Adaptive maximum likelihood algorithms for the blind tracking of time-varying multipath channels

摘要

Transmissions through multipath channels suffer from Rayleigh fading and intersymbol interference. This can be overcome by sending a (known) training sequence and identifying the channel (active identification). However, in a non-stationary context, the channel model has to be updated by periodically sending the Training sequence, thus reducing the transmission rate. We address herein the problem of blind identification, Which does not require such a sequence and allows a higher transmission rate. We have fist proposed A two-stage algorithm (see Reference 2) for the blind identification of multpath channel.