An Interference-Cancellation Scheme for Carrier ... - IEEE Xplore

IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 7, JULY 2005

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An Interference-Cancellation Scheme for Carrier Frequency Offsets Correction in OFDMA Systems Defeng (David) Huang, Member, IEEE, and Khaled Ben Letaief, Fellow, IEEE

Abstract—Recently, orthogonal frequency-division multiplexing (OFDM), with clusters of subcarriers allocated to different subscribers (often referred to as OFDMA), has gained much attention for its ability in enabling multiple-access wireless multimedia communications. In such systems, carrier frequency offsets (CFOs) can destroy the orthogonality among subcarriers. As a result, multiuser interference (MUI) along with significant performance degradation can be induced. In this paper, we present a scheme to compensate for the CFOs at the base station of an OFDMA system. In the proposed scheme, circular convolutions are employed to generate the interference after the discrete Fourier transform processing, which is then removed from the original received signal to increase the signal-to-interference power ratio (SIR). Both SIR analysis and simulation results will show that the proposed scheme can significantly improve system performance. Index Terms—Carrier frequency offsets (CFOs) correction, 802.16a, multiple access, orthogonal frequency-division multiplexing (OFDM).

I. INTRODUCTION

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ECENTLY, much research has been devoted to orthogonal frequency-division multiplexing (OFDM) [1]–[5] in broadband wireless communications for its high spectral efficiency and ability in mitigating the effects of multipath propagation. When OFDM is used in a multiple-access scenario, time-division multiple access (TDMA), code-division multiple access (CDMA), and/or frequency-division multiple access (FDMA) can be used as the multiaccess protocol. To accommodate the variable data rates and Quality of Service (QoS) requirements of multimedia communications, OFDM, with clusters of subcarriers allocated to different subscribers (normally referred to as OFDMA), has attracted much attention. For example, OFDMA has been proposed to be used

Paper approved by C. Tellambura, the Editor for Modulation and Signal Design of the IEEE Communications Society. Manuscript received May 1, 2003; revised January 29, 2004 and June 15, 2004. This work was supported in part by the Hong Kong Telecom Institute of Information Technology and in part by the Hong Kong Research Grant Council. This paper was presented in part at the 14th IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications, Beijing, China, September 2003. D. Huang was with Center for Wireless Information Technology, Electrical and Electronic Engineering Department, The Hong Kong University of Science and Technology, Kowloon 190, Hong Kong. He is now with the Department of Electronic Engineering, Tsinghua University, Beijing 100084, China (e-mail: [email protected]). K. B. Letaief is with the Center for Wireless Information Technology, Electrical and Electronic Engineering Department, The Hong Kong University of Science and Technology, Kowloon 190, Hong Kong (e-mail: [email protected]). Digital Object Identifier 10.1109/TCOMM.2005.851558

in wireless metropolitan area networks (MANs) [2], satellite communications [3], and cable television system (CATV) data networks [4]. In OFDMA systems, sampling clock frequency discrepancies, carrier frequency offsets (CFOs) induced by Doppler effects and/or poor oscillator alignments, and time delay caused by multipath and nonideal synchronization, will destroy the orthogonality among different subcarriers. Furthermore, they introduce intercarrier interference (ICI), as well as multiuser interference (MUI) [5], [6]. Symbol-sampling discrepancies can often be compensated for by channel estimation. For time-delay discrepancies, guard intervals, a global positioning system (GPS), and/or the downlink information can be employed to mitigate their impacts. Since the carrier frequency is often on the order of gigahertz, CFOs are normally on the order of several kilohertz, and mitigating their impacts is the most critical challenge among the problems listed above. Some schemes have been proposed to reduce the ICI in OFDM systems [7]–[10]. These schemes can be divided into two categories: Windowing and self-ICI cancellation-based approaches. The self-ICI cancellation-based approach can be regarded as a coding scheme, where only the codewords with low ICI are used. Hence, spectrum efficiency is reduced, since the coding rate is less than one [8]. The windowing approach is achieved by shaping the signals at the output of the inverse discrete Fourier transform (IDFT) by a window. This scheme normally results in signal-to-noise power ratio (SNR) loss and ICI in the case of no CFOs [9]. Thus, all these schemes may not be suitable for use in OFDMA systems because of the disadvantages mentioned above and the necessary coordinations to be maintained among multiple subscribers. To mitigate the detrimental effects of the CFOs in OFDMA systems, it is normally required that the subscriber stations (SS) are synchronized with the base station (BS) [22]. Therefore, before any uplink data transmission, a synchronization stage is performed to guarantee the residual CFOs within the range of tolerance. During normal data transmission, the SS should track the carrier frequency changes of the BS and make proper adjustments [22]. To achieve a reasonably good performance, the requirement for the synchronization between the SS and the BS is stringent, in general. For example, in 802.16a, it is required that a precision of 2% subcarrier spacing should be maintained [22]. However, this increases the cost of the SS, which is undesirable for most application scenarios. It was suggested in [12] that the CFO estimation should be performed at the BS of an OFDMA system. The CFO information can then be transmitted back to the subscribers via the downlink channel with the oscillators adjusted at the SS. However, when this technique is used

