基于快速独立成分分析的高效合作频谱感知方法  

High efficient cooperative spectrum sensing method based on fast independent component analysis

作　　者：罗成[1] 邢志强[2] 李颖 曲洪权[2] 梅顺良[1] 宋鹏[2] 陈巍[1] 

机构地区：[1]清华大学电子工程系微波与数字通信国家重点实验室,北京100084 [2]北方工业大学信息工程学院,北京100144 [3]中国电子设备系统工程公司研究所,北京100141

出　　处：《传感器与微系统》2012年第12期19-22,共4页Transducer and Microsystem Technologies

基　　金：北京市教委科技发展计划重点资助项目(KZ2010100009009);国家自然科学基金资助项目(60832008;60902001)

摘　　要：针对能量检测无法区分主用户与次用户的局限性,将基于快速独立成分分析的盲源分离算法引入频谱感知以分离主次用户的混合信号。在此基础上,提出一种基于近似负熵的判决准则对分离后的信号进行检测。针对单节点频谱感知的不可靠性,将以上算法拓展到加权合作感知,同时提出一种选择合作感知算法以降低感知数据传输开销和检测延时。仿真结果表明:所提算法能够可靠地检测主用户并能有效地提高频谱利用率。To overcome the limitations of energy detection which cannot differentiate primary user （ PU ） from secondary user（ SU ）, blind source separation algorithm based on fast independent component analysis （ICA）is introduced to separate the mixed signals of PU and SU. A decision rule based on approximation of negentropy is proposed to perform detection after separation. Then a weighted cooperative sensing method based on fast ICA is proposed to combat the unreliability of single node sensing. Finally, a selective cooperative sensing algorithm is also proposed to reduce the transmission overhead and detecting delay. Simulations results show that the proposed algorithm can realize reliable detection of PU and increase the spectrum efficiency.

关 键 词：合作频谱感知 快速独立成分分析 加权合作感知 选择合作感知 

分 类 号：TN925[电子电信—通信与信息系统]