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Underwater acoustic channel estimation via complex Homotopy

Underwater acoustic (UWA) channel is typically sparse. In this paper, a complex Homotopy algorithm is presented and then applied for UWA OFDM channel estimation. Two enhancements that exploit UWA channel temporal correlation for the compressed-sensing(CS)-based channel estimators are proposed. The first one is based on a first-order Gauss-Markov (GM) model which uses the previous channel estimate to assist current one. The other is to use the recursive least-squares (RLS) algorithm together with the CS algorithms to track the time-varying UWA channel. Simulation results show that the Homotopy algorithm offers faster and more accurate UWA channel estimation performance than other sparse recovery methods, and the proposed enhancements offer further performance improvement.