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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Main Authors: Yongwei Zhang, Pin Wan, Shunchao Zhang, Yonghua Wang, Nan Li
Format: Article
Language:English
Published: Wiley 2017-01-01
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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