Physical Layer Data Analysis for Abnormal User Detecting: A Random Matrix Theory Perspective

Abstract

Physical layer security (PLS) is a promising technology to enhance security performance of wireless communication systems, while the analyzing of PLS abnormal user detection is an important aspect of PLS research. Considering random matrix theory (RMT) is a time-efficient and theory-mature method, we will utilize RMT to analyze the abnormal user detection problem from the perspective of physical layer data analysis, where the carrier frequency offset (CFO) data is used as an indicator for abnormal user detection. Specially, the ring law theory and empirical spectral analysis of RMT are adopted for the analysis of CFO data, which is time-efficient and can be implanted in other detection methods. The proposed abnormal user detection method can provide a guidance for the appropriate choice of security enhancement technologies, so as to improve the utilization efficiency of different PLS technologies.