A sparse adaptive decision feedback equalization approach for the high data rate vertical underwater acoustic communication in deep sea

Abstract

In underwater acoustic communication (UWAC) environments, multichannel decision feedback equalizer (MDFE) techniques combined with single carrier modulation schemes are widely employed to suppress multipath interference while adapting to time-varying channel response. While MDFE is a powerful technique, the estimation of the numerous filter taps is generally complex problem, and the numerically complexities can lead to the instability of solutions including the occurrence of the burst errors. In this study, we propose a method that introduces L1-norm regularization into the adaptive algorithm of MDFE, considering a sparse channel response environment in the vertical UWAC channel in deep-sea areas. We applied the proposed method to simulation and experimental data, comparing it with conventional methods. As a result, the proposed method demonstrated a clear improvement in bit error rate performance, obtaining sparse filter coefficient estimates and effectively suppressing burst errors.