Time-varying channel estimation using amplitude-division based parallel NLMS technique

In this paper, we propose a channel estimation technique to combat the rapidly time-varying characteristics of multipath channel. The proposed method uses a normalized least mean square (NLMS) based novel adaptation scheme with amplitude-division technique. It supposes multiple linear transversal filters as estimators, which are arranged in a parallel fashion. The coefficient vectors for each estimator are formed with the amplitude-division based classification technique according to the information of the channel coefficient values. The coefficient vector selected at each iteration is adapted with the NLMS algorithm to handle the time variation effect of the rapidly time-varying channel. Computer simulation results demonstrate that the proposed estimator provide better tracking performance than the conventional NLMS estimator and amplitude-division parallel LMS (ADPLMS) estimator for a second order Markov communication channel in various fade rate conditions.