Soft bayesian recursive interference cancellation and ... - IEEE Xplore

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 19, NO. 9, SEPTEMBER 2001

Soft Bayesian Recursive Interference Cancellation and Turbo Decoding for TDD-CDMA Receivers R. Cusani and D. Crea

Abstract—A novel receiver is proposed for CDMA links with recursive turbo-coding, based on a soft-input soft-output multistage interference canceler (IC) and an iterative turbo-decoder (TD). After performing IC and TD a first time, the coder state estimates available from the two soft-output Viterbi algorithms in the last TD iteration are exploited to calculate the data bits and the redundancy bits. These are employed for preliminary hard cancellation in the first iteration of a supplementary IC run, and then the TD is run again. An alternative solution with soft feedback is obtained by approximating the reliabilities of the redundancy bits with those of the coder state estimates, and using them for preliminary soft cancellation. Simulation results show the effectiveness of the proposed solutions. Index Terms—Code division multiaccess, coding, multiuser channel.

I. INTRODUCTION

M

ULTI-USER detection (MUD) is often considered in CDMA receivers to combat multiple-access interference (MAI). Referring in particular to the terrestrial radio interface (UTRA) of the future third-generation cellular mobile system (UMTS), MUD constitutes a possible option for the base station in the UTRA-FDD mode (mainly devoted to voice services) but is mandatory for both mobile and base stations in the UTRA-TDD mode, which seems more suitable for high-speed data transmission [1], [9]. Classic MUD techniques are the Zero-Forcing and the minimum-mean-square-error receivers, eventually supported by a decision-feedback strategy [7]. Multistage interference cancelers (ICs) emerged in the last year as feasible MUD solutions: their sensitivity to channel estimation and decision errors can be mitigated by using partial [2] or soft [3], [4] cancellation, possibly with a degree of “softness” decreasing from a stage to the other until that hard cancellation is performed in the last stage. For coded transmissions, improved performance can be obtained by coupling the IC and the channel decoding tasks instead of simply cascading them. In [4], an iterative receiver structure is proposed where interference cancellation and single-user channel decoding are alternated, thus approaching single-user performance for large signal-to-noise ratios (SNRs). Although a reduced-complexity solution is proposed for multipath channels, the receiver in [4] exhibits a large computational complexity and seems more suitable for CDMA links with a of active users and a small spreading factor small number Manuscript received March 29, 2000. The authors are with the INFO-COM Department, University of Rome “La Sapienza,” 00184 Rome, Italy. Publisher Item Identifier S 0733-8716(01)07953-7.

( and in the simulations of [4], where perfect channel estimation is also assumed). In [5], the CDMA channel is viewed as a time-varying convolutional code concatenated to the channel coder, and a serial turbo decoder is proposed. In this paper, a novel receiver is proposed for turbo-coded CDMA links employing recursive coding, such as the turboencoded UTRA-TDD system. It is constituted by a soft-input soft-output (SISO) IC working at symbol rate, the Multistage Bayesian (MB) canceler of [3], and by a classic iterative turbodecoder (TD) employing soft-output Viterbi algorithm (SOVA) modules. The re-encoding task is easily accomplished by properly extracting from the two SOVAs operating in the last TD iteration the hard- or soft-information about both data and redundancy bits, and using it for preliminary cancellation before rerunning the IC. The MB canceler is described in Section II together with the employed system model, while different receiver architectures with hard or soft re-encoding are proposed in Section III. Their effectiveness is compared in Section IV: in particular, the so-called soft-feedback solution is proposed for practical applications in CDMA receivers. II. THE SYSTEM MODEL AND THE MULTISTAGE BAYESAN (MB) INTERFERENCE CANCELER The received signal, sampled at chip rate , is preliminary subject to coherent combining (CC) and despreading for each of the users. The CC task is supported by a channel estimator (CE) which computes the equivalent baseband discrete-time (at chip rate ) channel impulse response (C-CIR). In the downlink, the C-CIR is estimated by cross-correlating the received training sequence with its replica available at receiver site. A more sophisticated scheme, based on recursive C-CIR estimation and interference cancellation, has been proposed in [3] for the uplink. TDD employs short-length spreading codes with periodicity (complex) received sequences equal to . The following , (one for each of the users) are obafter CC and despreading the tained at symbol rate received signal:

