IEEE Wireless Communications • June 200744 1536-1284/07/$20.00 © 2007 IEEE

Match filters

ε^’

nth stage ofML estimation

nth stageof MPIC

The authors proposea novel joint detection methodcalled M-ML-MPIC(Modified MaximumLikelihood MultistageParallel InterferenceCanceller) to eliminate the frequency offset andMAI simultaneously.

NE X T-GE N E R AT I O N CDMA VS . OFDMA FOR

4G WIRELESS AP P L I C AT I O N S

INTRODUCTION

Orthogonal frequency-division multiplexing(OFDM) communications systems can providehigher frequency efficiency and are not sensitiveto frequency selective fading. However, theyhave several disadvantages when compared toother existing systems, such as difficulty withsubcarrier synchronization and sensitivity to fre-quency offset and nonlinear amplification, just tomention a few. In recent years, the combinationof a code-division multiple access (CDMA)scheme and OFDM paradigm, called a multicar-rier (MC) CDMA system [1, 2], has drawn a lotof attention in the field of radio communicationssystems. MC-CDMA is a form of OFDM, and issometimes also called CDMA-OFDM. It hasone major advantage in that it can lower thesymbol rate in each subcarrier so that longersymbol duration makes it easier to quasi-syn-chronize transmissions. Furthermore, MC-CDMA-based systems have the spectralefficiency of CDMA systems and the robustnessagainst intersymbol interference (ISI) of OFDMsystems. Therefore, they are viewed as promisingcandidates in the fourth generation (4G) and/orfuture generations of wireless communicationsystems. However, before MC-CDMA systemsbecome a commodity, several issues remain to

be resolved. Some of the most important sourcesof performance degradation in MC-CDMA sys-tems are carrier frequency offset and multipleaccess interference (MAI). The frequency offsetcauses intercarrier interference (ICI), whichthen substantially degrades the system’s perfor-mance [3]. Several approaches have beenaddressed to overcome this drawback. For exam-ple, Y. Jiao et al. [4] use the correlation betweenthe received streams and the correspondingspreading codes to find the frequency offset.However, as the fading effect increases, theaccuracy of estimation deteriorates considerably.To overcome this problem, J. H. Deng et al. [5]propose to use either additional pilots or hard-ware blocks such as phase locked loops to miti-gate the ICIs; unfortunately, however, this will inturn degrade the data transmission rate andincrease costs for the synchronization mecha-nism. It is important to recall that when MC-CDMA systems suffer from MAI, there is also asevere performance deterioration that follows. Inmost of the earlier work done by researchers,the frequency offset estimation and compensa-tion method of OFDM systems has been used inorder to eliminate MAI and frequency offset.But frequency offset and MAI are quite related.This is mainly due to the fact that MAI and fre-quency offset estimations are not perfectly accu-rate, and deviations can still occur. On the otherhand, the MC-CDMA systems’ sensitivity to fre-quency offset makes their performance declinedrastically, while the frequency offset also makesthe MAI change. While many schemes havebeen proposed for OFDM systems in order toestimate the frequency offset, they cannot bedirectly applied to MC-CDMA systems. This ismainly due to the nature of MAI and the corre-lation between the different subcarriers’ data. Indirect sequence CDMA (DS-CDMA) systems,on the other hand, many detection schemes havebeen proposed to eliminate the MAI interfer-ence problem. However, when these schemes areapplied to MC-CDMA systems directly, theirperformance becomes worse even in the pres-ence of a small frequency offset, as outlined in[6]. As a consequence, we do believe that fre-quency offset and MAI should be considered

YANJUN HU, ANHUI UNIVERSITY

AZZEDINE BOUKERCHE, UNIVERSITY OF OTTAWA

ABSTRACTWhile multicarrier CDMA techniques are

used to reduce interference and improve theperformance of the system in fading channel,carrier frequency offset and multiple accessinterference remain major obstacles for a multi-carrier CDMA system’s performance. In thisarticle we propose a novel joint detectionmethod called Modified Maximum LikelihoodMultistage Parallel Interference Canceller (M-ML-MPIC) to eliminate the frequency offset andMAI simultaneously. The main idea of ourapproach is to combine PIC multiuser detectionand frequency offset estimation based on a maxi-mum likelihood function with guard interval. Wediscuss our scheme and report on its perfor-mance using a set of simulation experiments.

