Peer-Reviewed Technical Communication

IEEE JOURNAL OF OCEANIC ENGINEERING, VOL. 40, NO. 1, JANUARY 2015 159

Peer-Reviewed Technical Communication

OFDM-Modulated Dynamic Coded Cooperation inUnderwater Acoustic Channels

Yougan Chen, Member, IEEE, Zhaohui Wang, Member, IEEE, Lei Wan, Student Member, IEEE, Hao Zhou,Shengli Zhou, Fellow, IEEE, and Xiaomei Xu

Abstract—Dynamic coded cooperation (DCC) allows relaydiversity without altering the transmission procedure from thesource to the destination. In this paper, we propose a practicalorthogonal frequency-division multiplexing (OFDM)-modulatedDCC scheme for underwater relay networks, where OFDM mod-ulation accommodates multipath fading channels with large delayspread. Two cooperation strategies are studied, where the relaytransmits either identical or different OFDM blocks as the sourceduring the cooperation phase. The block-level synchronization be-tween the OFDM blocks from the source and the relay is achievedby a delay control mechanism at the relay, by knowing the dis-tances among the source, relay, and destination. Two OFDM–DCCdesign examples are presented, one based on nonbinary rate-com-patible low-density parity-check (LDPC) codes applied acrossmultiple OFDM blocks, and the other using layered interblockerasure correction and intrablock error-correction coding. Inaddition to simulation studies, one particular design has been im-plemented on practical OFDMmodems, and tested in a swimmingpool and in a recent sea experiment. The proposed OFDM–DCCscheme is particularly appealing to underwater acoustic (UWA)networks where a relay node with abundant resources (e.g., asurface buoy) can enhance communications among underwaternodes without changing their transmission procedure.

Manuscript received July 08, 2013; revisedDecember 02, 2013; accepted Jan-uary 28, 2014. Date of publication June 05, 2014; date of current version Jan-uary 09, 2015. The work of Y. Chen and X. Xu was supported by the NationalNatural Science Foundation of China under Grants 41176032 and 41376040,by the Specialized Research Fund for the Doctoral Program of Higher Educa-tion under Grant 20130121120033, by the Fundamental Research Funds for theCentral Universities under Grant 201112G020, and by the China ScholarshipCouncil. The work of Z.-H. Wang, L. Wan, H. Zhou, and S. Zhou was sup-ported PECASE under Grant N00014-09-1-0704 and by the National ScienceFoundation (NSF) under Grants ECCS-1128581 and CNS-1205665.Associate Editor: J. Gomes.Y. Chen and X. Xu are with the Department of Applied Ocean Physics and

Engineering, Ministry of Education (MOE) Key Laboratory of UnderwaterAcoustic Communication and Marine Information Technology, Xiamen Uni-versity, Xiamen, Fujian 361005, China (e-mail: [email protected];[email protected]).Z.-H. Wang was with the Electrical and Computer Engineering Department,

University of Connecticut, Storrs, CT 06269 USA. She is now with the Depart-ment of Electrical and Computer Engineering, Michigan Technological Univer-sity, Houghton, MI 49931-1295 USA (e-mail: [email protected]).L. Wan and S. Zhou are with the Department of Electrical and Computer

Engineering, University of Connecticut, Storrs, CT 06269 USA (e-mail:[email protected]; [email protected]).H. Zhou was with the Department of Electrical and Computer Engi-

neering, University of Connecticut, Storrs, CT 06269 USA. He is nowwith Aquatic Sensor Network Technology, Storrs, CT 06269 USA (e-mail:[email protected]).Digital Object Identifier 10.1109/JOE.2014.2304254

Index Terms—Dynamic coded cooperation (DCC), orthogonalfrequency-division multiplexing (OFDM), rate-compatible coding,underwater acoustic (UWA) communications.

I. INTRODUCTION

R ELAY-BASED strategies provide a new dimension to thedesign space of wireless networks in which the coverage

and throughput may be significantly enhanced [1]–[3]. Considera network consisting of three terminals denoted as source (S),relay (R), and destination (D), as illustrated in Fig. 1, multiplerelay strategies can be applied, e.g., amplify and forward (AF),decode and forward (DF), and compression and forward (CF)[2], [3]. Out of various choices, the dynamic coded coopera-tion (DCC) scheme, as studied in [4]–[6], is particularly inter-esting. Specifically, the half-duplex relay listens until it can de-code the message correctly and then switches to the transmis-sion mode. When transmitting, the relay superimposes its trans-mission on the ongoing transmission from the source to the des-tination. There is no extra transmission time scheduled for therelay, making it bandwidth efficient. The source can be even un-aware of the existence of the relay.In this paper, we consider the application of DCC to under-

water systems. For example, consider an underwater acoustic(UWA) [7], [8] sensor network as depicted in Fig. 1. A sur-face buoy can serve as a relay to assist the communicationbetween any pair of underwater nodes. Note that the surfacebuoy can be solar powered, having unlimited power supply,and can have large processing capability with a large re-ceiver array. Adding a surface buoy to improve the com-munications among resource-limited underwater nodes is par-ticularly appealing to practical UWA communications. Thereare a few relay strategies that have been recently studiedspecifically for UWA cooperative communications, e.g., dis-tributed space-time block coding in [9], and amplify forwardand decode forward in [10]–[15]. Unlike DCC, these cooper-ative schemes require extra transmission time scheduled forthe relay after the source transmission.Existing works on the DCC scheme [4]–[6] assume fre-

quency-flat channels, and assume symbol level (or samplelevel) synchronization of the transmissions from the sourceand the relay. UWA channels, however, have very large delayspreads. Also, it is hard to synchronize the transmission on the

