de Baynast, AlexandreDeclercq, DavidDe Lathauwer, LievenAazhang, Behnaam2007-10-312007-10-312003-10-012003-10-01A. de Baynast, D. Declercq, L. De Lathauwer and B. Aazhang, "Bayesian Blind PARAFAC Recievers forDS-CDMA Systems," 2003.https://hdl.handle.net/1911/19834Conference paperIn 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.engPARAFACBayesian Blind PARAFAC Recievers forDS-CDMA SystemsConference paperPARAFAC