Dynamic Compressive Sensing Based Adaptive Equalization for Underwater Acoustic Communications

Abstract

The wide-sense sparsity of a direct adaptive equalizer (DAE) for single-carrier underwater acoustic (UWA) communications has been recognized and utilized to reduce the equalization complexity via the idea of partial tap updating (PTU). Existing PTU schemes run in a batch mode so positions of the partial taps to be updated, once chosen, remain unchanged over a block. Under harsh channel conditions, however, the sparse structure of a DAE may change even within one block and existing PTU schemes will fail. This fact motivates us to seek a way to track also the dynamics of the DAE structure, in addition to its coefficients. In this paper, we propose to adopt the dynamic compressed sensing (DCS) technique to achieve the aforementioned goal. Specifically, the sparse adaptive orthogonal matching pursuit (SpAdOMP) as a typical greedy-type DCS algorithm, is employed. The taps of the resulting SpAdOMP DAE are updated with the affine projection algorithm (APA), leading to the SpAdOMP-APA-DAE. The SpAdOMP-APA-DAE was tested by experimental data collected in an at-sea UWA communication trial. Experimental results showed it significantly outperformed existing DAEs attributed to tracking only significant DAE taps while dropping negligible ones.