0364-9059 © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

160 IEEE JOURNAL OF OCEANIC ENGINEERING, VOL. 40, NO. 1, JANUARY 2015

Fig. 1. (a) Generic setup of three-node cooperative communication. (b) Appli-cation in a UWA system.

sample level from distributed nodes. The work carried out inthis paper is as follows.• We propose a practical orthogonal frequency-divisionmul-tiplexing (OFDM) modulated DCC scheme for multipathchannels with large delay spread. We introduce a delaycontrol mechanism at the relay to achieve the block-levelsynchronization between the transmissions from the sourceand the relay, which requires the knowledge of the dis-tances among source, relay, and destination. Two coopera-tion strategies are studied, one termed as repetition redun-dancy (RR) cooperation where the relay transmits identicalOFDM blocks as the source during the cooperation phase,and the other termed as extra redundancy (ER) cooperationwhere the relay transmits different OFDM blocks from thesource during cooperation.Note that the application of OFDM in other types of relaycooperations can be found in [16]–[18] for radio channelsand in [14] and [15] for UWA channels.

• For the proposed OFDM–DCC scheme, we presenttwo concrete design examples, one based on nonbinaryrate-compatible low-density parity-check (LDPC) codes,and the other based on layered interblock erasure-correc-tion coding and intrablock error-correction coding. Theformer design jointly decodes all the accumulated OFDMblocks, while the latter relies on block-by-block channeldecoding and throws away the OFDM blocks decoded inerror. Hence, the former design is expected to have betterperformance and the gap to the information-theoretic limitis evaluated, while the latter can be easily implementedthrough erasure coding on top of existing physical layerchannel coding in modems currently available.

• In addition to simulation studies, we have implementedthe OFDM–DCC scheme based on layered coding and RRcooperation in a practical OFDM modem [19]. Real-timeOFDM–DCC operation is demonstrated not only in aswimming pool, but also in a recent sea experiment, inKaohsiung, Taiwan, May 26, 2013.Note that existing works have only used simulations[10]–[12], [14], [15] or emulated data sets with recordedsignals [9].

The rest of the paper is organized as follows. The proposedOFDM–DCC framework is presented in Section II. The designexample based on nonbinary rate-compatible LDPC codes isspecified in Section III, and the design example based on layerederasure- and error-correction coding is detailed in Section IV.Conclusions are contained in Section V.

II. OFDM-MODULATED DCC

We consider a three-node network consisting of a source, adestination, and a relay which helps the transmission from thesource to the destination. All the transceivers work in a half-du-plex fashion, which is the case in UWA networks. The channelsamong the source, the relay, and the destination are multipathfading channels with large delay spread. For this reason, OFDMmodulation is adopted. We assume that the guard interval be-tween consecutive OFDM symbols, either cyclic prefix (CP) orzero padding (ZP), is larger than themaximum delay spread plusthe offset between the signals from the source and the relay toreach the destination. As such, there is no interblock interfer-ence (IBI) between consecutive OFDM blocks at the relay andat the destination.The source divides a packet into multiple blocks, say

blocks, with each block modulated on one OFDM symbol. Thesource transmits OFDM blocks, which will reach both therelay and the destination. Note that these blocks are related toeach other, depending on the coding schemes to be specifiedin Sections III and IV, and the whole packet can be recoveredbased on a subset of these blocks.

A. Relay Operations

The relay has two operational phases: the listening phaseand the cooperative transmission phase. First, the relay is inthe listening phase. For every new OFDM block that it col-lects, the relay tries to decode the whole packet using the accu-mulated OFDM blocks. After successfully decoding the trans-mitted packet before the end of the transmission from the source,the relay switches to the cooperation phase.1) Cooperation Strategies: Denote as the number of

OFDM blocks that the relay has used for successful decoding.The relay starts to superimpose its transmission to the ongoingtransmission from the source, from the th block tothe th block, where is an integer to be determined. Twopossible cooperation strategies at the relay are the following.• RR cooperation: The relay regenerates and transmits iden-tical OFDM blocks as the source, from the block index

to .• ER cooperation: The relay generates and transmits dif-ferent redundant OFDM blocks from the source from theblock index to .

An illustration of RR and ER will be provided in Fig. 3 for adesign example in Section III.2) Block-Level Synchronization: During the cooperative

transmission phase, the OFDM blocks from the source andthe relay need to be aligned at the block level at the receiverside. This is achieved through a delay control mechanism at therelay.

CHEN et al.: OFDM-MODULATED DYNAMIC CODED COOPERATION IN UNDERWATER ACOUSTIC CHANNELS 161

Fig. 2. Relay introduces a waiting time before the cooperative transmission to achieve the block-level synchronization.

Fig. 3. One OFDM–DCC example. The numbers shown are the indexes of theOFDM blocks transmitted. in this example. (a) Repetition redundancy.(b) Extra redundancy.