(1) is the transmitted data sequences with generwhere is additive ally complex modulation, e.g., QPSK, (Gaussian) observation noise sequences obtained after CC and the baseband despreading of the thermal noise, and

0733–8716/01$10.00 © 2001 IEEE

CUSANI AND CREA: SOFT BAYESIAN RECURSIVE INTERFERENCE CANCELLATION AND TURBO DECODING

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TABLE I BASIC PARAMETERS OF THE UTRA-TDD SYSTEM

discrete-time (sampled at symbol rate ) equivalent channel impulse responses (S-CIRs) between the th user and the output of the th despreader.1 The S-CIRs are computed from the estimated C-CIR by considering the presence of spreader and despreader. consecuFor each user, the IC processes a block of tive received samples (1), which are collected in the vector . In the “tentative decisions” first iteration, are computed and collected in the vector . The following is employed by (complex) memoryless nonlinearity the MB canceler of [3] to calculate the tentative decisions:

(2) represents the current received sample and its corresponding tentative decision, , , are the constellation symbols (e.g., in BPSK, in QPSK), and , where , , are the variances of MAI, ISI and observation noise respectively. The total interference due to both MAI and (residual) ISI affecting user # at epoch is then estimated from the tentative decisions as

where

(3)

The difference: then constitutes the received sequences “cleaned” from the estimated interference. times, but the tentative The above procedure is iterated and decisions are now computed from the soft decisions not from the original received sequence.2 The basic equations for the th iteration are the same as before, with the subscript 1 . The IC outputs calcureplaced by the index lated in the last iteration are finally fed to the soft-input decoder, described in the next section.3 III. MB INTERFERENCE CANCELLATION DECODING

a consequence of the CC operation, the S-CIRs are noncausal and have (maximum) length .

2L + 1

TURBO

In this paper, we consider a turbo-coded transmission link employing a recursive systematic coder (RSC). As a practical case, we refer to the UTRA-TDD system (see [1], [9], and Table I) with the turbo-encoder of Fig. 1. The turbo decoder (TD) is described in Fig. 2: the log-likelihood ratio (LLR) reliability measure of the data bit, available from SOVA-2 after times. The sign of LLR is de-interleaving, is calculated , where , assumed equal to the sign of , are deducted from the SOVA-2 coder state estimate (in the last iteration also constitutes the decoded bit). Similarly, the sign of the reliability LLR1 (calculated by SOVA-1) is that which is also obtained from SOVA-1. of An immediate feed-forward (FF) receiver architecture is obtained by feeding the deinterleaver/decoder with the soft-valued sequences available at MB output and pertaining to the user of interest (in the uplink, all user sequences are decoded in parallel). An alternative solution with hard-feedback re-encoding (HF-R) is obtained by re-encoding, re-interleaving, and remodulating the hard-decoded data bits for all users, thus obtaining hard estimates of the transmitted sequences. The MB canceler is then applied again, using such estimates in the first iteration for preliminary interference cancellation. Deinterleaving and decoding then follows again. 2Hard

1As

AND

N >1

cancellation is performed in the last iteration if . MB canceler can be implemented in both parallel and sequential versions. The simulation results reported in this paper refer to the parallel version. 3The

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Fig. 1. The 1 : 3 RSC employed in UTRA-TDD, using two 8-state 2 are the redundancy bits. The channel interleaver is uniform.

r

b

r

r

G(13,15) modules and a uniform internal rotated block interleaver (RBI); b is the data bit, r1,

Fig. 2. Block diagram of the TD: , 1 , 2 , available from MB output, are the received (soft) data bit and the redundancy bits; LLR1 and LLR are the reliabilities of as calculated by SOVA-1 and SOVA-2, respectively; ^, ^1, and ^2 are the (hard) estimates of , 1, and 2, obtained as described in Section III. In the first iteration the LLR input of SOVA-1 is absent.

