基于多层分簇优化的认知无线电网络协作频谱感知策略

Multilayer clustering optimization based cooperative spectrum sensing scheme of cognitive radio network

针对认知无线电网络(CRN)中基于簇的频谱感知策略的检测性能和能耗问题,提出一种基于多层分簇优化的协作频谱感知策略。首先,将CRN分成多个簇,进而将簇分成多个组,再将组分成多个子组,构建三层分簇结构;然后,利用提出的优化算法获得最优的分簇参数和决策阈值;最后,通过投票机制和K-out-of-N规则对各级决策进行聚合,进行频谱感知。实验结果表明,该方案在获得较高主要用户(PU)频谱占用检测率的同时,能够最大限度地减少信道开销,提高了网络的吞吐量。

To solve the problems of detection performance and energy consumption of the clustering-based spectrum sensing scheme in cognitive radio network（CRN）,a cooperative spectrum sensing scheme based on multilayer clustering optimization is proposed. With the schene,the CRN is divided into several clusters,then the clusters are divided into several groups,and the groups are divided into several subgroups to construct a three- layer clustering structure. The proposed optimization algorithm is used to obtain the optimal clustering parameters and decision- making thresholds. The decision of each level is clustered by means of the voting mechanism and K-out-of-N rule to perform the spectrum sensing. The experimental results show that the proposed scheme can reduce the channel overhead and improve the network throughput to the maximum extent while obtaining the high detection rate of the primary user（PU）spectrum occupancy.