Define , , and as the transmission delays betweenthe source and the relay, the relay and the destination, and thesource and the destination, respectively. Denote the start time ofthe th block at the source as , the relay processing time as

, and the relay waiting time as . To synchronize thereception of the th OFDM block at the destination,the following relationship should be satisfied as illustrated inFig. 2:

(1)

Hence, the extra waiting time before the cooperative transmis-sion at the relay is

(2)

The parameter should be taken as a small integer that leads toa nonnegative waiting time . The processing time isknown to the relay. The difference depends onthe source–relay–destination geometry. In a favorable geometrywhere is small and with a relay having, the value of could be as small as one.

The relay needs to have the knowledge of the source–relaydistance , the relay–destination distance , and thesource–destination distance to determine the waiting timefrom (2). Since the acoustic modems are often equipped withthe ranging functionality, the relay needs to probe the sourceand the destination to obtain and . The source needs toprobe the destination to obtain , and conveys it to the relay.For example, the source–destination distance could be put intothe packet header, along with the source ID and destination ID.The cooperation phase lasts for OFDM blocks,

hence the duration is dynamic depending on the channel qualityfrom the source to the relay.

B. Receiver Processing at the Destination

Let denote the number of receiving elements at the desti-nation. We consider an OFDM modulation with subcarriers.For the first blocks, the destination only receives thetransmission from the source. After the necessary preprocessingsteps which involve Doppler compensation and fast Fouriertransform (FFT) operation [20], the input–output relationshipof the th received OFDM block at the th receiving element is

(3)

where is the vector containing the frequency measure-ments across subcarriers, is the vector of transmitted sym-bols on subcarriers, denotes the channel mixing ma-trix for the channel between the source and the destination, and

is the ambient noise.For the last blocks, the destination receives the

superposition of the signals from the source and the relay. Weexamine the two different cooperation strategies individually.1) RR Cooperation: Since the relay transmits identical

OFDM blocks as the source, the input–output relationship is

(4)

where denotes the channel mixing matrix for thechannel between the relay and the destination. Clearly, anequivalent channel, which consists of multipath arrivals fromboth the source and the relay, is formed.


2) ER Cooperation: Since the relay and the source transmitdifferent OFDM blocks, the input–output relationship is

(5)

where is the information block transmitted by the relay.Since is different from , two parallel data streams needto be separated at the receiver side, leading to a receiver de-sign problem that has been addressed in the context of mul-tiple-input–multiple-output (MIMO) OFDM.For the first OFDM blocks without cooperation and

the next OFDM blocks during the RR coopera-tion phase, the destination can adopt a receiver as in [20] thatignores the residual intercarrier interference (ICI) after Dopplercompensation, where the channel mixing matrices and

become diagonal, or a receiver as in [21] that dealswith ICI explicitly imposing a banded structure on the channelmixing matrices.For the OFDM blocks received during the ER

cooperation phase, two data streams in and need tobe separated. The ICI-ignorant MIMO–OFDM receiver in [22]or the ICI-progressive MIMO–OFDM receiver in [23] can beadopted to demodulate the OFDM blocks, generating the a pos-teriori probabilities of the corresponding symbols. At the endof the source transmission, the soft information accumulated forall the symbols during the direct transmission phase and the ERcooperation phase are used to decode the whole packet.

C. Discussions

In the RR cooperation, the relay transmission increases thereceived power and provides multipath diversity benefits to thelast OFDM blocks. While in the ER cooperation,the relay could provide both the diversity and the coding benefitsthrough newly added blocks that contain more parity symbols.Hence, ER is expected to have better performance than RR. Onthe implementation side, however, RR is more convenient thanER.• The ER cooperation requires the destination to detect thestarting point of the cooperation phase. The generalizedlog-likelihood ratio test (GLRT) was proposed in [5], anda power detector was developed in [6]. For the OFDM sig-nals, one could reserve several subcarriers for the detec-tion of relay cooperation, which, however, introduces extraoverhead.

• For the ER cooperation, the destination needs to demodu-late two data streams in the cooperation phase. Hence, thereceiver needs to adjust its processingmodules between thenoncooperation phase and the ER cooperation phase.

For the RR cooperation, no change is needed at the destina-tion. Note that the OFDM modem in [19] performs channel es-timation on a block-by-block basis, in order to deal with fastchannel variations in underwater environments. Hence, the re-ceiver does not need to be aware of the existence of a relay.Further, instead of one relay, multiple relays can be easily addedinto the OFDM–DCC scheme if using the RR cooperation.

Fig. 4. Performance of nonbinary RC–LDPC codes over AWGN channel,where is the energy per BPSK symbol and is the noise vari-ance. Red dashed lines: Shannon limit with BPSK input; right to left:

.

Fig. 5. Performance comparison with one receive element at the destination.

III. ONE DESIGN EXAMPLE BASED ON RATE-COMPATIBLECHANNEL CODING

Code design for the DCC is an important task. The relay dealswith truncated codewords with different truncation lengths,while the destination deals with extended codewords in the ERcooperation. Rateless coding has been suggested in [4] and [5],which requires a large number of blocks. Multiple turbo codeshave been designed in [6] for DCC. Here, we present a designexample leveraging nonbinary rate-compatible quasi-cyclic(QC) LDPC codes [25], which have good performance forshort block lengths and low encoding and decoding complex-ities. Other designs of rate-compatible codes can be similarlyincorporated into the OFDM–DCC scheme.

