BLIND EQUALIZATION BY DIRECT EXAMINATION OF THE INPUT SEQUENCES

This paper presents a novel approach to blind equalization (deconvolut ion), which is based on direct examination of possible input sequences . In contrast to many other approaches, it does not rely on a model of the approximative inverse of the channel dynamics. To start with, the blind equalization identifiability problem for a noise-free finite im pulse response channel model is investigated. A necessary condition fo r the input, which is algorithm independent, for blind deconvolution i s derived. This condition is expressed in an information measure of th e input sequence, A sufficient condition for identifiability is also i nferred, which imposes a constraint on the true channel dynamics, The analysis motivates a recursive algorithm where all permissible input s equences are examined. The exact solution is guaranteed to be found as soon as it is possible. An upper bound on the computional complexity of the algorithm is given. This algorithm is then generalized to cope with time-varying infinite impulse response channel models with additi ve noise. The estimated sequence is an arbitrary good approximation of the maximum a posteriori estimate. The proposed method is evaluated o n a Rayleigh fading communication channel. The simulation results indi cate fast convergence properties and good tracking abilities.