ADAPTIVE BLIND EQUALISATION OF FIR CHANNELS USING HIDDEN MARKOV MODELS

摘要

This paper addresses the problem of blind equalisation of digital communications signals passed through a finite impulse response(FIR)channel with additive Gaussian white noise on the OUtput.The input signal is modelled as a finite state Markov process,and we derive the fixed lag smoother equations for estimating this input sequence.The unknown channel taps are simultaneously estimated using an incomplete data version of the recursive least squares(RLS)algorithm,where the(unknown)regressed data error and covariance are replaced by their expectations conditioned on the observations.A Sufficient condition for local convergence of the tap estimates is given in terms of a sufficiency of excitation condition of the input Markov chain.Sub-optimal algorithms of reduced computation requirement which utilise reduced state estimation (via decision feedback) are specified.The performance of the algorithIns are illustrated using simulations employing QPSK ignals.