MIMO-OFDM hydroacoustic channel estimation based on joint sparse optimization of AMP and OMP

Aiming at the problem of MIMO-OFDM system in hydroacoustic communication which is affected by multipath, bandwidth limitation and time-varying channel. We consider a two-phase sparse channel estimation algorithm Global AMP with Local OMP Refinement (GAMP-LOMP) based on the compressed sensing. This algorithm improves the performance through the framework of non-uniform guide frequency distribution and adaptive modulation. Simulations show that the algorithm strongly adaptive to guide frequency sparsity and Doppler effect, and excels in convergence speed, throughput, and parameter identification accuracy, making it suitable for dynamic hydroacoustic communication environments.