A Novel Goodness of Fit Test Spectrum Sensing Using Extreme Eigenvalues  

作　　者：LI He ZHAO Wenjing LIU Chang JIN Minglu YOO Sang-Jo 

机构地区：[1]School of Information and Communication Engineering,Dalian University of Technology,Dalian 116024,China [2]Department of Information and Communication Engineering,Inha University,Incheon 22212,South Korea

出　　处：《Chinese Journal of Electronics》2020年第6期1201-1206,共6页电子学报（英文版）

基　　金：supported by the Ministry of Science,ICT(MSIT),South Korea,under the Information Technology Research Center(ITRC)support program(IITP-2019-2014-1-00729);supervised by the Institute of Information and communications Technology Planning and Evaluation(IITP).

摘　　要：The existing Goodness of fit(GoF)test based spectrum sensing algorithms mostly use samples or energies as observations to make decisions,which can hardly achieve satisfactory performance especially when the Primary user(PU)signals are highly correlated.Meanwhile,the eigenvalue of covariance matrix can reflect signal correlations well.Motivated by this,we study the distribution of eigenvalue and propose an eigenvalue based GoF spectrum sensing algorithm.In the proposed scheme,we use the ratios of maximum to minimum eigenvalue as observations and thus it can bring performance improvements through capturing correlation of PU signals.We also provide the related theoretical analysis for the proposed method.Simulation results show that the proposed method overcomes the problem of noise uncertainty and achieves performance improvement over the classical samples-based GoF test.

关 键 词：Cognitive radio spectrum sensing goodness of fit test EIGENVALUE 

分 类 号：TN925[电子电信—通信与信息系统]