Bayesian Blind and Semi-Blind Equalization of Channels with Markov Inputs
Christophe Andrieu, Arnaud Doucet, R. Urien · Bristol Research (University of Bristol) · 2001
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.