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Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks
Current modulation recognition methods in wireless sensor networks rely too much on simulation datasets. Its practical application effect cannot reach the expected results. To address this issue, in this paper we collect a large amount of real-world wireless signal data based on the software radio d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371033/ https://www.ncbi.nlm.nih.gov/pubmed/35957271 http://dx.doi.org/10.3390/s22155715 |
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author | Liu, Kun Xiang, Xin Yin, Liyan |
author_facet | Liu, Kun Xiang, Xin Yin, Liyan |
author_sort | Liu, Kun |
collection | PubMed |
description | Current modulation recognition methods in wireless sensor networks rely too much on simulation datasets. Its practical application effect cannot reach the expected results. To address this issue, in this paper we collect a large amount of real-world wireless signal data based on the software radio device USRP 2920. We then propose a real radio frequency (RF) database architecture and preprocessing operators to manage real-world wireless signal data, conduct signal preprocessing, and export the dataset. Based on different feature datasets derived from the RF database, we propose a multidimensional feature hybrid network (MFHN), which is used to identify unknown signals by analyzing different kinds of signal features. Further, we improve MFHN and design a multifeatured joint migration network (MJMN) to identify small-sample targets. The experimental results show that the recognition rates for unknown target signals of the MFHN and MJMN are 82.7% and 93.2%, respectively. The proposed methods improve the recognition performance in the single node of wireless sensor networks in complex electromagnetic environments, which provides reference for subsequent decision fusion. |
format | Online Article Text |
id | pubmed-9371033 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93710332022-08-12 Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks Liu, Kun Xiang, Xin Yin, Liyan Sensors (Basel) Article Current modulation recognition methods in wireless sensor networks rely too much on simulation datasets. Its practical application effect cannot reach the expected results. To address this issue, in this paper we collect a large amount of real-world wireless signal data based on the software radio device USRP 2920. We then propose a real radio frequency (RF) database architecture and preprocessing operators to manage real-world wireless signal data, conduct signal preprocessing, and export the dataset. Based on different feature datasets derived from the RF database, we propose a multidimensional feature hybrid network (MFHN), which is used to identify unknown signals by analyzing different kinds of signal features. Further, we improve MFHN and design a multifeatured joint migration network (MJMN) to identify small-sample targets. The experimental results show that the recognition rates for unknown target signals of the MFHN and MJMN are 82.7% and 93.2%, respectively. The proposed methods improve the recognition performance in the single node of wireless sensor networks in complex electromagnetic environments, which provides reference for subsequent decision fusion. MDPI 2022-07-30 /pmc/articles/PMC9371033/ /pubmed/35957271 http://dx.doi.org/10.3390/s22155715 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Kun Xiang, Xin Yin, Liyan Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks |
title | Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks |
title_full | Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks |
title_fullStr | Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks |
title_full_unstemmed | Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks |
title_short | Radio Frequency Database Construction and Modulation Recognition in Wireless Sensor Networks |
title_sort | radio frequency database construction and modulation recognition in wireless sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371033/ https://www.ncbi.nlm.nih.gov/pubmed/35957271 http://dx.doi.org/10.3390/s22155715 |
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