A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks
In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless...
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Format: | Article |
Language: | English |
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Wiley
2017-01-01
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Series: | Advances in Multimedia |
Online Access: | http://dx.doi.org/10.1155/2017/2895680 |
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author | Yongwei Zhang Pin Wan Shunchao Zhang Yonghua Wang Nan Li |
author_facet | Yongwei Zhang Pin Wan Shunchao Zhang Yonghua Wang Nan Li |
author_sort | Yongwei Zhang |
collection | DOAJ |
description | In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance. |
format | Article |
id | doaj-art-52cfa7173f474f4ebbb3fc2f1981998a |
institution | Kabale University |
issn | 1687-5680 1687-5699 |
language | English |
publishDate | 2017-01-01 |
publisher | Wiley |
record_format | Article |
series | Advances in Multimedia |
spelling | doaj-art-52cfa7173f474f4ebbb3fc2f1981998a2025-02-03T06:12:44ZengWileyAdvances in Multimedia1687-56801687-56992017-01-01201710.1155/2017/28956802895680A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor NetworksYongwei Zhang0Pin Wan1Shunchao Zhang2Yonghua Wang3Nan Li4School of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaSchool of Automation, Guangdong University of Technology, Guangzhou 510006, ChinaIn order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.http://dx.doi.org/10.1155/2017/2895680 |
spellingShingle | Yongwei Zhang Pin Wan Shunchao Zhang Yonghua Wang Nan Li A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks Advances in Multimedia |
title | A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks |
title_full | A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks |
title_fullStr | A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks |
title_full_unstemmed | A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks |
title_short | A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks |
title_sort | spectrum sensing method based on signal feature and clustering algorithm in cognitive wireless multimedia sensor networks |
url | http://dx.doi.org/10.1155/2017/2895680 |
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