Bayesian blind FIR channel estimation algorithms in SIMO systems

Omar, Samir Mohamad;Slock, Dirk T M; Bazzi, Oussama
SSP 2011, IEEE Workshop on Statistical Signal Processing, June 28-30, 2011, Nice, France

Blind channel estimation techniques were developed and usually evaluated for a given channel realization, i.e. with a deterministic channel model. On the other hand, in wireless communications the channel is typically modeled as Rayleigh fading, i.e. with a Gaussian (prior) distribution expressing variances of and correlations between channel coefficients. In this paper we explore a Bayesian approach to blind channel estimation, exploiting a priori information on fading channels. We mainly focus on joint ML/MAP estimation of channels and symbols on one hand, and on ML/MAP estimation of channels with elimination of symbols on the other hand. As a consequence, a unified framework in addition to three new Bayesian estimators are introduced where their performance is compared by simulations to three existing non-Bayesian estimators. In the same context, we provide an insightful discussion of the accurate way of deriving the Bayesian Cramer Rao bound (BCRB) with an emphasis on its singularity.


Systèmes de Communication
Eurecom Ref:
© 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.