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Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter
The modulated wideband converter (MWC) is a kind of sub-Nyquist sampling system which is developed from compressed sensing theory. It accomplishes highly accurate broadband sparse signal recovery by multichannel sub-Nyquist sampling sequences. However, when the number of sparse sub-bands becomes lar...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087391/ https://www.ncbi.nlm.nih.gov/pubmed/27690034 http://dx.doi.org/10.3390/s16101602 |
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author | Xu, Ziyong Li, Zhi Li, Jian |
author_facet | Xu, Ziyong Li, Zhi Li, Jian |
author_sort | Xu, Ziyong |
collection | PubMed |
description | The modulated wideband converter (MWC) is a kind of sub-Nyquist sampling system which is developed from compressed sensing theory. It accomplishes highly accurate broadband sparse signal recovery by multichannel sub-Nyquist sampling sequences. However, when the number of sparse sub-bands becomes large, the amount of sampling channels increases proportionally. Besides, it is very hard to adjust the number of sampling channels when the sparsity changes, because its undersampling board is designed by a given sparsity. Such hardware cost and inconvenience are unacceptable in practical applications. This paper proposes a distributed modulated wideband converter (DMWC) scheme innovatively, which regards one sensor node as one sampling channel and combines MWC technology with a broadband cooperative spectrum sensing network perfectly. Being different from the MWC scheme, DMWC takes phase shift and transmission loss into account in the input terminal, which are unavoidable in practical application. Our scheme is not only able to recover the support of broadband sparse signals quickly and accurately, but also reduces the hardware cost of the single node drastically. Theoretical analysis and numerical simulations show that phase shift has no influence on the recovery of frequency support, but transmission loss degrades the recovery performance to a different extent. Nevertheless, we can increase the amount of cooperative nodes and select satisfactory nodes by a different transmission distance to improve the recovery performance. Furthermore, we can adjust the amount of cooperative nodes flexibly when the sparsity changes. It indicates DMWC is extremely effective in the broadband cooperative spectrum sensing network. |
format | Online Article Text |
id | pubmed-5087391 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-50873912016-11-07 Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter Xu, Ziyong Li, Zhi Li, Jian Sensors (Basel) Article The modulated wideband converter (MWC) is a kind of sub-Nyquist sampling system which is developed from compressed sensing theory. It accomplishes highly accurate broadband sparse signal recovery by multichannel sub-Nyquist sampling sequences. However, when the number of sparse sub-bands becomes large, the amount of sampling channels increases proportionally. Besides, it is very hard to adjust the number of sampling channels when the sparsity changes, because its undersampling board is designed by a given sparsity. Such hardware cost and inconvenience are unacceptable in practical applications. This paper proposes a distributed modulated wideband converter (DMWC) scheme innovatively, which regards one sensor node as one sampling channel and combines MWC technology with a broadband cooperative spectrum sensing network perfectly. Being different from the MWC scheme, DMWC takes phase shift and transmission loss into account in the input terminal, which are unavoidable in practical application. Our scheme is not only able to recover the support of broadband sparse signals quickly and accurately, but also reduces the hardware cost of the single node drastically. Theoretical analysis and numerical simulations show that phase shift has no influence on the recovery of frequency support, but transmission loss degrades the recovery performance to a different extent. Nevertheless, we can increase the amount of cooperative nodes and select satisfactory nodes by a different transmission distance to improve the recovery performance. Furthermore, we can adjust the amount of cooperative nodes flexibly when the sparsity changes. It indicates DMWC is extremely effective in the broadband cooperative spectrum sensing network. MDPI 2016-09-28 /pmc/articles/PMC5087391/ /pubmed/27690034 http://dx.doi.org/10.3390/s16101602 Text en © 2016 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 Xu, Ziyong Li, Zhi Li, Jian Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter |
title | Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter |
title_full | Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter |
title_fullStr | Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter |
title_full_unstemmed | Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter |
title_short | Broadband Cooperative Spectrum Sensing Based on Distributed Modulated Wideband Converter |
title_sort | broadband cooperative spectrum sensing based on distributed modulated wideband converter |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087391/ https://www.ncbi.nlm.nih.gov/pubmed/27690034 http://dx.doi.org/10.3390/s16101602 |
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