认知无线电网络中利用FEC和DE的多节点频谱感知算法  

Multi-nodes Cooperative Spectrum Sensing Algorithms Based on FEC and DE in Cognitive Radio Network

作　　者：马同伟[1] 刘丹[1] 解瑞云[1] 海本斋[2] 

机构地区：[1]河南机电高等专科学校计算机科学与技术系,河南新乡453000 [2]武汉理工大学信息工程学院,武汉430070

出　　处：《计算机测量与控制》2015年第4期1305-1308,共4页Computer Measurement &Control

基　　金：国家自然科学基金(61103143);河南省教育厅科学技术研究重点资助项目(14A520085);河南省教师教育课程改革项目(2014-JSJYYB-026)

摘　　要：针对认知无线电网络(CRN)中空闲频谱感知困难的问题,提出了利用前向纠错和差分进化算法的多节点频谱感知算法;首先,利用基于差分进化算法的协同检测完成信号感知;然后,研究了信道噪声对频谱感知性能的影响;最后,分析了前向纠错技术在信道存在噪声时对频谱感知性能的影响;仿真实验将纠错和无纠错控制信道的不同信噪比作为依据,采用3种不同的检测方法评估了文章的算法;结果表明,在存在噪声的认知无线电网络中,该算法提高了系统的性能和检测概率,且协同感知算法的性能随着节点数目的增加而提高,该算法适合应用于实时性要求较高的应用程序。For the issue of the free spectrum in cognitive radio networks （CRN）, multi--nodes sensing algorithms based on forward error correction （FEC） and differential evolution （DE） algorithm is proposed. Firstly, cooperative detection based on DE algorithm is used to predict the presence of signal. Then the effect of noise in control channel is studied on the spectrum sensing capabilities. Finally, the effect of forward error correction technique in the noisy control channel on the sensing capabilities is analyzed. Our algorithm is evaluated through three different detection methods and different signal--to--noise ratio in control channel with and without error correction is set as evaluate basis. The simulate results show that detection probability or the system efficiency can be increased with error correction technique and the performance of the cooperative sensing algorithm improves with increase in number of nodes in noisy cognitive radio network. Proposed algorithm is suitable for applications with high real--time demand.

关 键 词：前向纠错 差分进化 认知无线电网络 频谱感知 协同检测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]