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Fig. 1.


OFDMA system model.

in mobile communications, where Doppler frequencies also induce the CFOs, the adjustments can be outdated because of the delay. Also note that the requirement to transmit the CFOs information induces extra load for the downlink transmission. In this paper, we employ a two-stage approach to deal with the CFOs issue in OFDMA systems. Before the uplink data transmission, a coarse synchronization stage is performed at the SS to adjust the CFOs within a tolerable or reasonable range with the aid of any well-known CFO-estimation techniques [11]–[17]. In the second stage, an advanced signal-processing technique is employed in the BS to further mitigate the impact of the residual CFOs during normal data transmission. Due to the use of the signal-processing technique, the requirement of the coarse synchronization can be very loose, and this results in a low-cost SS transceiver. Furthermore, the possibility that synchronization adjustment is required during the normal data transmission is also reduced, which results in high data-transmission efficiency. Several approaches have been proposed to operate along this line. In [6], the CFOs are compensated at the BS for each subscriber using the single-user detector, where the sampled sequence is compensated for in the time domain, and then discrete Fourier transform (DFT)-processed for each subscriber. As a result, multiple DFT blocks, each for one subscriber, are used. However, the complexity of DFT processing is a major concern for system implementation [18]. To reduce this complexity, Jihoon et al. [19] used a post-DFT processing technique by employing the fact that time-domain multiplication is equivalent to frequency-domain circular convolution. Both the Choi–Lee–Jung–Lee (CLJL) scheme1 and the single-user detector cannot significantly reduce the ICI and/or the MUI. To do so, multiuser detection can be used [20]. In [20], an iterative algorithm is employed, where the detectors or decoders are used to tentatively restore the original symbols during each iteration. The interference is then generated and removed from the received signal. Unfortunately, the problem of error propagation can be severe in this case. In addition, a large number of iterations may be required to achieve a reasonably good performance. For example, eight iterations are used in [20]. In this paper, we propose a new iterative interference-cancellation scheme to be used in the BS to significantly reduce the MUI in an OFDMA system. In the proposed scheme, the original signals are tentatively restored using the CLJL scheme before the detection or the decoding process. As a result, error propagation will not occur. Analytic and simulation results will show that within only one iteration, MUI can be significantly

reduced with a good system performance. Simulation results also show that the performance of the proposed scheme is much better than the CLJL scheme. Furthermore, our scheme can make the coarse synchronization requirement between the SS and the BS less stringent. With the aid of the proposed scheme, the residual CFO values after the coarse synchronization can be as large as 20% of the subcarrier spacing. Compared with the 2% of the subcarrier spacing requirement in 802.16a [22], the improvement is significant. Simulation results also show that the proposed scheme is robust against CFO estimation errors. When the received signal power of a specific subscriber is significantly larger than that of other subscribers, the MUI induced by this subscriber can be relatively large, which results in significant performance degradation for other subscribers. As a result, power control should be used with the proposed scheme. In this paper, it will be shown that the requirement of power control is not stringent. For example, a 10 dB power difference can be tolerated. The rest of this paper is organized as follows. In Section II, we present the system model, along with the single-user detector and the CLJL scheme. The signal-to-interference power ratio (SIR) analysis for the CLJL scheme is presented in Section III. In Section IV, the proposed scheme is introduced and analyzed. Further discussions about the proposed method are given in Section V. Finally, simulation results and concluding remarks are presented in Sections VI and VII, respectively.