A. Code Design

We present one specific design based on [25], where the rate-compatible code is designed in a Galois field (GF) of size 16,with a protograph of eight information nodes and a set of coderates . The main difference with [25] is thatthe approximate cycle extrinsic (ACE) algorithm factor is 16


Fig. 6. Performance comparison with two receive elements at the destination.

Fig. 7. Performance with different numbers of hydrophones at the buoy.

here, resulting in the information length of1024 b.

The 1024 information bits are divided into eight blocks, with128 b per block. The source transmits eight blocks of informa-tion symbols and six blocks of parity check symbols, hence thecode rate at the source is 8/14. In the ER operation, the relaygenerates additional redundant blocks of parity check symbolswith the lowest code rate to be 8/19. Fig. 3 illustrates the sixpossible cases that can occur at the relay, for both RR and ERoperations, where . In case 1, the relay can successfullydecode the source message after only receiving the informationblocks, while in case 6, the relay cannot decode the source mes-sage in time to perform cooperation.Fig. 4 shows the packet error rate (PER) performance of the

RC–LDPC codes in additive white Gaussian node (AWGN)channels with binary phase-shift keying (BPSK) modulation.All the codes perform about 2–2.5 dB away from the Shannonlimit with the BPSK input. Considering the small block length,this is a set of good codes for the DCC.

B. Simulation Results

We now use simulations to verify the system performance.The simulated OFDM system contains 128 data subcarriers,

and a BPSK constellation is used for symbol mapping. Thesource-to-relay, source-to-destination, and relay-to-destina-tion channels are independently generated, each consisting of16 Rayleigh distributed taps. The channels are quasi-static,meaning that they remain constant for each OFDM block, butchange independently from block to block. We further assumeperfect channel estimation at both the relay and the destination.1) Test Case 1: Assume a topology where the relay is much

closer to the source than to the destination. Let and de-note the average signal-to-noise-ratio (SNR) of the signal fromthe source at the destination and the relay, respectively. Letdenote the average SNR from the relay to the destination. Forthis topology, we assume

(6)

where is a constant.Figs. 5 and 6 depict the performance of the proposed schemes

with one1 and two receive elements at the destination, respec-tively, where 20 dB. As a comparison, the theoreticaloutage probability performance bounds assuming perfectchannel coding with BPSK input are also included, where wefollow the approach in [26] to calculate the mutual informa-tion for single-input or multiple-input OFDM systems withphase-shift keying (PSK) constellations in fading channels. Anoutage occurs if the total mutual information at the destinationafter the DCC is lower than the transmission rate.As we can see, both RR and ER outperform the noncooper-

ative case by about 1 dB. ER is slightly better than RR. Theperformance gaps of the RC–LDPC coded system to the outageprobabilities vary from 1.5 to 3 dB. This is consistent with theperformance gap in AWGN channels.2) Test Case 2: Consider a UWA network where the water

depth is 50 m, the distance between the source and the desti-nation is 1 km, and the surface buoy is deployed in the middle.A spreading loss of about in UWA transmissions isassumed, which leads to 4.5 dB, and .Fig. 7 depicts performance with different number of hy-

drophones at the surface buoy, where the destination has onehydrophone. Note that multiple hydrophones at the relay areused for reception purpose only, and the relay has only onetransducer for transmission. Clearly, as the number of hy-drophones increases at the relay, the performance of dynamiccoded relay improves. With four hydrophones, there is 2-dBgain at PER 10 for RR and 2.5 dB for ER relative to thenoncooperative transmission.

IV. ONE DESIGN EXAMPLE BASED ON LAYERED ERASURE-AND ERROR-CORRECTION CODING

The OFDM–DCC design in Section III suggests rate-com-patible channel coding across multiple OFDM blocks. In manyexisting designs of underwater OFDM transmissions, channelcoding has been applied on a block-by-block basis [20], whichis also the case for the OFDM modem implemented in [19].

1Using the signal from one hydrophone to compute the soft log-likelihoodratio (LLR) information from two or multiple data streams in the ER case fol-lows the formation of a maximum a posteriori (MAP) detector. For example,see the MAP detector in [24] for a similar problem with two data streams su-perimposed together at the receiver.


TABLE IEXPERIMENT-RELATED PARAMETERS

Without altering the channel coding performed within eachOFDM block, a separate layer of erasure-correction coding canbe applied across OFDM blocks [27]. Rateless coding has beensuggested in [4] and [5] to enable the DCC operation. However,rateless coding requires a large number of blocks, which mightnot be suitable for UWA communications. Next, we suggest anapproach to use erasure-correction coding over a finite numberof blocks.

A. Code Design

Here, we use nonbinary linear coding to perform the in-terblock erasure-correction coding. Operating over GF ,every eight bits are grouped into one byte before encoding.First, divide one packet into information blocks, where eachblock contains symbols in GF . Denote the th symbol ofthe th block as . An encoder which generates codedsymbols from information symbols is applied as

...

.... . .

. . ....

... (7)

where is a primitive element in GF [28]. After the erasure-correction coding, each set of symbolswill be forwarded to the error-correction channel encoder togenerate the coded symbols to be modulated in the th OFDMblock.The OFDM blocks which fail in channel decoding will be

discarded (each block has its own CRC flags, as done in, e.g.,[19]). Thanks to the Vandermonde structure of the code gener-ation matrix in (7), any square submatrix drawn from it is guar-anteed to be nonsingular and thus invertible in the finite field.Hence, as long as the relay collects correctly decoded blocks,all the information symbols can be recovered, and the wholepacket can be regenerated. Note, however, that this layered de-coding approach is expected to be suboptimal relative to a jointdecoding approach where all accumulated blocks are decodedjointly.

