Pilot allocation for MIMO-ZP-OFDM systems in underwater acoustic channel based on structured compressive sensing

Recently, many key techniques which was proved effective in radio communication have been utilized in underwater acoustic (UWA) communication, such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM). Channel estimation for MIMO-OFDM systems has been improved observably based on compressive sensing (CS) techniques. In recent years, by exploiting the inherent common sparsity of channels between different transmitting and receiving antennas pairs, channel estimation for MIMO-OFDM systems can be further enhanced. To take advantage of this characteristic, some block-structured CS methods have been proposed for MIMO-OFDM systems. In this paper, we treat the UWA channel with same Doppler scaling factor on all propagation paths and adopt an approach to mitigating the Doppler effect. Then, we investigate the channel estimation property for MIMO-OFDM systems based on the block-structured CS techniques. Finally, we introduce the blocked orthogonal matching pursuit (BOMP) algorithm to obtain the channel estimation result. Simulation results demonstrate that the proposed pilot allocation scheme and the modified block-structured CS method perform very well in MIMO-OFDM systems.