Adaptive and Efficient Nonlinear Channel Equalization for Underwater Acoustic Communication
Dariush Kari, Nuri Denizcan Vanli, Suleyman Serdar Kozat

TL;DR
This paper presents a hierarchical, adaptive nonlinear equalization method for underwater acoustic channels that significantly improves bit error rate performance while maintaining computational efficiency.
Contribution
It introduces a novel hierarchical, adaptive piecewise linear equalizer that learns the structure and adapts in real-time for challenging underwater channels.
Findings
Significant BER performance improvement over linear equalizers.
Efficient polynomial complexity adaptive algorithm.
Validated through realistic underwater acoustic channel simulations.
Abstract
We investigate underwater acoustic (UWA) channel equalization and introduce hierarchical and adaptive nonlinear channel equalization algorithms that are highly efficient and provide significantly improved bit error rate (BER) performance. Due to the high complexity of nonlinear equalizers and poor performance of linear ones, to equalize highly difficult underwater acoustic channels, we employ piecewise linear equalizers. However, in order to achieve the performance of the best piecewise linear model, we use a tree structure to hierarchically partition the space of the received signal. Furthermore, the equalization algorithm should be completely adaptive, since due to the highly non-stationary nature of the underwater medium, the optimal MSE equalizer as well as the best piecewise linear equalizer changes in time. To this end, we introduce an adaptive piecewise linear equalization…
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