Sliding-window homotopy adaptive filter for estimation of sparse UWA channels
Sliding-window homotopy adaptive filter for estimation of sparse UWA channels
In this paper, a sparse recursive least squares (RLS) adaptive filter is investigated in application to channel estimation in underwater acoustic (UWA) channels. The adaptive filter is based on sliding-window, homotopy, and dichotomous coordinate descent iterations. It is used in a multi-antenna receiver of an UWA communication system with guard-free orthogonal frequency division multiplexing (OFDM) signals and superimposed pilot symbols. More specifically, it is used for channel estimation in the channel-estimate-based equalizer. We compare the sliding-window homotopy RLS adaptive filter with the exponential-window homotopy and classic RLS algorithms. The results show that the proposed algorithm provides an improved performance compared to the other adaptive filters. The comparison is based on signals recorded on a 14-element vertical antenna array in sea trials at a distance of 105 km transmitted by a fast moving transducer. In these conditions, error-free transmission is achieved with a spectral efficiency of 0.33 bit/s/Hz.
underwater acoustics, underwater acoustic communication, array signal processing
Li, Jianghui
9c589194-00fa-4d42-abaf-53a32789cc5e
Zakharov, Yuriy
2abf7642-edba-4f15-8b98-4caca66510f6
September 2016
Li, Jianghui
9c589194-00fa-4d42-abaf-53a32789cc5e
Zakharov, Yuriy
2abf7642-edba-4f15-8b98-4caca66510f6
Li, Jianghui and Zakharov, Yuriy
(2016)
Sliding-window homotopy adaptive filter for estimation of sparse UWA channels.
In 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM).
IEEE.
4 pp
.
(doi:10.1109/SAM.2016.7569608).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper, a sparse recursive least squares (RLS) adaptive filter is investigated in application to channel estimation in underwater acoustic (UWA) channels. The adaptive filter is based on sliding-window, homotopy, and dichotomous coordinate descent iterations. It is used in a multi-antenna receiver of an UWA communication system with guard-free orthogonal frequency division multiplexing (OFDM) signals and superimposed pilot symbols. More specifically, it is used for channel estimation in the channel-estimate-based equalizer. We compare the sliding-window homotopy RLS adaptive filter with the exponential-window homotopy and classic RLS algorithms. The results show that the proposed algorithm provides an improved performance compared to the other adaptive filters. The comparison is based on signals recorded on a 14-element vertical antenna array in sea trials at a distance of 105 km transmitted by a fast moving transducer. In these conditions, error-free transmission is achieved with a spectral efficiency of 0.33 bit/s/Hz.
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More information
Accepted/In Press date: 1 April 2016
e-pub ahead of print date: 10 July 2016
Published date: September 2016
Venue - Dates:
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), , Rio de Janerio, Brazil, 2016-07-10 - 2016-07-13
Keywords:
underwater acoustics, underwater acoustic communication, array signal processing
Identifiers
Local EPrints ID: 425537
URI: http://eprints.soton.ac.uk/id/eprint/425537
ISSN: 2151-870X
PURE UUID: 198c229d-4130-4396-bda0-8031cfe45dfa
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Date deposited: 24 Oct 2018 16:30
Last modified: 15 Mar 2024 22:18
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Author:
Yuriy Zakharov
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