B. Implementation on OFDM Modem

We have implemented the OFDM–DCC scheme with layeredcoding and RR cooperation into the modem prototype [19]. The

modem has the parameters shown in Table I. For simplicity, weadopt the least-squares-based channel estimator; more imple-mentation details can be found in [19].Each OFDM block carries 80 B of payload data [19]. Here,

we set and for the erasure-correction coding,and hence each packet has 640 B of information data.Twomajor tasks on implementation have been accomplished.• Erasure-correction decoding. Gaussian elimination is usedfor matrix inversion over the finite field for erasure-cor-rection decoding. Thanks to the small code length, a verysmall computational overhead is added to the modem pro-cessing. Specifically, it only takes 0.111 ms to decode onecodeword with 8 symbols in GF , using the TIDSP chip TMS320C6747 [19]. To decode the packet of640 B, the total time is only 8.88 ms, much smaller thanthe OFDM block duration.

• Synchronization. To achieve the block-level synchroniza-tion, as described in Section II-A, two changes have beenmade to the modem: 1) the relay performs a fine synchro-nization step to locate the starting time of each OFDMblock that it has received [30]; and 2) after correctly de-coding the packet, the relay needs to hold on its transmis-sion for seconds. A timer is issued, and when it ex-pires, a hardware interrupt is triggered that will get thetransmission of the OFDM blocks actually started. Thisway, the relay can align its transmission to achieve theblock-level (quasi-) synchronization for the OFDM blocksreceived at the destination from both the source and therelay.

C. Experiment in Swimming Pool

The experiment was carried out in August 9, 2012, in theBrundage Pool at the University of Connecticut, with the setupshown in Fig. 8. With the source node and the destination nodeset in two sides of the pool, the relay node was put in three dif-ferent locations in the middle, as shown in Fig. 9. The distancefrom the source node to the destination node is about50 ft. Relay node was placed between the source node and thedestination node. According to its distance to the source node ,three possible relay locations were included: , , andaway from the source node, respectively. In all the three set-tings, the relay node has the same transmit power as the sourcenode. Since the source, the relay, and the destination are on aline, . The value of is set to be one in thisexperiment as .In total, four scenarios were tested: no relay, and one relay at

three different locations. In each scenario, 40 packets of datawere recorded at the destination node , where each packethas 18 OFDM blocks with interblock erasure-correctioncoding, as specified in Section IV-B. The input SNRs as mea-sured at the received blocks without relay are high, e.g., about20 dB. Fig. 10 shows the channel statistics of one packet fromthe scenario of relay at away from the source node. Clearly,the RR cooperation leads an equivalent multipath channel thatis stronger than the original multipath channel through signalsuperposition.We now add white Gaussian noise of different levels to the 40

recorded packets in each test scenario. Fig. 11 plots the PER per-


Fig. 8. Experimental setup in the swimming pool.

Fig. 9. There is only one relay used between the source and the destination.The relay can be placed at different locations, as marked.

Fig. 10. Samples of the estimated channels without the relay cooperation andwith the relay cooperation.

formance in different test scenarios, as a function of the varianceof the added noise which is normalized by the variance of therecorded ambient noise in the signal band. Note that during thisexperiment, the source node has enough transmission power sothat the decoding performance at the relay is similar in all loca-tions, with . Since the noise is only added at the recordeddata set at the destination locally, the closer the relay node to thedestination, the better the PER performance becomes due to thehigher SNRs for the OFDM blocks received at the cooperationphase. This trend is clearly observed in Fig. 11.

D. Sea Experiment

The Underwater Sensor Network (UWSN) Lab at the Uni-versity of Connecticut participated in a joint experiment led by

Fig. 11. PER is obtained by adding noise to the recorded data at the destination.Note that the relay operation is done online in real time.

Fig. 12. Locations of the source (node 4), the relay (node 5), and the destination(node 9). Using the ranging function of the modems, the reported distances are:

1.63 km, 2.39 km, and 3.72 km. The water depths at thesource, relay, and destinations were about 27, 26, and 22 m, respectively.

the National Sun Yat-sen University, at the sea near the Kaoh-siung City, Taiwan, May 22–28, 2013. The OFDM–DCC exper-iment was carried out on May 26, 2013, where the source, therelay, and the destination were deployed as shown in Fig. 12.The OFDM modems were attached to the surface buoys, at awater depth of 6 m. One OFDM modem and one surface buoyduring the deployment are shown in Fig. 13.The OFDM–DCC firmware from the swimming pool test was

loaded to the OFDM modems deployed in this experiment. Intotal, 189 transmissions were transmitted, and each transmissioncontained 20 zero-padded OFDMblocks encoded using (7) with

and . The block delay was set as duringthe experiment.The waveform of one data set recorded at the destination is

shown in Fig. 14, where the received signals weremuch strongerduring the relay cooperation phase. Note also that there existedimpulsive noises, which would affect the communication per-formance for those affected blocks. Both the relay and the des-


Fig. 13. (a) OFDM modem before entering the water during deployment. (b)Buoy after being deployed.

tination decoded the received blocks online. The performanceresults are as follows.• Due to the short distance to the source, the relay decodedthe data very well. In 188 transmissions, the relay was ableto decode the whole packet with the first eight receivedblocks, and in one transmission, the relay used nine blocksto decode the packet.

