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Title:
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Bayesian Blind PARAFAC Recievers forDS-CDMA Systems |
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Author:
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de Baynast, Alexandre; Declercq, David; De Lathauwer, Lieven; Aazhang, Behnaam
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Type:
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Conference Paper |
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Keywords:
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PARAFAC |
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Citation:
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A. de Baynast, D. Declercq, L. De Lathauwer and B. Aazhang,"Bayesian Blind PARAFAC Recievers forDS-CDMA Systems," in Statistical Signal Processing Workshop, |
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Abstract:
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In this paper an original Bayesian approach for blind detec-tion for Code Division Multiple Access (CDMA) Systems in presence of spatial diversity at the receiver is developed. In the noiseless context, the blind detection/identification problem relies on the canonical decomposition (also re-ferred as Parallel Factor analysis [Sidiropoulos, IEEE SP 00], PARAFAC. The author in [Bro,INCINC 96] pro-poses a suboptimal solution in least-squares sense. How-ever, poor performance are obtained in presence of high noise level. The recently emerged Markov chain Monte Carlo (MCMC) signal processing method provide a novel paradigm for tackling this problem. Simulation results are presented to demonstrate the effectiveness of this method. |
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Date Published:
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2003-10-01 |
