NDLI: Variational Bayesian blind and semiblind channel estimation

Content Provider	IEEE Xplore Digital Library
Author	Omar, S.-M. Slock, D.T.M.
Copyright Year	2010
Description	Author affiliation: Mobile Communications Dept., EURECOM, BP 193, 06904 Sophia Antipolis Cdx, France (Omar, S.-M.; Slock, D.T.M.)
Abstract	Blind and semiblind channel estimation is a topic that enjoyed explosive developments throughout the nineties, and then came to a standstill, probably because of perceived unsatisfactory performance. Blind channel estimation techniques were developed and usually evaluated for a given channel realization, i.e. with a deterministic channel model. Such blind channel estimates, especially those based on subspaces in the data, are often only partial and ill-conditioned. 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 recent years, such prior information on the channel has started to get exploited in pilot-based channel estimation, since often the pure pilot-based (deterministic) channel estimate is of limited quality due to limited pilots. In this paper we explore a Bayesian approach to (semi-)blind channel estimation, exploiting a priori information on fading channels. In the case of deterministic unknown input symbols, it suffices to augment the classical blind (quadratic) channel criterion with a quadratic criterion reflecting the Rayleigh fading prior. In the case of a Gaussian symbol model the blind criterion is more involved. The joint ML/MAP estimation of channels, deterministic unknown symbols, and channel profile parameters can be conveniently carried out using Variational Bayesian techniques. Variational Bayesian techniques correspond to alternating maximization of a likelihood w.r.t. subsets of parameters, but taking into account the estimation errors on the other parameters. To simplify exposition, we elaborate the details for the case of MIMO OFDM systems.
Starting Page	1
Ending Page	6
File Size	4470816
Page Count	6
File Format	PDF
ISBN	9781424462858
e-ISBN	9781424462872
DOI	10.1109/ISCCSP.2010.5463451
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-03
Publisher Place	Cyprus
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Blind equalizers Wireless communication Fading Maximum likelihood estimation Estimation error Bayesian methods Channel estimation Rayleigh channels Explosives MIMO
Content Type	Text
Resource Type	Article

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