Sparse Channel Estimation Algorithm for Doubly Selective MIMO OFDM-Based UWAC Systems With Double Focusing

Abstract

In this paper, a channel estimation algorithm is proposed for sparse underwater acoustic channels. The channel estimator utilizes the path-based channel model that can be characterized by a path delay, a Doppler scaling factor, and an attenuation factor. Assuming MIMO-OFDM with two transmitters and multiple receivers, the proposed estimator first employs orthogonal matching pursuit algorithm for initial estimation of path gains and delay values. Then, an iterative algorithm named double focusing interchangeably employs delay focusing and Doppler focusing approaches for channel estimation. The proposed approach is evaluated presented in terms of average mean square error and symbol error rate for 16QAM signaling with different residual Doppler spreading factors. The simulation results show that the proposed approach with the continuous focusing functions can outperform the compressed sensing-based orthogonal matching pursuit (OMP) algorithm and the basis pursuit-based generalized approximate message passing (GAMP) algorithm.