Estimation of Underwater Acoustic MIMO-OFDM Channel Based on Compressed Sensing

Abstract

Underwater acoustic (UWA) channel estimation is crucial for underwater acoustic communications. In this paper MIMO-OFDM system is applied in shallow water acoustic communication. The channel estimation is based on compressed sensing (CS) theory due to the sparse characteristic of UA channel. Aiming at the unknown sparsity, an improved orthogonal matching pursuit (OMP) algorithm, which is the combination of regularized OMP (ROMP) and sparsity adaptive MP (SAMP) algorithm, is presented. Compared with OMP, SAMP and ROMP algorithm by simulation, the improved algorithm has shorter running time and lower bit error rate (BER). It is feasible in performance and efficiency.