A Blind Spectrum Sensing Based on Low-Rank and Sparse Matrix Decomposition  

作　　者：Junsheng Mu Xiaojun Jing Hai Huang Ning Gao 

机构地区：[1]Laboratory of Biological Recognition and Information Application, Beijing University of Posts and Telecommunications [2]Key Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education

出　　处：《China Communications》2018年第8期118-125,共8页中国通信（英文版）

基　　金：supported by the open project fund (No. 201600017) of the National Key Laboratory of Electromagnetic Environment;NSFC (No.61471066), China

摘　　要：As a crucial component in Cognitive Radio(CR) networks, spectrum sensing has been attracting lots of attention. Some conventional methods for spectrum sensing are sensitive to uncertain signal and noise, its applicability is limited thereof. In this paper, a novel blind spectrum sensing method is proposed, where low-rank and sparse matrix decomposition is applied to the observation signal of a CR in the frequency domain. Then the ratio of the energy of the sparse part and the received signal in the time domain is considered as the criterion to decide whether the radio frequency band is idle by means of a comparison with a predefined threshold. The proposed method is independent of prior knowledge of signal and white noise, and has a better detection performance. Simulation experiments verify the performance of the proposed method in additive white Gaussian noise(AWGN), Rayleighand Rician channels.As a crucial component in Cogni- tive Radio （CR） networks, spectrum sensing has been attracting lots of attention. Some conventional methods for spectrum sensing are sensitive to uncertain signal and noise, its applicability is limited thereof. In this paper, a novel blind spectrum sensing method is proposed, where low-rank and sparse matrix decomposition is applied to the observation signal of a CR in the frequency domain. Then the ratio of the energy of the sparse part and the received signal in the time domain is considered as the criterion to decide whether the radio frequency band is idle by means of a comparison with a predefined threshold. The proposed method is independent of prior knowledge of signal and white noise, and has a better detection performance. Simulation experiments verify the performance of the proposed method in additive white Gaussian noise （AWGN）, Rayleighand Rician channels.

关 键 词：spectrum sensing cognitive radio OFDM RAYLEIGH AWGN 

分 类 号：TN925[电子电信—通信与信息系统]