2015/04/29 by Liping Du, Du, Liping, Mihir Laghate +5
Computer Science · #Blind Source Separation Techniques #Cognitive Radio Networks and Spectrum Sensing #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI)
paper · pdf · doi:10.48550/arxiv.1504.07738
openalex publication_date 2015/04/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Eigenvalue-based detectors are considered as an important method of spectrum sensing since they do not require the information about the primary user (PU) signal. In this paper we propose a method to improve the performance of the eigenvalue-based detector. The proposed method introduces a new test statistic based on combinatorial matrix with components which are overlapping subgroups extracted from the array of received signals. As a result, its covariance matrix has a larger maximum eigenvalue and trace value than the one without overlapping. Simulation results show that our proposed method can further improve the detection performance of the optimal eigenvalue-based detector. The paper also shows the effect of different overlapping methods on the receiver operating characteristic curve.