Improved Dynamic Compressive Sensing Based Channel Estimation for Single-Carrier Underwater Acoustic Communication

In this paper, an improved dynamic compressed sensing (DCS) scheme was proposed for time-varying channel estimation and tracking in single-carrier underwater acoustic (UWA) communication systems. It employs the stochastic weak selection gradient matching pursuit (StoWGradMP) algorithm to track the support set of the channel impulse response (CIR), and the reduced-order Kalman filter (KF) to estimate the significant taps. Different from existing schemes, the support set is allowed to expand or shrink during the estimation process. Experimental results show the proposed KF-StoWGradMP channel estimation outperforms existing DCS based channel estimation methods at lower complexity.