deposit_your_work

Bayesian Blind PARAFAC Recievers forDS-CDMA Systems

Files in this item

Files Size Format View
deB2003Oct5BAYESIANBL.PDF 123.2Kb application/pdf Thumbnail

Show full item record

Item Metadata

Title: Bayesian Blind PARAFAC Recievers forDS-CDMA Systems
Author: de Baynast, Alexandre; Declercq, David; De Lathauwer, Lieven; Aazhang, Behnaam
Type: Conference Paper
Keywords: PARAFAC
Citation: A. de Baynast, D. Declercq, L. De Lathauwer and B. Aazhang,"Bayesian Blind PARAFAC Recievers forDS-CDMA Systems," in Statistical Signal Processing Workshop,
Abstract: 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.
Date Published: 2003-10-01

This item appears in the following Collection(s)

  • ECE Publications [1046 items]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students