1Throughout this paper, we will refer to the method in [19] as the CLJL scheme.

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II. SYSTEM MODEL We consider an OFDMA system with subscribers, where each SS communicates with the BS through an independent multipath channel, as shown in Fig. 1. For simplicity, we assume that both time synchronization and sampling are ideally subcarriers in performed. We further assume that there are each OFDM symbol, and one subcarrier can be only allocated to one subscriber. The information symbol for the th subscriber at the th subcarrier is denoted by , , where is the set of subcarriers assigned to subscriber . Then, and , for . In the OFDMA samsystem, the length of the guard interval is equivalent to ples, and assumed to be longer than the maximum channel delay spread. After IDFT processing and guard-interval insertion at the transmitter, the time-domain sequence of the th subscriber is given by

HUANG AND LETAIEF: AN INTERFERENCE-CANCELLATION SCHEME

Fig. 2.

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Single-user detector for an OFDMA system.

After passing through the channel, the th subscriber’s signal is as follows: (2) where “ ” denotes linear convolution, and is the th subscriber’s channel impulse response (CIR). It is assumed that is nonzero only for , where is the maximum channel delay spread. By taking into account the CFOs and the additive noise, the received baseband signal is given by

where

, , and for any

function . For convenience, we can rewrite (5) into a vector form as follows: (6.1) (6.2)

(3) where , denotes the th subscriber’s CFO normalized by the subcarrier spacing, and is the additive white Gaussian noise. In the single-user detector (as shown in Fig. 2) and for the th is multiplied by a timesubscriber, the received sequence domain sequence before the DFT processing. After the multiplication and guard-interval removal, the signal at the th branch is then given by

denotes circular convolution, ,

where

, , , , and in the superscript denotes transpose. In (6.2), the first term is the th subscriber’s received signal, the second term is MUI, and the third term is the additive noise. The th subscriber’s received signal can then be represented by an vector as follows: (7)

(4) In the above equation, the first term is the signal for the th subscriber, the second term is MUI, and the third term is the additive noise. In the single-user detector, one DFT block is needed for each subscriber to detect the information symbols. To reduce the required number of DFT blocks, the CFOs can be compensated for in the frequency domain. In the CLJL scheme [19], after the guard-interval removal and DFT processing of in (3), the received signal is as follows:

(5)

is the frequency-domain representation of , , restoring from can be achieved as follows: Since

(8) and . When the CFO values are small compared with the subcarrier spacing, the received th subscriber’s power is mainly concentrated in the prescribed subcarrier positions. We can then use to replace in (8) to obtain , where is a diagonal matrix, and where

We note that here acts as a filter, which keeps most of the th subscriber’s received signal power and eliminates most of

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other subscribers’ power. As a result, from (6.2) and (8), the subscriber’s signal for the CLJL scheme is given by2

th

The MUI from the th subscriber to the th subscriber at the th subcarrier is also given in the Appendix, and the MUI power is as follows:

(9.1)

(13)

(9.2)

Using (11)–(13), the SIR for the th subscriber at the th subcarrier can be obtained as follows:

In (9.2), the first term includes both the signal for the th subscriber and ICI. The second term is MUI, and the third term is the additive noise. III. SIR ANALYSIS FOR THE CLJL SCHEME Previous work published so far did not give the SIR analysis for the CLJL scheme. Hence, this section provides such an analysis. Throughout this section, we assume that the MUI and the ICI are independent and Gaussian distributed. This is a reasonable assumption as long as the number of subcarriers for each subscriber is large enough. For the CLJL scheme, we can use (9.2) to obtain the th subscriber’s received signal power, ICI, and MUI. From the first term of (9.2), the received th subscriber’s signal at the th subcarrier is as follows:

(14)

When all the subscribers’ average received signal powers are the same at the BS, the SIR for the th subscriber at the th subcarrier is as follows:

(15) (10) As a result, the received signal power for the the th subcarrier is given by

th subscriber at

For comparison, the SIR performance of the single-user detector at the th subscriber and th subcarrier is given as follows:

(16)

(11) denotes the norm of , and denotes the average where of . The ICI for the th subscriber at the th subcarrier is given in the Appendix, and the ICI power is as follows:

where

is the variance of the interference from the th subscriber to the th subscriber at the th subcarrier. When all the subscribers’ received signal powers are the same, the SIR for the th subscriber at the th subcarrier is then as follows: (17) (12) 2Besides

using (9.1) to compensate for the CFOs, where the noise term is ignored, we can also optimally restore based on some criterion such as minimum mean-square error (MMSE). For example, the th subscriber’s signal can be directly estimated from the received signal using an optimal linear estimator. However, the mathematical development of the estimator is tedious, and this estimator is very complex due to the requirement of the realtime inversion of a large matrix.

Y

R

m

In the following, we consider an OFDMA system with to compare the SIR performance of the single-user detector and the CLJL scheme. Each subscriber is allocated 16 subcar. The CFOs are , , riers , and , respectively. We consider two kinds of subcarrier allocations, block allocation and interleaved


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tentatively [this can be seen by comparing (9.1) with (19)]. The proposed scheme can also be regarded as a parallel interference cancellation (PIC) scheme [21]. But in contrast to the conventional PIC, the proposed scheme does not use a detector or a decoder to tentatively restore the original symbol. In the following, we analyze the SIR performance of the proposed scheme. By putting (6.2) into (18), we have

(20) By substituting (20) into (19), the restored signal at the th loop is then as follows:

Fig. 3.

SIR performance for the single-user detector and the CLJL scheme.

allocation. In the block allocation, the spectrum is uniformly partitioned into blocks of subcarriers with each block assigned to one subscriber. In the interleaved allocation, we uniformly interleave the subcarriers across all the subscribers. The SIR performance [based on (15) and (17)] is as shown in Fig. 3. It can be seen that the CLJL scheme is always better than the single-user detector, even though it has ICI. This can be further justified by the simulation results presented in [19]. IV. INTERFERENCE CANCELLATION In this section, based upon the principle of interference cancellation, we propose a scheme (as shown in Fig. 4) to further reduce the MUI. The proposed scheme can be best described as an algorithm where the interference cancellation is performed denoting the restored signal in an iterative fashion, with at the th step. Interference Cancellation Algorithm Initialization: Set and for . Loop:

(21) In the above equation, the first term is the th subscriber’s signal and ICI, the second term is MUI, and the third term is the additive noise. By comparing (21) with (9.2), it can be seen that the signal power and ICI in the proposed scheme are always the same as those of the CLJL scheme. As a result, the signal component is exactly the same as that given by (10). After the coarse synchronization, the CFO values are normally small. As a result, we have the following approximation:

(22)

Set for

(18)

for

(19)

By comparing (21) with (9.2), it can also be seen that in in (21) the second term of (9.2) is replaced by . As a result, we can use (13) to calculate MUI with for replaced by , where is the th element of . Assume that the noise and th step the interference are independent, the SIR at the and th subcarrier is given by

Go back to Loop. and only An example of the proposed scheme with one iteration is shown in Fig. 5. In the proposed scheme, after DFT processing, circular convolution is used to generate the interference, which is then removed from the original signal. In each loop, the interference is cancelled out using (18). After that, the CLJL scheme is used to produce the original signal

(23)

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Fig. 4. Block diagram of the proposed scheme.