b

br

Both FF and HF-R solutions are described in Fig. 3, where denotes the number of iterations employed by the , the number of iterations two MB cancellers and , , , employed by the two TDs. The quadruple [ ] then characterizes the actual receiver configuration: as , , 0, 0) denotes the FF receiver while particular cases, ( , 0, 0) denotes turbo-decoding without IC (but with CC (0, and despreading only). As evidenced in Fig. 3, the MB canceler (and not at deals with sequences sampled at symbol rate ), thus directly exploiting the TD output for prechip rate liminary IC without additional spreading/despreading. Due to the recursive nature of the encoder, the errors in the decoded bits are spread over many re-encoded bits and HF-R is outperformed by FF at small SNRs, as shown in the next section. Such error propagation phenomenon is bypassed by directly calculating the data bits and the redundancy bits from the last iteration of the TD, without re-encoding. In fact, we observe that SOVA-1 in Fig. 2 estimates step by step the state of the first (13,15) module of Fig. 1, i.e., it estimates the bits , ,

r

br

r

, and . A similar consideration applies for SOVA-2, so can be calculated, rethat the estimated redundancy bits , spectively, from SOVA-1 and SOVA-2 as (4) Using (4) the receiver of Fig. 3 is modified as shown in Fig. 4 are to give our HF solution: the estimated bits , , and calculated only in the last TD iteration and interlaced by the MUX. After interleaving and remodulation, they are employed in the first iteration of the second MB canceler for preliminary hard IC. A soft-feedback (SF) alternative is obtained by assuming that the reliability of is equal to LLR1 and the reliability of is LLR, which are available from SOVA-1 and SOVA-2, respectively (see Fig. 2). Similarly to [6], these are employed to calas culate the error probabilities of , LLR

(5)

The above equation is obtained by using [8, eqs. (5) and (10)].


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Fig. 3. Block diagram of FF (shadowed box) and HF-R (whole diagram) receivers. The labels T , T , and T denotes that the receiver is working at chip rate, symbol rate, or bit rate respectively. For the HF-R solution the first TD and the associate re-encoding are performed for all active users in both downlink and uplink.

K

TABLE II POWER-DELAY PROFILE OF THE RAYLEIGH WSSUS VEHICULAR A TEST CHANNEL EMPLOYED IN THE SIMULATIONS. FOR THE SAKE OF COMPARISON WITH PREVIOUS RESULTS, IT IS THE SAME SUGGESTED BY ETSI FOR THE CHIP RATE OF 4.096 Mcps ALTHOUGH THE ACTUAL UTRA CHIP RATE IS 3.84 Mcps. CHANNEL REALIZATIONS ARE KEPT CONSTANT THROUGH EACH TIMESLOT AND ARE INDEPENDENT FROM ONE TIMESLOT TO THE OTHER

Fig. 4. Modification to the block diagram of Fig. 3 to obtain the HF receiver: the MUX block replaces the re-encoder block of Fig. 3. ^, ^1, and ^2 are extracted from the last stage of the turbo decoder as shown in Fig. 2.

br

r

The constellation symbol probabilities and the expected value of the remodulated symbol are then obtained and finally exploited in the first stage of the second MB for preliminary soft IC. In [6], a CDMA receiver with soft re-encoding has been proposed. Its performance (evaluated for BPSK modulation, AWGN channel, and single-path Rayleigh fading channel with perfect interleaving) exhibits a BER floor for large SNRs, and is quite far from the single-user performance bound. In [6], the of the decoded data bit is obtained as in error probability (5) but the convolutional code is nonrecursive (nonturbo) and the error probabilities of the re-encoded bits are then easily calculated and exploited for weighted interference cancellation. The same procedure does not apply in our case of recursive coding. IV. COMPUTATIONAL COMPLEXITY, RESULTS, CONCLUSIONS

AND

The computational complexity of the proposed solutions is and : in fact we verified that mainly determined by

one TD iteration, including heavy interleaving/deinterleaving operations, is nearly ten times more expensive than one iteration TD iterations of the MB canceler. We also observe that the concern all active users for the uplink receiver (base station) but only one user for the downlink (handset) receiver, while the TD iterations concern all users IC iterations and the first in both cases. HF is less complex than SF-R, having skipped the re-encoding operations, while SF is slightly more complex than HF, because soft re-encoding is employed. Computer simulations have been carried out to compare the performance of FF, HF-R, HF, and SF receivers by considering the UTRA-TDD system of Table I for the downlink case only. The channel interleaver is random with length 4140 bits (i.e., 15 timeslots). The internal interleaver is a uniform Rotated Block Interleaver (RBI, for better decoding of the bits at the end of the interleaved block) with length 4140/3 1380 bits. The fading channel is Rayleigh WSSUS with the power/delay profile of Table II; channel realizations are constant within each timeslot and are independent from a timeslot to the other. The C-CIR taps.4 CC employs only the largest

L

4Changing the performance may vary significantly, but the curve behavior and the hierarchy between different solutions are preserved. In particular, for the Veh.A test channel an optimal choice seems to be = 2. However, the optimization of is beyond the scope of this paper.

