A New Adaptive Stopping Criterion for Sparse Channel Estimation in MIMO-OFDM Underwater Acoustic Communications

Multiple inputs, multiple outputs (MIMO) systems are an attracting method for establishing high data rate underwater acoustic (UWA) communications. While the estimation of MIMO channels is challenging, sparse decomposition algorithms may enable efficient estimation methods. In this paper, a new stopping criterion for the compressed sampling matching pursuit channel estimation algorithm is proposed. Based on the residual statistics, it enables accurate channel estimation without prior knowledge of the channel sparsity level and signal-to-noise ratio (SNR).