Spectrum Sensing Based on kNN Algorithm for 230 MHz Power Private Networks

摘要：

　　In this work,a spectrum sensing method based on K-nearest neighbors(kNN)algorithm is proposed.The energy and cyclic spectrum parameters of primary signal are extracted and system performance is analyzed.Results show that the detection probability of the proposed kNN method has better performance than support vector machine(SVM),energy detection(ED),and cyclostationary eigenvalue detection(CD)methods.False alarm rate of the kNN algorithm is much lower comparing with other detection methods.The proposed method reduces the complexity of cyclostationary signal detection as the kNN algorithm is easy to implement based on distance division,not on category.The provided results are useful for design of 230 MHz power private networks.

关键词： spectrum sensing kNN algorithm detection probability false alarm rate power private network

作者: Chunyan An Donglei Zhang Chenglong Yuan Liang Li Xiongwen Zhao Suiyan Geng Weijun Zheng WeiPing Shao

作者单位: Global Energy Interconnection Research Institute Co.,Ltd.Beijing,China School of Electrical and Electronic Engineering North China Electric Power University Beijing,China State Grid Jiaxing Power Supply Company Jiaxing,China State Grid Zhejiang Electric Power Limited company hangzhou,China

会议类型: 国际会议

会议名称: The 12th International Symposium Antennas, Propagation, and EM Theory(ISAPE 2018)?(第十二届天线、传播与电磁理论国际学术会议)

会议地点: 杭州

会议语种:英文

页码: 1-4

在线出版日期: 2018-12-03（万方平台首次上网日期，不代表论文的发表时间）