223120001,the Key Project of Natural Science Research of JiangsuUniversity under Grant no. 11KJA520002, the Natural ScienceFoundation of Jiangsu Province under Grant no. BK2011754,and the Project of Nanjing University of Posts and Telecom-munications under Grant no. NY214099.

References

[1] D. Zhang and Z. Chen, “Energy-efficiency of cooperative com-munication with guaranteed E2E reliability in WSNs,” Interna-tional Journal of Distributed Sensor Networks, vol. 2013, ArticleID 532826, 11 pages, 2013.

[2] Z. Zhou, S. Zhou, J.-H. Cui, and S. Cui, “Energy-efficient coop-erative communication based on power control and selectivesingle-relay in wireless sensor networks,” IEEE Transactions onWireless Communications, vol. 7, no. 8, pp. 3066–3079, 2008.

[3] T. Predojev, J. Alonso-Zarate, M. Dohler, and L. Alonso,“Energy consumption optimisation for duty-cycled schemes inshadowed environments,” International Journal of DistributedSensor Networks, vol. 2014, Article ID 709135, 10 pages, 2014.

[4] N. Marchenko, T. Andre, G. Brandner, W. Masood, and C.Bettstetter, “An experimental study of selective cooperativerelaying in industrial wireless sensor networks,” IEEE Transac-tions on Industrial Informatics, vol. 10, no. 3, pp. 1806–1816, 2014.

[5] S. Abdulhadi, M. Jaseemuddin, and A. Anpalagan, “A survey ofdistributed relay selection schemes in cooperative wireless adhoc networks,” Wireless Personal Communications, vol. 63, no.4, pp. 917–935, 2012.

[6] A. P. Bianzino,M. Asplund, E. J. Vergara, and S. Nadjm-Tehrani,“Cooperative proxies: optimally trading energy and quality ofservice in mobile devices,” Computer Networks, vol. 75, pp. 297–312, 2014.

[7] M. Xiao and M. Skoglund, “Multiple-user cooperative commu-nications based on linear network coding,” IEEE Transactionson Communications, vol. 58, no. 12, pp. 3345–3351, 2010.

[8] M. Xiao, J. Kliewer, and M. Skoglund, “Design of networkcodes for multiple-user multiple-relay wireless networks,” IEEETransactions on Communications, vol. 60, no. 12, pp. 3755–3766,2012.

[9] X. Tang, R. Liu, P. Spasojevic, and H. V. Poor, “On the through-put of secure hybrid-ARQ protocols for Gaussian block-fadingchannels,” IEEE Transactions on InformationTheory, vol. 55, no.4, pp. 1575–1591, 2009.

[10] C. Zhang, W. Wang, and G. Wei, “Design of ARQ protocols fortwo-user cooperative diversity systems in wireless networks,”Computer Communications, vol. 32, no. 6, pp. 1111–1117, 2009.

[11] M. Nasim, S. Qaisar, and S. Lee, “An energy efficient coopera-tive hierarchical MIMO clustering scheme for wireless sensornetworks,” Sensors, vol. 12, no. 1, pp. 92–114, 2012.

[12] M. Kakitani, G. Brante, and R. Souza, “Energy efficiency anal-ysis of a two dimensional cooperative wireless sensor networkwith relay selection,” Radio Engineering, vol. 22, no. 2, pp. 549–557, 2013.

[13] H. Chen, Y. Cai, W. Yang, D. Zhang, and Y. Hu, “Throughputand energy efficiency of a novel cooperative ARQ strategy forwireless sensor networks,” Computer Communications, vol. 35,no. 9, pp. 1064–1073, 2012.

[14] S. Culver, M. Gidlund, and G. Wang, “Performance of coop-erative relaying with ARQ in Wireless sensor networks,” inProceedings of the IEEE 34th Conference on Local ComputerNetworks (LCN ’09), pp. 317–319, IEEE, Zurich, Switzerland,October 2009.

[15] H. Y. Wang, G. Yang, Z. Y. Chen, and J. Xu, “Throughput andenergy efficiency optimization of ARQ protocols for exploitingcooperative communication in wireless sensor networks,” Jour-nal of Convergence Information Technology, vol. 7, no. 19, pp. 39–47, 2012.

[16] S. Cui, A. J. Goldsmith, and A. Bahai, “Energy-efficiency ofMIMO and cooperativeMIMO techniques in sensor networks,”IEEE Journal on Selected Areas in Communications, vol. 22, no.6, pp. 1089–1098, 2004.

[17] Q. Xiao, K. Zheng, S. Luo, Y. Yang, and L. Zhang, “An effi-cient algorithm for time-driven data gathering in wireless sen-sor networks using inter-session network coding,” Journal ofConvergence Information Technology, vol. 7, no. 1, pp. 11–18, 2012.

[18] Q. Liu, S. Zhou, and G. B. Giannakis, “Cross-layer combiningof adaptive modulation and Coding with truncated ARQ overwireless links,” IEEE Transactions on Wireless Communications,vol. 3, no. 5, pp. 1746–1755, 2004.

[19] G. Yu, Z. Zhang, and P. Qiu, “Efficient ARQ protocols forexploiting cooperative relaying in wireless sensor networks,”Computer Communications, vol. 30, no. 14-15, pp. 2765–2773,2007.

[20] Q. Zhao and L. Tong, “Energy efficiency of large-scale wirelessnetworks: proactive versus reactive networking,” IEEE Journalon Selected Areas in Communications, vol. 23, no. 5, pp. 1100–1112, 2005.

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttp://www.hindawi.com Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014


Active and Passive Electronic Components

Control Scienceand Engineering

Journal of



RotatingMachinery


Hindawi Publishing Corporation http://www.hindawi.com

Journal ofEngineeringVolume 2014

Submit your manuscripts athttp://www.hindawi.com

VLSI Design



Shock and Vibration


Civil EngineeringAdvances in

Acoustics and VibrationAdvances in



Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation http://www.hindawi.com

Volume 2014

The Scientific World JournalHindawi Publishing Corporation http://www.hindawi.com Volume 2014

SensorsJournal of


Modelling & Simulation in EngineeringHindawi Publishing Corporation http://www.hindawi.com Volume 2014


Chemical EngineeringInternational Journal of Antennas and

Propagation




Navigation and Observation



DistributedSensor Networks


research article a novel cooperative arq method for wireless...

Documents