Channel Estimation based on Compressed Sensing for High-speed Underwater Acoustic Communication

Compressed sensing is a topic that has recently gained much attention in high-speed underwater acoustic (UWA) communications. Combined the MIMO communication system with OFDM technology, they can realize high-speed data communication over UWA channels and overcome the fading problem efficiently. In this paper performance analysis of compressed sensing (CS) channel estimation algorithms for underwater acoustic communication is investigated. The estimation of UWA channel is mainly based on Least Square (LS), Orthogonal Matching Pursuit (OMP) and Compressed Sensing Matching Pursuit (CS-MP) channel estimation algorithms. We have compared the performance of channel estimation algorithms by measuring mean squared error (MSE) vs. SNR and calculation time vs. SNR. On the basis of the simulation results, the CS-MP channel estimation indicates to perform better performance than LS and OMP, which can lead to accurate channel state information (CSI) with fewer pilots so as to improve the frequency spectrum efficiency. CS provides some new idea about channel estimation for UWA communications.