A NOVEL JOINT DETECTION OF FREQUENCY OFFSETAND MAI FOR MC-CDMA SYSTEMS

HU LAYOUT 6/6/07 12:19 PM Page 44

IEEE Wireless Communications • June 2007 45

jointly. Recently, some joint methods have beendiscussed [7–12]. O. Takyu et al. [7] have ana-lyzed the effects of frequency offset compensa-tion with minimum mean square eerror basedmultiuser detection (MMSE-MUD) for MC-CDMA systems in a quasi-synchronous uplink.M. A. Visser et al. [8] have proposed a decorre-lator-based joint MUD and frequency offset cor-rection, while a parallel interference cancellation(PIC) receiver with a frequency offset estimationtechnique has been proposed in [9]. Feng-TsunChien et al. [10] presented an iterative approachbased on the Expectation-Maximization (EM)algorithm to estimate system parameters. B.Smida et al. [11] proposed an MC-CDMA space-time receiver. A genetic algorithm to approachfrequency offset estimation and MUD was pre-sented in [12].

In this article we propose a novel joint detec-tion method that we call Modified MaximumLikelihood Multistage Parallel Interference Can-celler (M-ML-MPIC) to correct the frequencyoffset and MAI simultaneously. Our approach isbased on the work done in [9, 13], combiningPIC MUD with frequency offset estimationbased on a maximum likelihood function with aguard interval.

The remainder of this article is organized asfollows. The system model of MC-CDMA withfrequency offset is given. The maximum likeli-hood estimation algorithm based on a guardinterval is analyzed. We present our proposedjoint detection method to eliminate both the fre-quency offset and MAI simultaneously. Numeri-cal simulation results are also discussed. Wethen conclude the article.

A SYSTEM MODEL OF MC-CDMA WITHFREQUENCY OFFSET

In this section we discuss the MC-CDMA basedsystem model we have used. In our model theMC-CDMA transmitter spreads the original datastream over different subcarriers using a givenspreading code in the frequency domain. In otherwords, a fraction of the symbol corresponding to achip of the spreading code is transmitted througha different subcarrier. In Fig. 1 we illustrate thestructure of the transmitter and receiver of MC-CDMA, also discussed in [14].

We consider a discrete-time baseband-equiva-lent model of a time synchronous MC-CDMAsystem with K users using N chip signature codes.N is also equal to the number of subcarriers.

Assuming that when there is no frequency offset,at the receiver the observed signal (which is thesuperposition of the signals corresponding to Kusers) is x(m), in the presence of carrier fre-quency offset, x(m) becomes x ′(m) =x(m)ej2πεm/N, where m = N – G, G is the lengthof guard interval; ε is the frequency offset nor-malized by the subcarrier spacing. To recoverthe transmitted symbols, the receiver applies N-fast Fourier transform (FFT) to the received sig-nal.

MAXIMUM LIKELIHOOD ESTIMATIONALGORITHM BASED ON THE

GUARD INTERVALIn this section we wish to present the maximumlikelihood (ML) frequency offset estimationscheme we use in our joint detection scheme.The proposed scheme is an extension of theguard-interval-based ML detector proposed forfrequency offset estimation in OFDM systems.While it is true that ML frequency offset estima-tion schemes have been applied to the OFDMsystem in the past, due to the ambiguity of thesubcarrier, the estimate range is limited to theinterval of the subcarrier, which represents aserious limitation to OFDM systems in general.However, this amount of correctable frequencyoffset is sufficient in MC-CDMA. The MC-CDMA system reaches the highest bit error rateif the amount of frequency offset is close to f ofthe subcarrier spacing. Therefore, this scheme issufficient to correct the frequency offset in MC-CDMA. Thus, the ML frequency offset estima-tion is certainly applicable to MC-CDMAsystems, as already outlined in [8, 13]. Here, thereceiver is assumed to be perfectly synchronizedwith the transmitters, so the receiver estimatesthe fading amplitude and phase perfectly eventhough the frequency offset causes a phase rota-tion in each subcarrier. The likelihood functionfor the frequency offset for an MC-CDMA sys-tem is fully discussed in [9], and the mean valueof the likelihood function is computed as fol-lows:

(1)

It is clear that the likelihood function reachesan absolute maximal value at the normalizedmean value of the frequency offset ε equal tozero. In order to find the frequency offset, the

EN

f

f m

offset

offsetn

N[ ]

cos( )

( )Λ =

−

+ −=

1 1 2

102 2

1

π∑∑∑

=m

M

1

.

