Low-Complexity Iterative Receiver for Space-Time Coded Signals over Frequency Selective Channels
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Low-Complexity Iterative Receiver for Space-Time Coded Signals over Frequency Selective Channels Noura Sellami France T´el´ecom R&D, 38-40 rue du G´en´eral Leclerc, 92794 Issy les Moulineaux, France ´ Equipe de Traitement des Images et du Signal, ENSEA-Universit´e de Cergy Pontoise, 6 avenue du Ponceau, 95014 Cergy-Pontoise, France Email: [email protected]
Inbar Fijalkow ´ Equipe de Traitement des Images et du Signal, ENSEA-Universit´e de Cergy Pontoise, 6 avenue du Ponceau, 95014 Cergy-Pontoise, France Email: [email protected]
Mohamed Siala Sup’Com, Route de Raoued Km 3.5, 2083 Ariana, Tunisia Email: [email protected] Received 31 May 2001 and in revised form 18 March 2002 We propose a low-complexity turbo-detector scheme for frequency selective multiple-input multiple-output channels. The detection part of the receiver is based on a List-type MAP equalizer which is a state-reduction algorithm of the MAP algorithm using per-survivor technique. This alternative achieves a good tradeoff between performance and complexity provided a small amount of the channel is neglected. In order to induce the good performance of this equalizer, we propose to use a whitened matched filter (WMF) which leads to a white-noise “minimum phase” channel model. Simulation results show that the use of the WMF yields significant improvement, particularly over severe channels. Thanks to the iterative turbo processing (detection and decoding are iterated several times), the performance loss due to the use of the suboptimum List-type equalizer is recovered. Keywords and phrases: space-time coded MIMO channel equalization, per-survivor processing, multidimensional whitened matched filter, turbo detection.
1. INTRODUCTION The growing demand for new services at high data rates indicates the need for new techniques to increase channel capacity. Foschini and Gans [1] have demonstrated the enormous capacity potential gain of wireless communication systems with antenna arrays at both transmitter and receiver. In order to achieve the promised high data rates over frequency selective multiple-input multiple-output (MIMO) channels, an equalizer has to be applied to reduce the channel time dispersion due to multipath propagation at high data rates. Several solutions have been proposed among them linear and decision-feedback structures with a zero forcing or minimum mean square error optimization [2]. These equalizers have a low-complexity but suffer from noise enhancement and error propagation. In terms of performance, it is better to use a maximum a posteriori (MAP) [3] or Viterbi equalizer. However, the complexity of these algorithms is proportional to the number of states of the trellis which grows
exponentially with the product of the channel memory and the number of transmit antennas [4]. When the channel memory becomes large and high-order constellations are used, the algorithm becomes impractical. Therefore, a reduced complexity approach is needed. In this paper, we consider a List-type MAP equalizer [5] which realizes a
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