Enhanced Underwater Acoustic Channel Estimation using BSMVC Method
2024 IEEE/OES Thirteenth Current, Waves and Turbulence Measurement (CWTM)(2024)
Abstract
This paper introduces a novel approach, the Block Sparsity Constraint Maximum Versoria Criterion (BSMVC) method, for precise underwater acoustic channel estimation. By leveraging block sparsity constraints and the Maximum Versoria Criterion, the proposed method optimally captures inherent patterns and correlations within signal blocks, significantly improving the accuracy of channel representation. Through extensive simulations, the BSMVC method demonstrates superior performance compared to traditional approaches, showcasing its effectiveness in handling the dynamic nature of underwater channels. This method presents a promising advancement for researchers and practitioners aiming to enhance the reliability and performance of underwater communication systems.
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Key words
Cluster sparse system identification,maximum Versoria criterion (MVC),maximum correntropy criterion (MCC),ℓ∞,0-norm constraint
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