The proposedscheme is an

extension of theguard interval basedmaximum likelihood

detector that is proposed for

frequency offset estimation in

orthogonal frequencydivision multiplexing

systems.

n Figure 1. MC-CDMA scheme: a) transmitter; b) receiver.

(a) (b)

Σ

ck(1)

sk(t)

user k

dk(t)Σ

dk,n

exp(j2πf1t)

ck(N) exp(j2πfNt)

exp(-j2πf1t)

(*)T

exp(-j2πfNt)

ξk(1)

ξk(N)

ξk(i) combining/equalizationcoefficients

r(t)

(*)T

HU LAYOUT 6/6/07 12:19 PM Page 45

IEEE Wireless Communications • June 200746

likelihood function is therefore minimized byusing the gradient method (i.e., by tracking thederivative of the likelihood function with respectto the estimation of the carrier frequency).

Let us now suppose that a special samplingpoint θ is the start point of an MC-CDMA sym-bol, the G sample data before θ the location of aprotection interval, and the G sample data afterθ – N the copy of the guard interval. Thus, wecan construct the likelihood function as follows:

(2)

where

is the noise vector; hence, the estimation valueof the frequency offset is

(3)

PROPOSED M-ML-MPIC JOINT DETECTION

Since PIC is most applicable to MUD, we pro-pose to combine the ML estimation algorithmbased on a guard interval with a modified PICreceiver based on work discussed in [9]. Ourproposed modified PIC receiver (M-ML-MPIC)with ML frequency offset estimation is shown inFig. 2.

As outlined in Fig. 2, the initial step of ourapproach consists of a conventional matched fil-ter that is used to estimate all users’ informa-tion bits without any consideration of thefrequency offset. Next, the first stage of PIC isused to regenerate all of the users’ received sig-nals from the estimated information bit. Theoriginal received signal is then subtracted fromthe MAI, which is considered to be the other

users’ received signals. The subtracted signal,which is considered to be MAI-free, is used toestimate the user’s frequency offset in the nextstage. The estimated frequency offset and MAIfree signal are then fed to the matched filter todetect the information bit. Finally, the estimat-ed frequency offset is fed to the next stage ofPIC in order to adjust the frequency of theoscillator at the modulator. In the downlink, allusers will require only one frequency compensa-tion scheme. In addition, users’ signals will notrequire despreading before the frequency detec-tion process. In the uplink, the signal receivedfrom each user in the system has a differentvalue of frequency offset. All users’ signals aredespread before the frequency offset estimationand respread after the frequency compensation.This allows us to separate user signals fromeach other. After despreading, the single-userreceived signals are fed into the frequency offsetestimator. The estimated frequency offset isthen used to modulate the single-user receivedsignals in order to remove the effect of frequen-cy offset. The modulated received signals arethen despread.

SIMULATION RESULTS

The performance of our proposed joint detec-tion method (M-ML-MPIC) was compared tothat of a conventional multistage PIC with MLfrequency offset estimation (ML+PIC), whichwas proposed in [9]. We also made a comparisonto another 4G proposal for OFDMA in the sameenvironment.

The simulation model was a synchronousMC-CDMA with binary phase shift keying(BPSK) modulation in a Rayleigh fading chan-nel; the power was controlled perfectly, andthe number of subcarriers (processing gain)was N = 64. The values of the normalized fre-quency offset for each user were randomly gen-erated. The performance of M-ML-MPIC,ML+PIC, and conventional OFDMA werecompared in terms of bit error rate. Given usernumber K = 8, the comparison of bit errorrates with different signal-to-noise ratios(SNRs) is shown in Fig. 3. Given SNR = 8.0dB, the comparison of bit error rates with dif-ferent user number K is shown in Fig. 4. Asyou can see, the results indicate clearly thatour method yielded better performance thanML+PIC. In contrast, using both MUD andfrequency offset estimation, the MC-CDMAperformance is better than that of the OFDMAsystem, because the MAI is the major degrada-tion factor of MC-CDMA.

