Joint Impulsive Noise Mitigation and Sparse Channel Estimation for Mobile Underwater Acoustic Communication

This letter presents a joint impulsive noise mitigation and sparse channel estimation algorithm for single-carrier systems in mobile underwater acoustic communication (UAC) to address the challenges posed by impulsive noise interference. The basis expansion model (BEM) is introduced to describe the underwater acoustic time-varying channels and reduce the channel parameters to be estimated. Based on the model, the variational Bayesian inference algorithm is employed to derive an iterative estimation expression for jointly estimating the sparse BEM channel coefficients and the impulsive noise. The proposed algorithm mitigates the impact of impulsive noise, leading to enhanced communication reliability. Simulations and sea trials validate the effectiveness of the proposed algorithm, highlighting its potential for practical applications in mobile underwater acoustic communication systems.