基于压缩感知的新型宽带频谱协作检测算法  

A Novel Cooperative Wideband Spectrum Detection Algorithm Based on Compressed Sensing

作　　者：陈磊[1] 王红军[1] 张旻[1] 毕光国[2] 

机构地区：[1]电子工程学院,安徽合肥230037 [2]东南大学国家移动通信研究实验室,江苏南京210096

出　　处：《空军工程大学学报（自然科学版）》2013年第4期76-80,共5页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：国家"973"基金资助项目(2007CB310603);国家自然科学基金资助项目(60972161)

摘　　要：针对认知无线电领域现有的宽带频谱检测技术在低信噪比情况下检测性能不足的问题,提出了一种新型的基于压缩感知的宽带频谱协作感知算法。该算法依据无线通信信号在循环谱域具有独特的稀疏特性,首先从信号相关函数的压缩采样中获取循环谱的观测值,然后利用稀疏自适应同步匹配追踪协作重构算法重构出整个宽带内所有信号的循环谱。仿真结果表明:该宽带检测算法在低信噪比和瑞利衰落信道条件下,具有较好的检测性能。同时,与以往经典的重构算法相比,该算法中提出的稀疏自适应同步匹配追踪协作重构算法在重构精度和算法复杂度等方面都有较大的提高。Aimed at the poor performance of the wideband spectrum detection under low SNR, a novel coop erative wideband spectrum detection algorithm is presented based on compressed sensing for cognitive ra- dio. By using the algorithm,first the measurements of cyclic spectrum from the signals＂ cross-correlation function of compressive samples are achieved on the basis of the unique sparse property of wireless commu nication signals in cyclic spectra region. Then all signals＇ cyclic spectra are reconstructed in the entire wide band by adopting the Sparse Adaptive Simultaneous Matching Pursuit （SASMP） cooperative algorithm. Simulation results show that the algorithm proposed has a better performance under Raleigh fading channel and low SNR environment, and the SASMP cooperative algorithm is improved in reconstructing quality and algorithm complexity compared with other classical algorithms.

关 键 词：认知无线电 压缩感知 稀疏特性 循环谱 宽带检测 

分 类 号：TN92[电子电信—通信与信息系统]