Semi-Blind Reception Using Joint Channel Estimation in IDMA Systems


In this paper a bi-directional system based on linear channel estimation and data detection using turbo detection algorithm is proposed. By combining channel estimation with an iterative chip-by-chip detection process (inner loop) in an iterative way (outer loop), communications performance can be further increased. We present results on blind reception in case of Interleave Division Multiple Access (IDMA) system when the channel coefficients are unknown. We develop a low-complexity iterative joint channel/code estimation method. The philosophy of the turbo processing is the iterative exchange of related information which yields a substantial improvement of the overall system performance. We analyze the achievable performance of the iterative system proposed. Simulation results demonstrate the efficiency of the proposed algorithms.

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A. Hamza, A. Kazem and G. Salut, "Semi-Blind Reception Using Joint Channel Estimation in IDMA Systems," International Journal of Communications, Network and System Sciences, Vol. 5 No. 7, 2012, pp. 430-435. doi: 10.4236/ijcns.2012.57053.

1. Introduction

The present paper proposes a semi-blind channel estimation method, based on conditional Gaussian particle algorithm for IDMA systems, to track varying channel coefficients. The performance of Code Division Multiple Access (CDMA) systems is mainly limited by Multiple Access Interference (MAI) and Inter Symbol Interference (ISI). Chip-level interleavers for user separation can separate different users without spreading within the CDMA framework. An interleaver based multiple access scheme has also been studied in [1,2] for high spectral efficiency, improved error performance and low receiver complexity. This paper concerns transmission and detection principles using interleavers as the only means for user separation, incorporating principles developed in [3,4]. Interleave Division Multiple-Access (IDMA) systems communication is one of the most promising technologies for high data rate wireless networks. IDMA inherits many advantages from CDMA, in particular, diversity against fading and mitigation of the worst-case other-cell user interference problem. Furthermore, IDMA allows a very simple chip-by-chip iterative Multi User Detection (MUD) strategy [5]. The normalized MUD cost (per user) can be made independent of the user number. From the receiver point of view the unknown channel degrades the accuracy of symbol detection. This can be eliminated using estimation methods on Channel State Information (CSI). Channel coefficient estimation is usually performed using known training sequences which are periodically transmitted (for instance, at the start of each frame), implicitly assuming that the channel does not vary between two training sequences. An iterative procedure to track the channel variations by refining the channel coefficients in a semi-blind manner is proposed. The paper is organized as follows: section 2 introduces the IDMA system and settles the various notations. Section 3 recalls the Chip by Chip (CBC) algorithm and its application on IDMA system, as well as channel estimation. This section presents also, the new detection system based on semi-blind channel estimation. Finally, section 4 illustrates the performance of the proposed algorithm through simulation results. Section 5 concludes the paper.

2. IDMA System Model

IDMA Transmitter and Receiver Structures are shown in

Figure 1 for the multiple access scheme under consideration with K simultaneous users, with perfect channel knowledge. The input data sequence dk of user-k is spread by a length C spreading sequence, generating a coded sequence ck = [ck(1); …; ck(j); …; ck(J)]T , where J is the frame length. The elements in ck are referred to as coded bits. Then ck is permuted by an interleaver π(k), producing the vector xk = [xk(1); …; xk(j); …; xk(J)]T. We

Conflicts of Interest

The authors declare no conflicts of interest.


[1] A. D. Damnjanovic and B. R. Vojcic, “Iterative Muli-User Detection/Decoding for Turbo Coded CDMA Systems,” IEEE Communications Letters, Vol. 5, No. 3, 2001, pp. 104-106. doi:10.1109/4234.913154
[2] X. Wang and H. V. Poor, “Iterative (Turbo) Soft Interference Cancellation and Decoding for Coded CDMA,” IEEE Transactions on Communications, Vol. 47, No. 7, 1999, pp. 1046-1061. doi:10.1109/26.774855
[3] S. Brck, U. Sorger, S. Gligorevic and N. Stolte, “Interleaving for Outer Convolutional Codes in DS-CDMA Systems,” IEEE Transactions on Communications, Vol. 48, No. 7, 2000, pp. 1100-1107. doi:10.1109/26.855517
[4] R. H. Mahadevappa and J. G. Proakis, “Mitigating Multiple Access Interference and Intersymbol Interference in Uncoded CDMA Systems with Chip-Level Interleaving,” IEEE Transactions on Wireless Communications, Vol. 1, No. 4, 2002, pp. 781-792. doi:10.1109/TWC.2002.804163
[5] C. Berrou and A. Glavieux, “Near Shannon Limit Error Correcting Coding and Decoding: Turbo-Codes,” IEEE Transactions on Communications, Vol. 44, No. 10, 1996, pp. 1261-1271. doi:10.1109/26.539767
[6] P. Li, L. H. Liu, K. Y. Wu and W. K. Leung, “Interleave Division Multiple-Access,” IEEE Transactions on Wireless Communications, Vol. 5, No. 4, 2006, pp. 938-947.
[7] P. Li, “Interleave-Division Multiple Access and Chip-by-Chip Iterative Multi-User Detection,” IEEE Communications Magazine, Vol. 43, No. 6, 2005, pp. S19-S23. doi:10.1109/MCOM.2005.1452830
[8] H. Abdelkrim, et al., “Independent Component Analysis in IDMA Systems,” Circuits and Systems and TAISA Conference, Toulouse, 28 June-1 July 2009, pp. 1-4.
[9] M. Moher and P. Guinand, “An Iterative Algorithm for Asynchronous Coded Multi-User Detection,” IEEE Communications Letters, Vol. 2, No. 8, 1998, pp. 229-231. doi:10.1109/4234.709440
[10] A. Kazem, G. Salut and F. Lehmann, “Iterative Joint Phase/Timing Estimation and Decoding for GEO Satellite Links in the Presence of Doppler Shift,” Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, Sydney, 28-31 August 2005, pp. 271-274.

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