Double Focusing: A New Sparse Channel Estimation Algorithm for Doubly Selective SFBC-OFDM-Based Underwater Acoustic Systems

摘要

In this letter, a new channel estimation algorithm is proposed for underwater acoustic channels undergoing Rayleigh fading with impulsive noise. For the channel estimation purpose, the algorithm utilizes the path-based channel model characterized by a path delay, a Doppler scaling factor, and an attenuation factor. Assuming antenna diversity coupled with Alamouti's space-frequency block coding, the proposed estimator first employs matching pursuit algorithm for initialization. Then, the iterative algorithm interchangeably employs delay focusing and Doppler focusing approaches for Doppler shifts and delays estimation, respectively, with their corresponding path gains. The performance of the proposed algorithm is then presented in terms of average mean square error and symbol error rate for 16QAM signaling with different pilot spacings. The simulation results show that the proposed approach with the continuous focusing functions can outperform the compressed sensing-based matching pursuit (MP) algorithm and the projected (PMP), and the basis pursuit-based generalized approximate message passing (GAMP) algorithm.