电讯技术2017，Vol.57Issue(7)：745-749,5.DOI:10.3969/j.issn.1001-893x.2017.07.002
基于压缩感知和最小二乘的分布式协作频谱感知
Distributed Cooperative Spectrum Sensing Based on Compressed Sensing and Least Squares
摘要
Abstract
For the shortcomings that centralized cognitive radio(CR) spectrum estimation sets strict requirement for fusion centers and has poor tolerance for node failure,this paper proposes a distributed multi-node cooperative algorithm based on compressed sensing.Each node of CR networks obtains the local compressed sampling according to compressed sampling theory firstly,then recovers the spectrum by exploiting l1 norm constrained algorithm.Finally,the spectrum estimated at the node is delivered to the next neighboring node until the algorithm converges.The theoretical analysis and simulation results show that this algorithm has not only low computational complexity and fast convergence speed,but also high accuracy and high reliability.关键词
认知无线电/压缩感知/协作频谱感知/最小二乘Key words
cognitive radio/compressed sensing/cooperative spectrum sensing/least squares分类
信息技术与安全科学引用本文复制引用
杨亚旗,姚彦鑫..基于压缩感知和最小二乘的分布式协作频谱感知[J].电讯技术,2017,57(7):745-749,5.基金项目
国家自然科学基金资助项目(61302073) （61302073）
北京市自然科学基金资助项目(4172021,Z160002) （4172021,Z160002）
北京市教育委员会科技发展计划面上项目(KM201711232010) （KM201711232010）
