A Novel Time-Varying Sparse Channel Estimation Based on Block-Type Pilot and SAMP

Using OMP algorithm for time-delay detecting and apply BEM based on comb-type pilot for channel estimation is the most commonly used method for sparse time-frequency doubly-selective channels, but the channel estimation performance will decrease sharply when the number of channel paths is large, and this method need to obtain the channel sparsity as prior information in advance. In this paper, a novel sparse channel estimation method based on block-type pilot and SAMP has been proposed, whereby using SAMP for time-delay detecting, using the BEM coefficients of pilot symbols and interpolation algorithm to obtain the BEM coefficients of the data symbols. The simulation verifies the proposed algorithm can achieve a good performance in the case of the channel paths is large and the channel sparsity is unknown.