认知无线电网络中压缩协作频谱感知  

Compressed Collaborative Spectrum Sensing in Cognitive Radio Networks

作　　者：石磊[1,2] 周正[1,2] 唐亮[1,2] 孙璇[1,2] 张静[1,2] 

机构地区：[1]泛网无线通信教育部重点实验室(北京邮电大学),北京100876 [2]北京邮电大学信息与通信工程学院,北京100876

出　　处：《北京邮电大学学报》2011年第5期76-79,91,共5页Journal of Beijing University of Posts and Telecommunications

基　　金：国家高技术研究发展计划项目(2009AA01Z262);国家自然科学基金项目(60772021);国家科技重大专项项目(2009ZX03006-006/-009);高等学校博士学科点专项科研基金项目(20070013029);Korean Ministry of Knowledge Economy Project(IITA-2009-C1090-0902-0019)

摘　　要：低频谱利用率条件下的信道状态向量具有稀疏性,为降低认知无线电网络中各个认知用户的频谱感知冗余,基于压缩感知技术提出了一种低复杂度的协作频谱感知方法.仿真结果表明,通过稀疏观测矩阵提高了单个认知用户感知过程的速度和效率;在融合中心对观测数据进行重构过程中使用因子图迭代算法,大幅降低了计算难度;同时可以根据认知网络中的频率使用情况,自适应调整认知用户的感知点数,确保整个网络的高效感知.The channel state vector is sparse under the conditions of low spectral efficiency. Based on compressed sensing technology, a low complexity collaborative spectrum sensing method is proposed to reduce the redundancy of each user in the cognitive radio networks. The processing speed and the efficiency of the single cognitive node are improved through the sparse measurement matrix. The fusion center reconstructs the observed data by the iterative algorithm of factor graph, dramatically reducing the computation. According to the frequency usage, the cognitive nodes adjust the sampling rate adaptively to ensure the maximum efficiency in the whole networks.

关 键 词：认知无线电网络 协作频谱感知 压缩感知 因子图 

分 类 号：TN929.5[电子电信—通信与信息系统]