Joint temporal-sparse recovery approach for estimation of underwater acoustic MIMO channels

Abstract

MIMO communication offers a potential solution for high speed underwater acoustic communication. However, the simultaneous presence of multipath and co-channel interference (Co-channel interference, CoI) poses serious difficulty for estimating acoustic MIMO channels. For MIMO channels with serous CoI, the performance gain achieved by exploiting the sparsity of a single acoustic channel is insufficient to meet the need of MIMO acoustic communication. In this paper, a temporal joint sparse recovery approach is proposed to exploit the sparse correlation between adjacent blocks and improve the performance of channel estimation. A joint sparse model under the framework of distributed compressed sensing (DCS) is adopted to derive a joint sparse recovery algorithm for estimating MIMO channels. Finally, underwater MIMO communication experimental results obtained in a shallow water channel are provided to demonstrate the effectiveness of the proposed method compared to the classic estimation methods.