计算机工程2017，Vol.43Issue(9)：68-74,7.DOI:10.3969/j.issn.1000-3428.2017.09.013
基于特征值极限分布的双门限DMM频谱感知算法
Double Threshold DMM Spectrum Sensing Algorithm Based on Limiting Eigenvalue Distribution
摘要
Abstract
This paper uses the Random Matrix Theory(RMT) of eigen structure,analyzes and researches the limiting eigenvalue distribution of sampling covariance matrix for multiple cognitive users,and proposes a double threshold spectrum sensing algorithm based on Difference Between the Maximum Eigenvalue and the Minimum Eigenvalue (DMM).The double thresholds are obtained by using the limiting eigenvalue distribution of both maximum and minimum eigenvalues.The soft decision and hard decision are adopted in both internal and external parts of the double threshold to achieve the final decision result.The self-adaptability of detected thresholds is realized by using eigenvalue noise estimation,which overcomes the impact of noise uncertainty on spectrum sensing.The simulation result shows that the algorithm has better detection performance than the DMM algorithm and Energy Detection(ED) algorithm under the situation of low signal noise ratio,low false alarm probability and relatively small number of sampling points,and it has good stability and strong robustness.关键词
认知无线电/频谱感知/随机矩阵理论/特征值极限分布/最大最小特征值之差Key words
Cognitive Radio (CR)/spectrum sensing/Random Matrix Theory (RMT)/limiting eigenvalue distribution/Difference Between the Maximum Eigenvalue and the Minimum Eigenvalue(DMM)分类
信息技术与安全科学引用本文复制引用
高鹏,刘芸江,高维廷,李曼..基于特征值极限分布的双门限DMM频谱感知算法[J].计算机工程,2017,43(9):68-74,7.基金项目
国家自然科学基金(61571364) （61571364）
中国博士后科学基金(2016M603044). （2016M603044）
