Low-SNR Energy Detection Based on Relevance in Power Density Spectrum

Energy detection is the most commonly used spectrum sensing method in cognitive radio because of its simplicity and there is no need for priori information. However, the performance of energy detection will seriously deteriorate under low-SNR condition. Various improved methods have been proposed to solve this problem, but at the expense of high complexity. This paper introduces an energy detection method based on the relevance in power density spectrum. It uses an iterative method to precisely estimate the noise power without any priori information and makes use of the relevance between occupied frequency points to detect low-SNR signals effectively. Simulation results show that the proposed method has better performance and lower complexity than traditional methods.