一种新型的认知无线电协作检测算法研究

A new method of cooperative detections algorithms in cognitive radio

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。

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 .