A Joint Optimization Criterion for Blind DS-CDMA Detection
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Research Article A Joint Optimization Criterion for Blind DS-CDMA Detection ´ Duran-D´ ´ Ivan ıaz and Sergio A. Cruces-Alvarez Departamento de Teor´ıa de la Se˜nal y Comunicaciones, Escuela T´ecnica Superior de Ingenieros, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Sevilla, Spain Received 30 September 2005; Revised 9 May 2006; Accepted 11 June 2006 Recommended by Frank Ehlers This paper addresses the problem of the blind detection of a desired user in an asynchronous DS-CDMA communications system with multipath propagation channels. Starting from the inverse filter criterion introduced by Tugnait and Li in 2001, we propose to tackle the problem in the context of the blind signal extraction methods for ICA. In order to improve the performance of the detector, we present a criterion based on the joint optimization of several higher-order statistics of the outputs. An algorithm that optimizes the proposed criterion is described, and its improved performance and robustness with respect to the near-far problem are corroborated through simulations. Additionally, a simulation using measurements on a real software-radio platform at 5 GHz has also been performed. Copyright © 2007 I. Dur´an-D´ıaz and S. A. Cruces-Alvarez. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Direct-sequence code-division multiple access (DS-CDMA) is a common technique in mobile communications that complements other preexisting access techniques such as TDMA or FDMA [1–7]. In systems that use CDMA, users share the same band of frequencies and the same time slots. So the signal that arrives at the receiver is a superposition (in time and frequency) of contributions from different users. Since the objective of the receiver is to extract the symbols sequence of the desired user, the system needs some prior information to achieve this aim. This information is the user’s code, also called spreading sequence. Each user transmits with a different cyclic code that multiplies its symbols. For different users, codes are quasiorthogonal. In this way, the receiver can separate the users’ contributions by means of the codes. When there is multipath propagation, we have to suppress the channel effects. Supervised algorithms use training sequences that provide the receiver with knowledge about the channels. Blind detection of users can be performed to obtain the symbol sequence of a desired user without knowledge of the propagation channels. The use of blind techniques increases the performance of the transmission system, avoiding the overheads associated with the transmission of training sequences, and providing increased robustness for channels with severe fading [1, 3, 8].
In the literature, there are several blind criteria for the estimation of a specific user with knowledge only of its spreading code. Some authors proposed the use of MMSE criteria to exploi
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