The adaptive matching pursuit algorithm for estimation and equalization of sparse time-varying channels

This paper addresses issues related to the estimation and equalization of channels with a large delay spread and an impulse response with significant values only over small regions. For a time-varying environment, an adaptive matching pursuit (AMP) algorithm is considered which updates the channel estimate while exploiting the channel´s sparsity. From the channel estimate, the equalizer taps are then derived. We show through simulations that using AMP to track the time-varying channel gives significant improvement in equalization performance over using the LMS or RLS algorithms. We also demonstrate how ANP may be modified to more quickly adapt to a fast time-varying channel.