Estimation of Underwater Acoustic Channel via Block-Sparse Recursive Least-Squares Algorithm

Underwater acoustic communication suffers from the serious multipath effect and fast time variation due to the sophisticated ocean environment. General channel estimation schemes have limited performance in underwater acoustic communication because of the lacking exploitation of the underwater acous...

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Veröffentlicht in:2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) S. 1 - 6
Hauptverfasser: Tian, Tian, Wu, Fei-Yun, Yang, Kunde
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.09.2019
Schlagworte:
Approximation algorithms
block sparse
Channel estimation
Estimation
mixed norm constraint
Numerical simulation
Oceans
recursive least squares (RLS)
Signal processing
Signal processing algorithms
Signal to noise ratio
Simulation
Underwater acoustic channel (UAC)
Underwater acoustics
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Zusammenfassung:Underwater acoustic communication suffers from the serious multipath effect and fast time variation due to the sophisticated ocean environment. General channel estimation schemes have limited performance in underwater acoustic communication because of the lacking exploitation of the underwater acoustic channel (UAC) inherent property. In this work, we address a new approximate mixed ℓ 2,0 -norm, and based on that norm, we develop a block-sparse recursive least-squares (BS-RLS) algorithm for UAC estimation which takes advantage of the underlying block-sparse structure of UAC. The simulation result shows that the proposed BS-RLS algorithm improves the channel estimation quality under block-sparse condition.
DOI:10.1109/ICSPCC46631.2019.8960886