Spectrum Sensing Method Based on Information Geometry and Deep Neural Network
文献类型：期刊论文
| 作者 | Du, Kaixuan1; Wan, Pin1,3; Wang, Yonghua1,2; Ai, Xiongzhi1; Chen, Huang1 |
| 刊名 | ENTROPY
 |
| 出版日期 | 2020 |
| 卷号 | 22期号:1页码:13 |
| 关键词 | spectrum sensing information geometry statistical manifold geodesic distance deep neural network |
| DOI | 10.3390/e22010094 |
| 通讯作者 | Wang, Yonghua(wangyonghua@gdut.edu.cn) |
| 英文摘要 | 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. |
| WOS关键词 | ALGORITHMS |
| 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] |
| WOS研究方向 | Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:000516825400083 |
| 出版者 | MDPI |
| 资助机构 | 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 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/38773]  |
| 专题 | 自动化研究所_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.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.South Cent Univ Nationalities, Hubei Key Lab Intelligent Wireless Commun, Wuhan 430074, Peoples R China |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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