Spectrum Sensing Method Based on Information Geometry and Deep Neural Network

doi:10.3390/e22010094

	Spectrum Sensing Method Based on Information Geometry and Deep Neural Network
	Du, Kaixuan 1; Wan, Pin 1,2; Wang, Yonghua 1,3; Ai, Xiongzhi 1; Chen, Huang 1
发表期刊	ENTROPY
	2020
卷号	22 期号:1 页码:13
通讯作者	Wang, Yonghua(wangyonghua@gdut.edu.cn)
摘要	Due to the scarcity of radio spectrum resources and the growing demand, the use of spectrum sensing technology to improve the utilization of spectrum resources has become a hot research topic. In order to improve the utilization of spectrum resources, this paper proposes a spectrum sensing method that combines information geometry and deep learning. Firstly, the covariance matrix of the sensing signal is projected onto the statistical manifold. Each sensing signal can be regarded as a point on the manifold. Then, the geodesic distance between the signals is perceived as its statistical characteristics. Finally, deep neural network is used to classify the dataset composed of the geodesic distance. Simulation experiments show that the proposed spectrum sensing method based on deep neural network and information geometry has better performance in terms of sensing precision.
关键词	spectrum sensing information geometry statistical manifold geodesic distance deep neural network
DOI	10.3390/e22010094
关键词[WOS]	ALGORITHMS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61971147] ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences[20180106] ; foundation of National & Local Joint Engineering Research Center of Intelligent Manufacturing Cyber-Physical Systems[008] ; Guangdong Provincial Key Laboratory of Cyber-Physical Systems[008] ; higher education quality projects of Guangdong Province ; Guangdong University of Technology ; [400170044] ; [400180004]
项目资助者	National Natural Science Foundation of China ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences ; foundation of National & Local Joint Engineering Research Center of Intelligent Manufacturing Cyber-Physical Systems ; Guangdong Provincial Key Laboratory of Cyber-Physical Systems ; higher education quality projects of Guangdong Province ; Guangdong University of Technology
WOS研究方向	Physics
WOS类目	Physics, Multidisciplinary
WOS记录号	WOS:000516825400083
出版者	MDPI
引用统计	被引频次：12[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/38774
专题	复杂系统管理与控制国家重点实验室
通讯作者	Wang, Yonghua
作者单位	1.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China 2.South Cent Univ Nationalities, Hubei Key Lab Intelligent Wireless Commun, Wuhan 430074, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Du, Kaixuan,Wan, Pin,Wang, Yonghua,et al. Spectrum Sensing Method Based on Information Geometry and Deep Neural Network[J]. ENTROPY,2020,22(1):13.
APA	Du, Kaixuan,Wan, Pin,Wang, Yonghua,Ai, Xiongzhi,&Chen, Huang.(2020).Spectrum Sensing Method Based on Information Geometry and Deep Neural Network.ENTROPY,22(1),13.
MLA	Du, Kaixuan,et al."Spectrum Sensing Method Based on Information Geometry and Deep Neural Network".ENTROPY 22.1(2020):13.