Title :
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
fDate :
8/1/2001 12:00:00 AM
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;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:20010152