Fig. 5. Interference cancellation and CFOs compensation with two subscribers.

where

is the variance of the additive noise. Then, we have

(24) As a result, at the th loop, the power of MUI from the th subscriber to the th subscriber at the th subcarrier is as follows:

(25) We can then calculate the SIR of the proposed scheme using the following two equations: (26) (27)

We denote the th subscriber’s SNR at the th subcarrier . It can then be seen from (25)–(27) that when by SNR SIR SNR SNR for all and , the SIR performance will be improved along with the progress of the iterative algorithm. When the CFO values are large, can be very small, and the SIR may not be improved SIR by the proposed scheme. This shows the importance of the coarse synchronization stage. From (25), it can also be seen that when both the received signal power and the CFO value of a specific subscriber happen to be large, the MUI induced by it to other subscribers may be very large. This shows that power control should be used in the proposed scheme. Fortunately, we will show in Section VI that the requirement of power control is not stringent. When the SNR value is large and the noise is negligible , the SIR performance of the proposed scheme is as shown in Fig. 6, using the same setup as that in the previous section. Compared with the CLJL scheme, it can be seen that the proposed scheme achieves much better performance. In fact, after only one iteration, the SIR is more than 30 dB for both the block and the interleaved allocations. With the same setup as that in Fig. 6, Fig. 7 shows the average SIR performance of the proposed scheme versus different SNR values. It can be seen that the performance of the proposed scheme is always better than the CLJL scheme. For the proposed scheme with one iteration, when the SNR is less than 25 dB, the SIR is much larger than the


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introduction, coarse synchronization is performed to reduce the CFO values within a tolerable or reasonable range. This implies that the received signal power for a specific subscriber is mainly concentrated in the prescribed subcarrier positions. By exploiting this fact, the training symbols for different subscribers can be transmitted simultaneously. For example, we can use two OFDM symbols [15] to estimate the CFO values. and to In this case, we use denote the received signals at the th subscriber’s subcarrier positions of the first and the second received training OFDM symbols, respectively. The CFO value for the th subscriber can then be obtained as follows:

(28)

Fig. 6. SIR performance of the proposed scheme.

where

in the superscript denotes conjugate.

B. Subcarrier Allocations

Fig. 7. Average SIR performance of the proposed scheme with different SNR values.

SNR. This SNR range corresponds to the one of most practical interest. As a result, we can expect that the impact of the CFOs on the performance of practical systems can be significantly reduced using the proposed scheme.

V. DISCUSSIONS A. CFO Estimation All the schemes (i.e., the single-user detector, the CLJL scheme, and the proposed scheme) require knowledge of the CFO values, which can be obtained using training signals. When the training signals are transmitted alternately from each subscriber, the CFO estimation schemes originally proposed for OFDM systems [12], [15] can be employed. However, in this case, the transmission efficiency is low due to the fact that a long total training period is required. As mentioned in the

It is well known that OFDM systems can take advantage of the frequency-domain diversity by using coding and interleaving. To guarantee a high diversity gain, the fading of distinct subcarriers should be made independent. The coherent bandwidth of the wireless channel is normally much larger than the subcarrier spacing of an OFDM system. As a result, when block allocation is employed in OFDMA systems, the correlation between different subcarriers in a specific subscriber would be quite large, and this results in a low diversity order. Using interleaved allocation, with subcarriers allocated as far as possible, the OFDMA system can take advantage of the frequency-domain diversity better. Besides frequency-domain diversity gain, subcarrier allocations also have an impact on the SIR induced by the CFOs. When the CFO values are large, the SIR performance of the block allocation could be much better than that of the interleaved allocation. This could result in a poorer system performance for the interleaved allocation. However, as will be seen from the simulation results, such CFO values are normally as large as 30% of the subcarrier spacing, which is much larger than the requirement of 802.16a [22]. C. Circular Convolution Complexity Reduction In general, the complexity of circular convolution is higher than that of DFT processing. In the proposed scheme, its complexity can be reduced, since most of the elements to be convoluted are zero. In (18) and (19), both and only have nonzero elements. Furthermore, and after the coarse synchronization, most elements in are quite small and can be taken as zeros.3 For example, th element of is given by the (29)

3We

note here that this fact is also employed and discussed in [19].

