Sparse Channel Estimation for MIMO Index Modulated OFDM Based Underwater Acoustic Communications

This paper presents a novel channel estimation algorithm for pilot aided MIMO-OFDM-IM underwater acoustic communications. The receiver employs the least squares technique for the initial channel coefficients estimation. Then, using the ESPRIT algorithm, the delays of the most significant taps are estimated. The initial estimated values are then inputted to the proposed focusing algorithm. This algorithm utilizes two one-dimensional continuous focusing functions for channel coefficients' estimation. Opposed to most algorithms in literature, the proposed focusing algorithm does not require an oversampling factor as in dictionary-based algorithms nor a learning parameter as in basis pursuit-based algorithms. Finally, for each branch of the MIMO receiver, the estimated channel coefficients are used for active subcarriers detection in each OFDM-IM chunk using the maximum likelihood detector. The performance of the proposed receiver is presented in terms of average mean square error and symbol error rate using synthetic underwater acoustic channels generated using VirTEX acoustic toolbox.