• The destination kept decoding 20 OFDM blocks for eachtransmission. For each block index from 1 to 20, definethe block error rate as the ratio of the number of erroneousblocks to the total number of transmissions. As shown inFig. 15, the BLER is around 0.05 before the relay cooper-ation, and it decreases to around 0.01 after the relay coop-eration, when averaged over all 189 transmissions.The pilot signal-to-noise ratio (PSNR), defined as thesignal power at the pilot subcarriers to the power at thenull subcarriers, is shown in Fig. 16, averaged over 189transmissions. A 2.5-dB increase is observed after therelay cooperation.

Fig. 17 shows the estimated channels before and after thecooperation. For the composite channel after relay cooperation,the first cluster corresponds to the channel from the source to the

Fig. 14. One received waveform after bandpass filtering; there are some im-pulsive noises.

Fig. 15. Block error rate as a function of the block index.

destination, and the second cluster corresponds to the channelfrom the relay to the destination. It can be seen that there is a15-ms gap between the peaks of these two clusters, reflectingthe synchronization offset.In short, this is a successful demonstration of the

OFDM–DCC operation in a sea environment. With the RRstrategy, the relay improves the performance of the source todestination communication without introducing any changes tothe transmission procedure between the source and the relay.

V. CONCLUSION

In this paper, we proposed an OFDM-modulated DCCscheme for underwater relay networks with long multipathchannels. We presented two concrete design examples, onebased on nonbinary rate-compatible LDPC coding, and theother based on layered erasure- and error-correction coding.Simulations showed the performance gain as a function of the


Fig. 16. PSNR as a function of the block index.

Fig. 17. Estimated channels before and after the relay cooperation.

relay capability. Experiments in a swimming pool and in arecent sea test were carried out to demonstrate the real-timeoperation of OFDM–DCC in a three-node network.The proposed OFDM–DCC scheme is especially appealing

for UWA networks where some powerful relay nodes can beused to assist each communication between a source and a des-tination.

ACKNOWLEDGMENT

The authors would like to thank Dr. J. Huang for his contri-butions to the early discussions of this research and his help inassisting with the use of the rate-compatible nonbinary LDPCcodes [25]. They would also like to thank Dr. T. C. Yang, Dr.C.-F. Huang, and Dr. D. Huang for providing the opportunity toparticipate in the sea test in Kaohsiung, Taiwan, May 2013, andL. Wei for carrying out the OFDM–DCC experiment at sea.

REFERENCES

[1] L. Xiao, T.-E. Fuja, J. Kliewer, and D.-J. Costello Jr., “Cooperativediversity based on code superposition,” in Proc. Int. Symp. Inf. Theory,Seattle, WA, USA, Jul. 9–14, 2006, pp. 2456–2460.

[2] G. Al-Habian, A. Ghrayeb, M. Hasna, and A. Abu-Dayya,“Threshold-based relaying in coded cooperative networks,” IEEETrans. Veh. Technol., vol. 60, no. 1, pp. 123–135, Jan. 2011.

[3] Q. Li, S. Ting, and C.-K. Ho, “A joint network and channel codingstrategy for wireless decode-and-forward relay networks,” IEEE Trans.Commun., vol. 59, no. 1, pp. 181–193, Jan. 2011.

[4] J. Castura and Y. Mao, “Rateless coding for wireless relay channels,”IEEE Trans. Veh. Technol., vol. 6, no. 5, pp. 1638–642, May 2007.

[5] K. Kumar and G. Caire, “Coding and decoding for the dynamic decodeand forward relay protocol,” IEEE Trans. Inf. Theory, vol. 55, no. 7, pp.3186–3205, Jul. 2009.

[6] K. Ishibashi, K. Ishii, and H. Ochiai, “Dynamic coded cooperationusing multiple Turbo codes in wireless relay networks,” IEEE J. Sel.Top. Signal Process., vol. 5, no. 1, pp. 197–207, Feb. 2011.

[7] X. Xu, Z.-H. Wang, S. Zhou, and L. Wan, “Parameterizing both pathamplitude and delay variations of underwater acoustic channels forblock decoding of orthogonal frequency division multiplexing,” J.Acoust. Soc. Amer., vol. 131, no. 6, pp. 4672–4679, Jun. 2012.

[8] X. Xu, S. Zhou, A. K. Morozov, and J. C. Preisig, “Per-survivorprocessing for underwater acoustic communications with direct-se-quence spread spectrum,” J. Acoust. Soc. Amer., vol. 133, no. 5, pp.2746–2754, May 2013.

[9] M. Vajapeyam, S. Vedantam, U. Mitra, J. Preisig, and M. Stojanovic,“Distributed space-time cooperative schemes for underwater acousticcommunications,” IEEE J. Ocean. Eng., vol. 33, no. 4, pp. 489–501,Oct. 2008.

[10] Z. Han and Y. L. Sun, “Cooperative transmission for underwateracoustic communications,” in Proc. IEEE Int. Conf. Commun., Bei-jing, China, May 19–23, 2008, pp. 2028–2032.