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As a result, as long as the CFO values are small, the elements are close to zero. We can then replace in the middle of by using the following vector:

(30) where is the number of elements that are not set to zero. Similarly, we can use

(31) to replace . Considering that the complexity of the circular convolution can be reduced and only one DFT block is required, the complexity of the proposed scheme is very low. However, we note that when the CFO values are large, a lot of the eleand cannot be neglected, and the comments in plexity of the proposed scheme cannot be significantly reduced. Therefore, the complexity reduction depends on the coarse synchronization stage to reduce the CFO values to a tolerable or reasonable range (e.g., 20% of the subcarrier spacing). When is small, the number of multiplications required to achieve the . As a result, the circular convolution is approximately total number of multiplications required for all subscribers in , which is independent of one iteration is approximately the number of subscribers .

Fig. 8. FER performance of the proposed scheme. The dotted lines and the solid lines denote block allocation and interleaved allocation, respectively.

VI. SIMULATION RESULTS A. FER Performance With QPSK Modulation and quaternary We consider an OFDMA system with phase-shift keying (QPSK) modulation. In the system, there are four subscribers, and each subscriber is allocated 16 subcarriers. Unless otherwise mentioned, the residual CFO values , , after the coarse synchronization are , and , which are the same as those used in Sections III and IV. We also assume that at the BS, the average received signal powers from all the SSs are the same. The channel model used here is a one-sample-spaced two-ray equal gain Rayleigh fading channel, and all subscribers’ channels are assumed to be statistically independent and perfectly known at the BS. For each subscriber, the coding scheme is a rate-1/2 convolutional code with constraint length 5, which is the same as that used in [19]. In our simulations, 10 OFDM symbols consist of one frame, and it is assumed that the channels do not vary within one frame, but vary from frame to frame. In each frame, an 8 40-block bit interleaver is employed. For the proposed scheme, only one iteration is performed. The average frame-error rate (FER) among all subscribers is shown in Fig. 8. It can be seen that for both the block allocation and the interleaved allocation, the CLJL scheme is better than the single-user detector, which can be justified by the analysis in Section III. However, note that an error floor exists in values, the performance of the both schemes. For high interleaved allocation is worse than that of the block allocation. This is due to the high residual MUI induced by the interleaved allocation. While for the proposed scheme, the performance is almost the same as that of a system without CFOs.

Fig. 9. System performance when the complexity of circular convolution is considered. The dotted lines and the solid lines denote block allocation and interleaved allocation, respectively.

Since the performance of an OFDMA system cannot benefit from the CFOs, given that all other parameters are the same, it is almost safe to say that the performance of the optimal receiver for a system with CFOs cannot be better than that of a system without CFOs. As a result, from the simulation results, we can say that optimal performance can be achieved by the proposed scheme. For the proposed scheme, it can also be seen that the interleaved allocation is much better than that of the block allocation. For example, more than 3-dB performance improve. This improvement is due to ment can be achieved at FER the high frequency-domain diversity gain achieved by the interleaved allocation. The FER performance of the proposed scheme, considering the complexity of circular convolution, is shown in Fig. 9. It can , the performance of the proposed be seen that even when scheme is significantly better than that of the CLJL scheme. To evaluate the effects of CFO estimation errors on system performance, the estimated CFO is obtained by adding the


Fig. 10. errors.

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FER performance of the proposed scheme with CFO estimation Fig. 12. FER performance of the proposed scheme with CFO estimation. The dotted lines and the solid lines denote block allocation and interleaved allocation, respectively.

When the CFO attenuation factor is less than two, good performance can be maintained for both allocations. This means that the proposed scheme can tolerate CFO values within about 20% of the subcarrier spacing, which is much larger than the 2% subcarrier spacing requirement in 802.16a. From Fig. 11, it can also be seen that for large CFO values, the performance of the block allocation is better than that of the interleaved allocation. This is due to the fact that in this case, the MUI is much larger for the interleaved allocation. B. FER Performance With DQPSK Modulation

Fig. 11.