CONCLUSION

We have proposed in this article a joint detec-tion method called M-ML-MPIC to correct fre-quency offset and MAI simultaneously. In ourscheme we combine both PIC multiuser detec-tion and frequency offset estimation based on amaximum likelihood function with a guard inter-val. We have discussed our scheme and present-ed a set of experiments we carried out in orderto evaluate the performance of our scheme. Ourresults show that our joint detection method

ˆ ( ) *( )επ

πε

θ

θ= ′ ′ −

= − +∑1

22

1

phase x m e x m Nj

m G

=′ ′ −

− = − + 1

21

2

1

π

πε

θtan

Im{ ( ) *( )}x m e x m Nj

m G

θθ

πε

θ

θ

∑

∑ ′ ′ −= − +

Re ( ) *( )}x m e x m Nj

m G

2

1

ρ =′

′ +

E x m

E x m E n mn m

( )

( ) ( ), ( )

2

2 2

Λx

m G

jx m e x

' ( , )

( )Re{ ( )

θ ε

ρθ

θπε

=

− ′ ′= − +∑ 2 1

1

2 **( }

( ) *(

m N

x m e x mj

− −

− ′ −

ρ

πε 2 NN )2

n Figure 2. Proposed maximum likelihood frequency offset estimation com-bined with parallel interference cancellation receiver.

Decisionε^

First stageof ML

estimation

r(t)

Match filters

Match filters

First stageof MPIC

ε^’

nth stage ofML estimation

nth stageof MPIC

HU LAYOUT 6/6/07 12:19 PM Page 46

IEEE Wireless Communications • June 2007 47

established better performance than a conven-tional maximum likelihood multistage parallelinterference canceller. In this way, the jointdetection method enables MC-CDMA systemsto outperform ordinary OFDMA systems.

REFERENCES[1] S. Hara and R. Prasead, “Overview of Multicarrier

CDMA,” IEEE Commun. Mag., Dec. 1997, pp. 126–33.[2] L. Hanzo et al., OFDM and MC-CDMA, Wiley and IEEE

Press, 2003.[3] L. Tomba and W. A. Krzymien, “Sensitivity of the MC-

CDMA Access Scheme to Carrier Phase Noise and Fre-quency Offset,” IEEE Trans. Vehic. Tech., vol. 48, no. 5,Sept. 1999, pp. 1657–65.

[4] Y. Jiao et al., “A Low-Complex and Faster Synchroniza-tion Method for MC-CDMA Systems,” Proc. IEEE VTC,May. 2002, pp. 1482–86.

[5] J. H. Deng and T. S. Lee, “An Iterative Maximum SINRReceiver for Multicarrier CDMA Systems over a MultipathFading Channel with Frequency Offset,” IEEE Trans. Wire-less Commun., vol. 2, May. 2003, pp. 560–69.

[6] Mashury, “Performance Analysis of Multiuser Detectorsfor MC-CDMA in the Presence of Frequency Offset,”Proc. IEEE Int’l. Conf. Acoustics, Speech, and Sig. Pro-cessing, vol. 4, 6–10 Apr. 2003, pp. 548–51.

[7] O. Takyu, T. Ohtsuki, and M. Nakagawa, “FrequencyOffset Compensation with MMSE-MUD for Multi-CarrierCDMA in Quasi-Synchronous Uplink,” IEEE ICC, vol. 4,11–15 May 2003, pp. 2485–89.

[8] M. A. Visser and Y. Bar-Ness, “Joint Multiuser Detectionand Frequency Offset Correction for Downlink MC-CDMA,” GLOBECOM ’99, 1999, vol. 5, pp. 2400–04.

[9] J. Songthanasak et al., “Parallel Interference Cancella-tion Receiver with Maximum Likelihood Frequency Off-set Estimation for Uplink MC-CDMA System,” 3rd IEEEInt’l. Symp. Sig. Proc. and Info. Tech., 14–17 Dec.2003, pp. 387–90.

