Dynamic compressed sensing estimation of time varying underwater acoustic channel

Weihua Jiang; Xiaoyang Wang; Feng Tong

doi:10.1109/ICSPCC.2017.8242623

Dynamic compressed sensing estimation of time varying underwater acoustic channel

Weihua Jiang, Xiaoyang Wang, Feng Tong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper the dynamic compressed sensing (DCS) estimation of time varying underwater acoustic (UWA) channel is investigated. By modeling the time varying UWA channels as sparse set consisting with constant and time-varying supports, the estimation of time varying UWA channel is transformed into a problem of dynamic compressed sensing (DCS) sparse recovery. Employing the combination of Kalman filter and compressed sensing for channel estimation, a time reversal receiver is driven by the channel estimate to improve the performance of the underwater acoustic communication. Finally the experimental results with the field data obtained in a shallow water acoustic communication experiment indicate that, the proposed algorithm outperforms the classic channel estimation methods.

Original language	English
Title of host publication	2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781538631409
DOIs	https://doi.org/10.1109/ICSPCC.2017.8242623
State	Published - 29 Dec 2017
Externally published	Yes
Event	7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017 - Xiamen, Fujian, China Duration: 22 Oct 2017 → 25 Oct 2017

Publication series

Name	2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017
Volume	2017-January

Conference

Conference	7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017
Country/Territory	China
City	Xiamen, Fujian
Period	22/10/17 → 25/10/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Kalman Filter
dynamic compressed sensing (DCS)
multipath
time reversal
time varying

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing

Access to Document

10.1109/ICSPCC.2017.8242623

Cite this

Jiang, W., Wang, X., & Tong, F. (2017). Dynamic compressed sensing estimation of time varying underwater acoustic channel. In 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017 (pp. 1-4). (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSPCC.2017.8242623

Jiang, Weihua ; Wang, Xiaoyang ; Tong, Feng. / Dynamic compressed sensing estimation of time varying underwater acoustic channel. 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-4 (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017).

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title = "Dynamic compressed sensing estimation of time varying underwater acoustic channel",

abstract = "In this paper the dynamic compressed sensing (DCS) estimation of time varying underwater acoustic (UWA) channel is investigated. By modeling the time varying UWA channels as sparse set consisting with constant and time-varying supports, the estimation of time varying UWA channel is transformed into a problem of dynamic compressed sensing (DCS) sparse recovery. Employing the combination of Kalman filter and compressed sensing for channel estimation, a time reversal receiver is driven by the channel estimate to improve the performance of the underwater acoustic communication. Finally the experimental results with the field data obtained in a shallow water acoustic communication experiment indicate that, the proposed algorithm outperforms the classic channel estimation methods.",

keywords = "Kalman Filter, dynamic compressed sensing (DCS), multipath, time reversal, time varying",

author = "Weihua Jiang and Xiaoyang Wang and Feng Tong",

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year = "2017",

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language = "English",

series = "2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017",

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Jiang, W, Wang, X & Tong, F 2017, Dynamic compressed sensing estimation of time varying underwater acoustic channel. in 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 7th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017, Xiamen, Fujian, China, 22/10/17. https://doi.org/10.1109/ICSPCC.2017.8242623

Dynamic compressed sensing estimation of time varying underwater acoustic channel. / Jiang, Weihua; Wang, Xiaoyang; Tong, Feng.
2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-4 (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In this paper the dynamic compressed sensing (DCS) estimation of time varying underwater acoustic (UWA) channel is investigated. By modeling the time varying UWA channels as sparse set consisting with constant and time-varying supports, the estimation of time varying UWA channel is transformed into a problem of dynamic compressed sensing (DCS) sparse recovery. Employing the combination of Kalman filter and compressed sensing for channel estimation, a time reversal receiver is driven by the channel estimate to improve the performance of the underwater acoustic communication. Finally the experimental results with the field data obtained in a shallow water acoustic communication experiment indicate that, the proposed algorithm outperforms the classic channel estimation methods.

AB - In this paper the dynamic compressed sensing (DCS) estimation of time varying underwater acoustic (UWA) channel is investigated. By modeling the time varying UWA channels as sparse set consisting with constant and time-varying supports, the estimation of time varying UWA channel is transformed into a problem of dynamic compressed sensing (DCS) sparse recovery. Employing the combination of Kalman filter and compressed sensing for channel estimation, a time reversal receiver is driven by the channel estimate to improve the performance of the underwater acoustic communication. Finally the experimental results with the field data obtained in a shallow water acoustic communication experiment indicate that, the proposed algorithm outperforms the classic channel estimation methods.

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KW - time reversal

KW - time varying

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PB - Institute of Electrical and Electronics Engineers Inc.

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Jiang W, Wang X, Tong F. Dynamic compressed sensing estimation of time varying underwater acoustic channel. In 2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-4. (2017 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2017). doi: 10.1109/ICSPCC.2017.8242623

Dynamic compressed sensing estimation of time varying underwater acoustic channel

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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