FER performance of the proposed scheme with different CFO values.

true value of the CFO with a zero-mean independent Gaussian random variable, where the variance of the random variable can be regarded as the mean square error of the CFO estimation. Fig. 10 shows that the performance of the proposed scheme with CFO estimation errors. It can be seen that the performance is good until the standard deviation of the CFO estimation errors is increased to 0.06. This shows that the requirement of the CFO estimation is not stringent. From Fig. 10, we can also find that both the block and the interleaved allocations are robust against CFO estimation errors. To show the impact of the CFO values on the performance of the proposed scheme, we let (32) where is a parameter used to adjust the CFO values. For convenience, we refer to as the CFO attenuation factor. It can be seen from Fig. 11 that the performance of the proposed scheme decreases along with the increase of the CFO attenuation factor.

To further demonstrate the feasibility of the proposed scheme, we simulate a practical OFDMA system with the CFOs estimated using (28). To avoid the issue of channel estimation, we use differential QPSK (DQPSK) modulation with the previous OFDM symbol taken as a reference. In this case, one frame consists of 13 OFDM symbols, with the first two identical ones used for CFO estimation, and the third one taken as a reference for DQPSK modulation. In the simulations, we use a 12-ray exponentially decaying Rayleigh fading channel model. The root mean square (RMS) delay spread of the channel is set to be 1.2 samples, and the uncoded symbol rate is set to 10 Mbaud/s. The channel is time-varying and the Doppler frequency is set to 5 Hz, which is a reasonable setting for fixed wireless communications such as 802.16a. Other parameters, such as the coding and interleaving schemes, are the same as those in Part A of this section. For both the block allocation and the interleaved allocation, it can be seen from Fig. 12 that the proposed scheme is much better values. For than the CLJL scheme, especially for high the CLJL scheme, error floors appear for both allocations, which are mainly induced by the high MUI. For the proposed scheme, an error floor appears only for the block allocation. For the interleaved allocation, using the estimated CFO values, there is about 1-dB performance degradation for the proposed scheme, compared with the ideal case (without CFOs). Furthermore, when perfect CFO values are used, the performance of the proposed

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Fig. 13. control.


FER performance of the proposed scheme with imperfect power

of the fourth subscriber is in a relatively low level, the average FER performance of the first three subscribers is not impacted, although the performance of the CFO estimation is poor. This is because the MUI induced by the fourth subscriber is also small, due to its low power. On the other hand, when the received signal power of the fourth subscriber is in a relatively high level, the average FER performance of other subscribers can still be degraded, although the performance of the CFO estimation for the fourth subscriber is good. This shows that power control should be used for the proposed scheme. From Fig. 13, it can be seen that the received signal power of the fourth subscriber can be more than 10 dB higher than that of any one of the first three subscribers without much impact on their average FER performance. This demonstrates that the requirement for power control is not stringent for the proposed scheme. Using the same setup as Fig. 13, Fig. 14 shows the average FER performance of the first three subscribers versus the number of iterations in value of 15 and 20 dB. In the proposed scheme for an the simulations, interleaved allocation is employed in the prodB and dB, respectively. It posed system with can be seen that by using two iterations, the average FER performance can be improved a little bit. However, using more iterations cannot improve system performance. VII. CONCLUSION

Fig. 14. FER performance of the proposed scheme with interleaved subcarrier allocation versus the iteration times with imperfect power control.

scheme is almost always the same as that of the ideal case. This shows that there is still a potential to improve the CFO estimation algorithm employed in this paper. In Figs. 13 and 14, we demonstrate the effects when the received signal power of a specific subscriber at the BS is significantly larger or lower than that of others. In the simulations, we use a 12-ray exponentially decaying quasi-static Rayleigh fading channel model. The RMS delay spread of the channel is set to be 1.2 samples. Other system parameters are the same as those used for Fig. 12. The received signal power of the first three subscribers is set to be the same. For convenience, the ratio between the received signal power of the fourth subscriber and that of any one of the first three subscribers is denoted by . The average FER performance of the first three subscribers versus is shown in Fig. 13 for values of 10, 15, and 20 dB, respectively. It can be seen that when the received signal power