L

L

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Fig. 5. BER versus SNR performance for the FF, HF-R, HF, and SF receivers for the UTRA-TDD downlink of Table I and the test channel of Table II. Two , , , and characterizes the actual receiver configuration: , iterations are employed for both the MB canceler and the TD. The quadruple denote the number of iterations employed by the two MB cancelers and , the number of iterations employed by the two TDs.

N

N N N N N

N

N

Fig. 6. Same as Fig. 5, with three iterations for both the MB canceler and the TD.

From Figs. 5 and 6, we verify that HF-R outperforms FF only for large SNRs, when the error propagation phenomenon is not relevant, and approaches HF performance. SF is always better than HF and also exhibits a smaller error floor.

In Fig. 5, the receiver employs a total of two iterations for each IC and TD tasks, while in Fig. 6 this total is three and better performance is obtained. Repeating the IC/TD procedure a third time does not give further benefits.


Recalling that the quadruple [ , , , ] characterizes the actual receiver configuration, we verified that the (2112) solution outperforms other solutions with the same total number of iterations, e.g., (1221) and (2211) (we also observe that for the downlink these latters are more expensive). Furthermore, we verified that (211 ) solutions, with outperform the corresponding (221 ) solutions at large SNRs (more than 3 dB) while are slightly worse at smaller SNRs. and is a We then assume that using good general choice, also offering minimum complexity for the downlink receiver. We also evaluated the effect of increasing , concluding that nearly-optimal performance is obtained . for We conclude that the proposed SF solution [in particular, the (2113) version] seems to offer a good tradeoff between complexity and performance and thus is a good candidate for future TDD receivers. In a practical application, the receiver stores an entire interleaved block and then processes it by carrying out the required , , , ] iterations (indeed, the first it[ erations can be executed without expecting the end of the received block). So, the overall processing delay is that associated with the unavoidable interleaving delay plus that due to the processing, which depends on the computing power available at the receiver.

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[2] G. Xue, J. Weng, T. Le-Ngoc, and S. Tahar, “Adaptive multistage parallel interference cancellation for CDMA,” IEEE Trans. Commun., vol. 17, pp. 1815–1827, Oct. 1998. [3] R. Cusani, M. Di Felice, and J. Mattila, “A simple Bayesian multistage interference canceller for multiuser detection in TDD-CDMA receivers,” IEEE Trans. Veh. Technol., vol. 50, July 2001. [4] X. Wang and H. V. Poor, “Iterative (turbo) soft interference cancellation and decoding for coded CDMA,” IEEE Trans. Commun., vol. 47, pp. 1046–1061, July 1999. [5] P. D. Alexander, M. C. Reed, J. A. Asenstorfer, and C. B. Schlegel, “Iterative multiuser interference reduction: Turbo CDMA,” IEEE Trans. Commun., vol. 47, pp. 1008–1014, July 1999. [6] W. Y. Joo, S. Y. Yoon, and H. S. Lee, “Weighted interference cancellation and decoding for coded CDMA,” Electron. Lett., no. 19, pp. 1617–1618, Sept. 1999. [7] A. Klein, G. S. Kaleh, and P. W. Baier, “Zero forcing and minimum mean-square-error equalization for multi-user detection in code-division multiple-access channels,” IEEE Trans. Veh. Technol., vol. 45, pp. 276–287, May 1996. [8] J. Hagenauer and P. Hoeher, “A Viterbi algorithm with soft-decision outputs and its applications,” in Proc. GLOBECOM ’89, 1989, pp. 47.1.1–47.1.7. [9] M. Haardt, A. K. R. Koehn, S. Oestreich, M. Purat, V. Sommer, and T. Ulrich. The TD-CDMA based UTRA TDD mode. IEEE J. Select. Areas Commun. [Online]. Available: http://www.3gpp.org

R. Cusani, photograph and biography not available at the time of publication.

REFERENCES [1] M. Haardt, A. K. R. Koehn, S. Oestreich, M. Purat, V. Sommer, and T. Ulrich, “The TD-CDMA based UTRA TDD mode,” IEEE J. Select. Areas Commun., vol. 18, no. 8, pp. 1375–1385, August 2000.

D. Crea, photograph and biography not available at the time of publication.