[11] R. Cao, F. Qu, and L. Yang, “On the capacity and system design ofrelay-aided underwater acoustic communications,” in Proc. IEEEWireless Commun. Netw. Conf., Sydney, Australia, Apr. 18–21, 2010,DOI: 10.1109/WCNC.2010.5506306.

[12] P. Wang, W. Feng, L. Zhang, and V. Li, “Asynchronous co-operative transmission in underwater acoustic networks,” inProc. IEEE Symp. Underwater Technol., Apr. 5–8, 2011, DOI:10.1109/UT.2011.5774167.

[13] R. Cao and L. Yang, “Reliable relay-aided underwater acoustic com-munications with hybrid DLT codes,” in Proc. IEEEMilitary Commun.Conf., Baltimore, MD, Nov. 7–10, 2011, pp. 412–417.

[14] X. Cheng, F. Qu, and L. Yang, “Relay-aided cooperative un-derwater acoustic communications: Selective relaying,” in Proc.MTS/IEEE OCEANS Conf., Yeosu, Korea, May 21–24, 2012, DOI:10.1109/OCEANS-Yeosu.2012.6263434.

[15] Q. Song and M. Garcia, “Cooperative OFDM underwater acousticcommunications with limited feedback,” Int. J. Comput. Appl., vol.54, no. 16, pp. 42–46, 2012.

[16] Y. Mei, Y. Hua, A. Swami, and B. Daneshrad, “Combating synchro-nization errors in cooperative relays,” in Proc. IEEE Int. Conf. Acoust.Speech Signal Process., Philadelphia, PA, USA, Mar. 18–23, 2005,DOI: 10.1109/ICASSP.2005.1415723.

[17] C.-H. Chen, C.-L. Wang, and C.-T. Chen, “A resource allocationscheme for cooperative multiuser OFDM-based cognitive radio sys-tems,” IEEE Trans. Commun., vol. 59, no. 11, pp. 3204–3215, Nov.2011.

[18] O. Javidbakht, N. N. Alizadeh, and S.M. Razavizadeh, “Dynamic relayselection and resource allocation in cooperative networks based onOFDM,” in Proc. 11th Eur. Wireless Conf. Sustain. Wireless Technol.,Vienna, Austria, Apr. 27–29, 2011.

[19] H. Yan, L. Wan, S. Zhou, Z. Shi, J.-H. Cui, J. Huang, and H. Zhou,“DSP based receiver implementation for OFDM acoustic modems,” J.Phys. Commun., vol. 5, no. 1, pp. 22–32, 2012.

[20] B. Li, S. Zhou, M. Stojanovic, L. Freitag, and P. Willett, “Multicarriercommunication over underwater acoustic channels with nonuniformDoppler shifts,” IEEE J. Ocean. Eng., vol. 33, no. 2, pp. 198–209, Apr.2008.

[21] J.-Z. Huang, S. Zhou, J. Huang, C. Berger, and P. Willett, “Progressiveinter-carrier interference equalization for OFDM transmission overtime-varying underwater acoustic channels,” IEEE J. Sel. Top. SignalProcess., vol. 5, no. 8, pp. 1524–1536, Dec. 2011.


[22] B. Li, J. Huang, S. Zhou, K. Ball, M. Stojanovic, L. Freitag, and P.Willett, “MIMO-OFDM for high rate underwater acoustic communi-cations,” IEEE J. Ocean. Eng., vol. 34, no. 4, pp. 634–644, Oct. 2009.

[23] J.-Z. Huang, S. Zhou, J. Huang, J. Preisig, L. Freitag, and P. Wil-lett, “Progressive intercarrier and co-channel interference mitigationfor underwater acoustic MIMO-OFDM,” Wireless Commun. MobileComput., vol. 14, no. 3, pp. 321–338, Feb. 2014, DOI: 10.1002/wcm.1251.

[24] Z.-H. Wang, J. Huang, S. Zhou, and Z. Wang, “Iterative receiver pro-cessing for OFDMmodulated physical-layer network coding in under-water acoustic channels,” IEEE Trans. Commun., vol. 61, no. 2, pp.541–553, Feb. 2013.

[25] J. Huang, W. Zhou, and S. Zhou, “Structured nonbinary rate-compat-ible low-density parity-check codes,” IEEE Commun. Lett., vol. 15, no.9, pp. 998–1000, Sep. 2011.

[26] B. Lu, G. Yue, and X. Wang, “Performance analysis and design opti-mization of LDPC coded MIMO OFDM systems,” IEEE Trans. SignalProcess., vol. 52, no. 2, pp. 348–361, Feb. 2004.

[27] C. R. Berger, S. Zhou, Y.Wen, P. Willett, and K. Pattipati, “Optimizingjoint erasure- and error-correction coding for wireless packet transmis-sions,” IEEE Trans. Wireless Commun., vol. 7, no. 11, pp. 4586–4595,Nov. 2008.

[28] S. Lin and D. J. Costello, Error Control Coding, 2nd ed. EnglewoodCliffs, NJ, USA: Prentice-Hall, 2004, ch. 7.3, pp. 237–240.

[29] J. Huang, S. Zhou, and P. Willett, “Nonbinary LDPC coding formulticarrier underwater acoustic communication,” IEEE J. Sel. AreasCommun., vol. 26, no. 9, pp. 1684–1696, Dec. 2008.

