Blind Equalization by Direct Examination of the Input Sequences

The authors' approach to blind equalization examines the possible input sequences directly by using a bank of filters and, in contrast to common approaches, does not try to find an approximative inverse of the channel dynamics. The identifiability question of a noise-free finite impulse response (FIR) model is investigated. A sufficient condition for the input sequence (persistently exciting of a certain order) is given which guarantees that both the channel model and the input sequence can be determined exactly in finite time. A recursive algorithm is given for a time-varying infinite impulse response (IIR) channel model with additive noise, which does not require a training sequence. The estimated sequence is an arbitrarily good approximation of the maximum a posteriori estimate. The proposed method is evaluated on a Rayleigh fading communication channel. It shows fast convergence properties and good tracking ability