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Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery
In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Dop...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891742/ https://www.ncbi.nlm.nih.gov/pubmed/31731649 http://dx.doi.org/10.3390/s19224976 |
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author | Li, Jie Chen, Fangjiong Liu, Songzuo Yu, Hua Ji, Fei |
author_facet | Li, Jie Chen, Fangjiong Liu, Songzuo Yu, Hua Ji, Fei |
author_sort | Li, Jie |
collection | PubMed |
description | In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Doppler-spread function is separable in delay and Doppler domain. Therefore, we introduce the low-rank criterion to estimate the UWA channels, which can help to improve the estimation performance in the case of strong dispersion. The estimator is based on the discrete delay-Doppler-spread function representation of channel, and is formulated as a low-rank matrix recovery problem which can be solved by the singular value projection technique. Simulation examples are carried out to demonstrate the effectiveness of the proposed low-rank-based channel estimator. |
format | Online Article Text |
id | pubmed-6891742 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68917422019-12-12 Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery Li, Jie Chen, Fangjiong Liu, Songzuo Yu, Hua Ji, Fei Sensors (Basel) Article In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Doppler-spread function is separable in delay and Doppler domain. Therefore, we introduce the low-rank criterion to estimate the UWA channels, which can help to improve the estimation performance in the case of strong dispersion. The estimator is based on the discrete delay-Doppler-spread function representation of channel, and is formulated as a low-rank matrix recovery problem which can be solved by the singular value projection technique. Simulation examples are carried out to demonstrate the effectiveness of the proposed low-rank-based channel estimator. MDPI 2019-11-15 /pmc/articles/PMC6891742/ /pubmed/31731649 http://dx.doi.org/10.3390/s19224976 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Jie Chen, Fangjiong Liu, Songzuo Yu, Hua Ji, Fei Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery |
title | Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery |
title_full | Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery |
title_fullStr | Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery |
title_full_unstemmed | Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery |
title_short | Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery |
title_sort | estimation of overspread underwater acoustic channel based on low-rank matrix recovery |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891742/ https://www.ncbi.nlm.nih.gov/pubmed/31731649 http://dx.doi.org/10.3390/s19224976 |
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