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Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters

Abstract

We consider the problem of identification of communication channels with a mix of static and time-varying parameters. Such scenarios are typical, among others, in underwater acoustics. In this paper, we further develop adaptive algorithms built on the local basis function (LBF) principle resulting in excellent performance when identifying time-varying systems. The main drawback of an LBF algorithm is its high complexity. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a significant reduction in the complexity for recursively computable basis functions, such as the complex exponentials. We propose a debiased fLBF algorithm which exploits the fact that only a part of the system parameters are time-varying. We also propose an adaptive technique to identify whether a particular tap is static or time-varying.

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DOI:
Digital Object Identifier (open in new tab) 10.1109/ICASSP43922.2022.9746753
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Copyright (2022 IEEE)

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Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) strony 5258 - 5262
Language:
English
Publication year:
2022
Bibliographic description:
Niedźwiecki M., Gańcza A., Shen L., Zakharov Y.: Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters// ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)/ : , 2022, s.5258-5262
DOI:
Digital Object Identifier (open in new tab) 10.1109/icassp43922.2022.9746753
Sources of funding:
Verified by:
Gdańsk University of Technology

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