Low-Complexity Fully Adaptive Equalization Algorithm for UWA Communication Systems

This paper presents an improved turbo equalization algorithm for underwater acoustic communications, designed to tackle severe time variations with reduced computational complexity. Our approach uses an enhanced optimization criterion that leverages soft information exchanged between the channel decoder and the equalizer to refine the equalizer's adaptation process. In contrast to previous works, our proposal has low computational complexity by selectively choosing the most relevant terms to be computed by the equalizer, and also by considering the sparsity of the Underwater Acoustic (UWA) channel. Our simulations, both on synthetic and real underwater channels, demonstrate that our method outperforms conventional equalization techniques. Compared to the full-complexity adaptive algorithm, our proposal shows better Bit Error Rate (BER) performance and lowers the computational complexity by about 90% for the 16-QAM constellation.