[30] C. R. Berger, S. Zhou, Z. Tian, and P.Willett, “Precise timing for multi-band OFDM in a UWB system,” in Proc. Int. Conf. Ultra Wideband,Waltham, MA, USA, Sep. 24–27, 2006, pp. 269–274.

Yougan Chen (S’12–M’13) received the B.S. degreefrom the Northwestern Polytechnical University(NPU), Xi’an, China, in 2007 and the Ph.D. degreefrom Xiamen University (XMU), Xiamen, China, in2012, both in communication engineering.He visited the Department of Electrical and

Computer Engineering, University of Connecticut(UCONN), Storrs, CT, USA, from November2010 to November 2012. He has been an AssistantProfessor with the Department of Applied OceanPhysics and Engineering, XMU, since 2013. His

research interests lie in the areas of communications and signal processing,currently focusing on channel coding and cooperative communications forunderwater acoustic channels.

Zhaohui Wang (S’10–M’13) received the B.S.degree from the Beijing University of ChemicalTechnology (BUCT), Beijing, China, in 2006, theM.S. degree from the Institute of Acoustics, ChineseAcademy of Sciences (IACAS), Beijing, China, in2009, and the Ph.D. degree from the University ofConnecticut (UCONN), Storrs, CT, USA, in 2013,all in electrical engineering.She has been with the Department of Electrical

and Computer Engineering, Michigan TechnologicalUniversity (Michigan Tech), Houghton, MI, USA,

as an Assistant Professor since 2013. Her research interests lie in the areas ofwireless communications and statistical signal processing, with recent focuson the multicarrier modulation and signal processing techniques for wirelesscommunications and networking in underwater acoustic environments.Dr. Wang served as a technical reviewer for many premier journals and con-

ferences. She was recognized as an Outstanding Reviewer of 2012 by the IEEEJOURNAL OFOCEANIC ENGINEERING. In 2013, she was honored with theWomenof Innovation Award by the Connecticut Technology Council.

LeiWan (S’10) received the B.S. degree in electricalinformation engineering from Tianjin University,Tianjin, China, in 2006 and the M.Sc. degree insignal and information processing from Beijing Uni-versity of Posts and Telecommunications (BUPT),Beijing, China, in 2009. He is currently workingtoward the Ph.D. degree in the Department ofElectrical and Computer Engineering, University ofConnecticut (UCONN), Storrs, CT, USA.His research interests include physical layer

algorithm design and implementation for underwateracoustic orthogonal frequency-division multiplexing (OFDM) systems.

Hao Zhou received the B.S. and Ph.D. degrees inelectronic engineering from the University of Scienceand Technology of China (USTC), Hefei, China, in2004 and 2009, respectively.He was a Postdoctoral Researcher in the De-

partment of Electrical and Computer Engineering,University of Connecticut (UCONN), Storrs, CT,USA, from 2009 to 2013. Currently, he is a ResearchEngineer at Aquatic Sensor Network Technology,Storrs, CT, USA. His main research interests liein the areas of communication systems and digital

signal processing. His present focus is on the implementation of orthogonalfrequency-division multiplexing (OFDM) underwater acoustic modem.

Shengli Zhou (S’99–M’03–SM’11–F’14) receivedthe B.S. and M.Sc. degrees in electrical engineeringand information science from the University ofScience and Technology of China (USTC), Hefei,China, in 1995 and 1998, respectively, and the Ph.D.degree in electrical engineering from the Universityof Minnesota (UMN), Minneapolis, MN, USA, in2002.He is now a Full Professor with the Department

of Electrical and Computer Engineering, Universityof Connecticut (UCONN), Storrs, CT, USA. He has

held a United Technologies Corporation (UTC) Professorship in EngineeringInnovation (2008–2011) and the Charles H. Knapp Associate Professor in Elec-trical Engineering (2012–2013). His general research interests lie in the areas ofwireless communications and signal processing. His recent focus has been onunderwater acoustic communications and networking.Dr. Zhou has served as an Associate Editor for the IEEE TRANSACTIONS ON

WIRELESS COMMUNICATIONS (2005–2007) and the IEEE TRANSACTIONS ONSIGNAL PROCESSING (2008–2010), and is now an Associate Editor for the IEEEJOURNAL OF OCEANIC ENGINEERING. He received the 2007 Office of Naval Re-search (ONR) Young Investigator award and the 2007 Presidential Early CareerAward for Scientists and Engineers (PECASE). He is a member of the Con-necticut Academy of Science and Engineering (CASE).

Xiaomei Xu received the B.S., M.S., and Ph.D.degrees in marine physics from Xiamen University(XMU), Xiamen, China, in 1982, 1988, and 2002,respectively.She was a Visiting Scholar with the Department of

Electrical and Computer Engineering, Oregon StateUniversity, Corvallis, OR, USA (1994–1995). Shevisited the Department of Electrical and ComputerEngineering, University of Connecticut (UCONN),Storrs, CT, USA, as a Senior Visiting Scholar in2012. She is now a Full Professor with the Depart-

ment of Applied Ocean Physics and Engineering, XMU. Her research interestslie in the fields of marine acoustics, underwater acoustic telemetry and remotecontrol, underwater acoustic communication, and signal processing.

Documents

Peer-Reviewed Technical Communication