In this paper, we proposed an interference-cancellation scheme to mitigate the effects of CFOs in OFDMA systems. After coarse synchronization between the SSs and the BS, the proposed scheme can be used at the BS to significantly reduce MUI induced by the residual CFOs. Both SIR analysis and simulation results show that the proposed scheme can tolerate relatively large residual CFO values, which enables a low-cost SS transceiver. By employing the proposed scheme, the interleaved subcarrier-allocation scheme can be used to fully take advantage of the frequency-domain diversity of OFDMA systems. Simulation results also show that the proposed scheme is robust to CFO estimation errors. Furthermore, even though power control is required in the proposed scheme due to the nature of MUI, its requirement is not stringent, as shown by the simulation results. APPENDIX From the first term of (9.2), the ICI for the the th subcarrier is given by

th subscriber at

(33)


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From the second term of (9.2), the interference from the th subscriber to the th subscriber at the th subcarrier is given by

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Defeng (David) Huang (M’01–S’02–M’05) received the B. E. E. E. and M. E. E. E. degrees in electronic engineering from Tsinghua University, Beijing, China, in 1996 and 1999, respectively, and the Ph.D. degree in electrical and electronic engineering from the Hong Kong University of Science and Technology (HKUST), Kowloon, Hong Kong, in 2004. From 1998 to 2001, he was an Assistant Teacher and later a Lecturer with Tsinghua University. Currently, he is with the Department of Electronic Engineering, Tsinghua University. His research interests include wireless communications, OFDM, multiple-access protocol, space–time processing, channel estimation, and digital implementation of communication systems. Dr. Huang received the Hong Kong Telecom Institute of Information Technology Postgraduate Excellence Scholarship in 2004.

Khaled Ben Letaief (S’85–M’86–SM’97–F’03) received the BS degree with distinction in 1984, and the MS and Ph.D. degrees in 1986 and 1990, respectively, all in electrical engineering, from Purdue University, West Lafayette, IN. From January 1985 and as a Graduate Instructor in the School of Electrical Engineering at Purdue University, he taught courses in communications and electronics. From 1990 to 1993, he was a Faculty Member with the University of Melbourne, Melbourne, Australia. Since 1993, he has been with the Hong Kong University of Science and Technology, Kowloon, where he is currently Professor and Head of the Electrical and Electronic Engineering Department. He is also the Director of the Hong Kong Telecom Institute of Information Technology, as well as the Director of the Center for Wireless Information Technology. His current research interests include wireless and mobile networks, broadband wireless access, OFDM, CDMA, and Beyond 3G systems. In these areas, he has published over 270 journal and conference papers and given invited talks as well as courses all over the world. He has served as consultant for different organizations, as well. Dr. Letaief is the founding Editor-in-Chief of the IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS. He has served on the editorial board of other prestigious journals, including the IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS—WIRELESS SERIES (as Editor-in-Chief) and the IEEE TRANSACTIONS ON COMMUNICATIONS. He has been involved in organizing a number of major international conferences and events. These include serving as the Technical Program Chair of the 1998 IEEE Globecom Mini-Conference on Communications Theory, as well as the Co-Chair of the 2001 IEEE ICC Communications Theory Symposium. In 2004, he served as the Co-Chair of the IEEE Wireless Communications, Networks and Systems Symposium, as well as the Co-Technical Program Chair of the 2004 IEEE International Conference on Communications, Circuits and Systems. He served as the Chair of the IEEE Communications Society Technical Committee on Personal Communications, and is a member of the IEEE ComSoc Technical Activity Council. He received the Mangoon Teaching Award from Purdue University in 1990; the Teaching Excellence Appreciation Award from the School of Engineering at HKUST (four times); and the Michael G. Gale Medal for Distinguished Teaching (highest university-wide teaching award and only one recipient/year is honored for his/her contributions). He is an IEEE Distinguished Lecturer of the IEEE Communications Society.