Underwater Acoustic OFDM Channel Estimation with Unknown Sparsity

Abstract

Underwater acoustic channels estimation accuracy seriously affects the demodulation performance of the receiver in underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) communications. Many channel estimation algorithms based on compressed sensing (CS) have been proposed. However, these algorithms usually needs the information of sparsity, while the information of sparsity is unavailable in many UWA OFDM communications. In this paper, a novel channel estimation algorithm based on fractional Fourier transform (FRFT) and orthogonal matching pursuit (OMP) is proposed, FRFT is introduced to process the synchronization signal, so sparsity is estimated. OMP is adopted to reconstruct channel impulse response (CIR). The most innovative feature of the proposed algorithm is the estimation of sparsity, which makes OMP algorithm more practical. Simulation results show that the proposed algorithm outperforms the least square (LS) and in UWA OFDM communication.