Sparse channel estimation for underwater acoustic OFDM systems with super-nested pilot design

Abstract

Underwater acoustic channels are usually sparse and have large delay spread. In this paper, super-nested array structure in the field of array signal processing is borrowed to be the pilot design of underwater acoustic OFDM systems, in order to better estimate large delay spread channels with limited number of pilots. Specifically, by constructing the pilot subcarriers’ covariance matrix and the pilot position difference, the virtual pilot on the differential co-array are employed for sparse channel estimation. In order to reduce the error between the estimated pilot subcarriers’ covariance matrix and the ideal covariance matrix, the cross-correlation matrix of pilot subcarriers is estimated in advance for interference cancellation. Then the sparse iterative covariance estimation algorithm (SPICE) is adopted to further refine the covariance matrix and improve the channel estimation performance. Simulation, pool and sea experimental results show that the proposed method can effectively estimate the large delay spread sparse channels and improve the performance of underwater acoustic OFDM systems.