Grid optimization based methods for estimating and tracking doubly spread underwater acoustic channels

In this paper, the methods for estimating and tracking sparse doubly spread channels in single-carrier coherent communications are investigated. The sparse doubly spread channel is parameterized by a few paths with different delays, Doppler scales, and gains. Based on the model, a low-complexity channel estimation algorithm is proposed. The channel estimation is divided into two stages, the first for path delays, and the second for the corresponding residual Dopplers and gains. In either stage, parameters are estimated iteratively with the help of adaptive grid optimization, which can dramatically reduce computational complexity. We also propose a channel tracking algorithm, which takes advantage of the estimation result from the previous frame, to further reduce the complexity. Simulation results have demonstrated that the proposed method can achieve a comparable performance with much lower complexity compared to the existing two-stage approach with OMP.