电讯技术2025，Vol.65Issue(11)：1747-1753,7.DOI:10.20079/j.issn.1001-893x.240722005
基于随机矩阵的盲频谱感知算法
Blind Spectrum Sensing Based on Random Matrix
摘要
Abstract
For the issue of decreased detection performance under low signal-to-noise ratio(SNR)conditions due to insufficient utilization of covariance matrix information in covariance-based eigenvalue algorithms for constructing detection statistics,a novel spectral sensing algorithm based on the ratio of the difference between the maximum and minimum eigenvalues to the harmonic mean of eigenvalues is proposed.This algorithm constructs the detection statistic by incorporating both the extreme eigenvalues and the harmonic mean of eigenvalues from the covariance matrix,thereby more comprehensively exploiting the eigenvalue information within the covariance matrix to enhance the detection capability.Furthermore,a novel approach for calculating the harmonic mean is introduced,leveraging the asymptotic distribution theory of eigenvalues in random matrices.This approach aims to not only improve the accuracy of the decision threshold but also further boost the detection performance.Simulation results demonstrate that the proposed algorithm,without requiring prior knowledge of primary users or channel conditions,achieves a detection probability increase of no less than 10%compared with several classic algorithms at-20 dB SNR.关键词
认知无线电/频谱感知/随机矩阵Key words
cognitive radio/spectrum sensing/random matrix分类
电子信息工程引用本文复制引用
殷晓虎,田冲,张珂珂,张安熠..基于随机矩阵的盲频谱感知算法[J].电讯技术,2025,65(11):1747-1753,7.基金项目
陕西省科技计划项目(2020GY-029) （2020GY-029）
