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Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing
Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5426933/ https://www.ncbi.nlm.nih.gov/pubmed/28441763 http://dx.doi.org/10.3390/s17040937 |
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author | He, Chengbing Jing, Lianyou Xi, Rui Li, Qinyuan Zhang, Qunfei |
author_facet | He, Chengbing Jing, Lianyou Xi, Rui Li, Qinyuan Zhang, Qunfei |
author_sort | He, Chengbing |
collection | PubMed |
description | Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between [Formula: see text] and [Formula: see text] for the conventional TR-DFE, and between [Formula: see text] and [Formula: see text] for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB. |
format | Online Article Text |
id | pubmed-5426933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54269332017-05-12 Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing He, Chengbing Jing, Lianyou Xi, Rui Li, Qinyuan Zhang, Qunfei Sensors (Basel) Article Multichannel receivers are usually employed in high-rate underwater acoustic communication to achieve spatial diversity. In the context of multichannel underwater acoustic communications, passive time reversal (TR) combined with a single-channel adaptive decision feedback equalizer (TR-DFE) is a low-complexity solution to achieve both spatial and temporal focusing. In this paper, we present a novel receiver structure to combine passive time reversal with a low-order multichannel adaptive decision feedback equalizer (TR-MC-DFE) to improve the performance of the conventional TR-DFE. First, the proposed method divides the whole received array into several subarrays. Second, we conduct passive time reversal processing in each subarray. Third, the multiple subarray outputs are equalized with a low-order multichannel DFE. We also investigated different channel estimation methods, including least squares (LS), orthogonal matching pursuit (OMP), and improved proportionate normalized least mean squares (IPNLMS). The bit error rate (BER) and output signal-to-noise ratio (SNR) performances of the receiver algorithms are evaluated using simulation and real data collected in a lake experiment. The source-receiver range is 7.4 km, and the data rate with quadrature phase shift keying (QPSK) signal is 8 kbits/s. The uncoded BER of the single input multiple output (SIMO) systems varies between [Formula: see text] and [Formula: see text] for the conventional TR-DFE, and between [Formula: see text] and [Formula: see text] for the proposed TR-MC-DFE when eight hydrophones are utilized. Compared to conventional TR-DFE, the average output SNR of the experimental data is enhanced by 3 dB. MDPI 2017-04-24 /pmc/articles/PMC5426933/ /pubmed/28441763 http://dx.doi.org/10.3390/s17040937 Text en © 2017 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 He, Chengbing Jing, Lianyou Xi, Rui Li, Qinyuan Zhang, Qunfei Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing |
title | Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing |
title_full | Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing |
title_fullStr | Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing |
title_full_unstemmed | Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing |
title_short | Improving Passive Time Reversal Underwater Acoustic Communications Using Subarray Processing |
title_sort | improving passive time reversal underwater acoustic communications using subarray processing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5426933/ https://www.ncbi.nlm.nih.gov/pubmed/28441763 http://dx.doi.org/10.3390/s17040937 |
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