Bayesian blind and semi-blind equalisation of channels with Markov inputs

Author

Doucet, A. ; Andrieu, C. ; Urien, R.

Author_Institution

Signal Process. Group., Cambridge Univ., UK

Volume

148

Issue

4

fYear

2001

fDate

8/1/2001 12:00:00 AM

Firstpage

269

Lastpage

274

Abstract

An original full Bayesian approach is developed for blind and semi-blind equalisation of fading channels with Markov inputs. The sequence of discrete symbols is estimated according to a marginal maximum a posteriori criterion; the other unknown parameters are regarded as random nuisance parameters and are integrated out analytically. A batch algorithm is proposed to maximise the marginal posterior distribution. Simulation results are presented to demonstrate the effectiveness of the method

Keywords

AWGN; Bayes methods; blind equalisers; fading channels; hidden Markov models; optimisation; parameter estimation; random processes; sequential estimation; Bayesian blind channel equalisation; Bayesian semi-blind channel equalisation; HMM; MMAP blind sequence estimation; Markov inputs; additive white Gaussian noise; batch algorithm; discrete symbols sequence estimation; fading channels; hidden Markov models; marginal MAP criterion; marginal maximum a posteriori criterion; marginal posterior distribution; optimisation; random nuisance parameters; signal model; simulation results;

fLanguage

English

Journal_Title

Vision, Image and Signal Processing, IEE Proceedings -

Publisher

iet

ISSN

1350-245X

Type

jour

DOI

10.1049/ip-vis:20010152

Filename

955439