[10] F.-T. Chien and C.-C. Jay Kuo, “Joint Symbol Detectionand Channel Estimation for MC-CDMA Systems in thePresence of Carrier Frequency Offset,” IEEE VTC ’04-Fall,vol. 1, 26–29 Sept. 2004, pp. 430–34.

[11] B. Smida et al., “A Multicarrier-CDMA Receiver withFull Interference Suppression and Carrier Frequency Off-set Recovery,” IEEE 6th Wksp. Sig. Proc. Advances inWireless Commun., 5–8 June 2005, pp. 435–39.

[12] H.-Y. Lu and W.-H. Fang, “Joint Frequency Offset Esti-mation and Multiuser Detection Using Genetic Algo-rithm in MC-CDMA,” IEEE Int’l. Symp. Circuits and Sys.,23–26 May 2005, vol. 2, pp. 1726–29.

[13] Mashury and H. Ali, “A Guard Interval based Frequen-cy Offset Compensation Scheme for MC-CDMA Up-link,” Proc. 3rd IEEE Int’l. Symp. Sig. Proc. and Info.Tech., 14–17 Dec. 2003, pp. 375–78.

[14] S. Hara and R. Prasad, “Design and Performance ofMulticarrier CDMA System in Frequency-SelectiveRayleigh Fading Channels,” IEEE Trans. Vehic. Tech.,vol. 48, no. 5, Sept. 1999, pp. 1584–95.

BIOGRAPHIESYANJUN HU (yanjunhu@ahu.edu.cn) is a full professor at theSchool of Electronic Science & Technology, Anhui Universi-ty, and vice director of Key Laboratory of Intelligent Com-puting and Signal Processing, Ministry of Education, China.She received a B.S. in electronic engineering and an M.S. incircuits and systems from Anhui University in 1989 and1992, respectively. Since 1992 she has been teaching atthe Department of Electrical Engineering and InformationScience of Anhui University. From September 1998 to2001, she studied at the University of Science and Technol-ogy of China (USTC) as a Ph.D. student, and received aPh.D. degree in communication and information systems inJune 2001. From 2002 to 2003 she was a postdoctoral fel-low at the School of Information Technology of USTC.From February 2005 to August 2006, she worked as a visit-ing research scientist at the PARADISE Research Laboratory,School of Information Technology and Engineering, Univer-sity of Ottawa, Canada. Her research interests are wirelessand mobile networking, wireless sensor networks, andwireless multimedia.

AZZEDINE BOUKERCHE is a full professor and holds a CanadaResearch Chair position in distributed simulation and wire-less and mobile networking at the University of Ottawa. Heis the founding director of tje PARADISE Research Labora-

tory at the university. Prior to this, he held a faculty posi-tion at the University of North Texas. He worked as asenior scientist in the Simulation Sciences Division, MetronCorporation, San Diego, California. He was also employedas a faculty member at the School of Computer Science,McGill University, and taught at Polytechnic of Montreal.He spent a year at the JPL/NASA Laboratory, CaliforniaInstitute of Technology, where he contributed to a projectcentered on the specification and verification of the soft-ware used to control interplanetary spacecraft operated byJPL/NASA Laboratory. His current research interests includesensor networks, mobile ad hoc networks, mobile and per-vasive computing, wireless multimedia, QoS service provi-sioning, performance evaluation and modeling oflarge-scale distributed systems, distributed computing,large-scale distributed interactive simulation, and paralleldiscrete event simulation.

n Figure 3. Given user number K = 8, the comparison of bit error rates withdifferent SNR.

Eb/N0 (dB)

20

10–4

BER

10–3

10–2

10–1

100

4 6 8 10

User number = 8

12 14 16 18

No offsetM-ML-MPICML+PICOFDM

n Figure 4. Given SNR = 8.0 dB, the comparison of bit error rates with different user number K.

User number K50

10–3

10–4

BER

10–2

10–1

100

10 15 20 25 30

OFDMML+MPICM-ML-MPICNo offset

HU LAYOUT 6/6/07 12:19 PM Page 47