Robust symbol detection for single-carrier underwater acoustic communication in impulsive noise environment.

This paper addresses robust underwater acoustic communication in the presence of impulsive noise. We propose a single-carrier iterative symbol detection method, which combines variational Bayesian inference (VBI) and vector approximate message passing (VAMP) for impulsive noise cancellation. Unlike existing methods, we model the measurements as a combination of two components: clean data without impulsive noise and impulse-noise-induced outliers. A set of binary indicator variables is used to identify outliers automatically. Under the proposed mixed model, we derive a VBI-based symbol detection method that can alternatively detect communication symbols and impulsive noise, and compensate for the impulsive noise when detecting communication symbols. To further improve detection performance, we integrate the VAMP into the VBI framework for communication symbols detection. Additionally, to reduce the overall complexity of the communication system, we propose a channel estimation method based on damped generalized approximate message passing. Simulation and experimental results show that the proposed detection method outperforms existing methods in terms of robustness and bit error rate.