Spectrum sensing algorithm based on improved MME-Cyclic stationary feature

Abstract

The maximum and minimum eigenvalue (MME) spectrum sensing algorithm with features such as low complexity, no need of the prior information of authorized users, etc. However, because of its detection distribution function is not clear, researchers have improved the MME spectrum sensing algorithm from the point of view of the distribution function, but cannot solve the insufficient detection performance issues of these algorithms in low signal noise ratio (SNR). To solve this problem, this paper proposes two joint spectrum sensing algorithms based on two improved MME algorithms and cyclic stationary feature detection algorithm. Simulation results show that the performance of these two kinds of joint spectrum sensing algorithms is superior to both individual performance. At the same time, its performance is better than the performance of the simple MME-cyclic stationary feature joint spectrum sensing algorithm.