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一种新型的认知无线电协作检测算法研究
引用本文:孟令文,李方伟,朱江.一种新型的认知无线电协作检测算法研究[J].微型机与应用,2013,32(14):61-64.
作者姓名:孟令文  李方伟  朱江
作者单位:重庆邮电大学移动通信技术重庆市重点实验室,重庆,400065
基金项目:国家自然科学基金项目,重庆市科委自然科学基金项目,重庆市教委科学技术研究项目,重庆邮电大学博士启动基金项目
摘    要:依据无线传感网络分簇协议,提出了一种算法。簇内采用能量自适应双门限检测,簇间通过Beta模型来并自动更新动态分配每一个簇头在数据融合中的权重因子,从而有效减小信任度较低的簇头对判决结果的影响,增强信任度较高的簇头参与度。理论分析和仿真结果表明,算法的复杂度和检测性能均优于传统的协作检测算法和分簇算法。

关 键 词:协作检测  分簇协议  Beta模型  权重因子

A new method of cooperative detections algorithms in cognitive radio
Meng Lingwen , Li Fangwei , Zhu Jiang.A new method of cooperative detections algorithms in cognitive radio[J].Microcomputer & its Applications,2013,32(14):61-64.
Authors:Meng Lingwen  Li Fangwei  Zhu Jiang
Affiliation:( Chongqing Key Lab of Mobile Communications Technology , Chongqing University of Posts and Telecommunications , Chongqing 400065 , China )
Abstract:Bases on the clustering protocol of wireless sensor networks, this paper proposes an algorithm. It uses doublethreshold detection within the cluster , the Beta model for updating the credit level and allocates dynamically to each cluster with head weight data fusion factor as early possible , weakening the judgment of the lower cluster head of the trust , strengthen the trust cluster head participation . Theoretical analysis and simulation results show that , the improved clustering algorithm is better than both traditional cooperative detection and traditional clustering cooperative spectrum sensing algorithm in the complexity of the algorithm and the detection performance .
Keywords:collaborative detection  clustering protocol  Beta model  weighting factor
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