一种基于信任度分簇处理协作感知算法

摘要

针对恶劣环境下能量感知算法感知性能差的问题，提出一种基于信任度分簇处理协作感知算法。在双门限能量检查算法基础上给出一种由采样信号均值、信噪比、采样信号相对误差组成的新信任度系数，并根据新信任度系数对双门限之间认知节点可靠性进行评定，并对需要优化的采样信号值修正后参与传统单门限能量感知得到本地感知结果；同时为不同可靠度认知节点对协作感知判决分配不同贡献，给出由采样信号方差和信噪比方差组成新权重值加权协作判决。实验仿真表明，该算法感知性能较传统双门限协作感知算法和信任度加权融合算法有一定改善。%To the problem of poor awareness of energy aware algorithm in poor environment,this paper proposed a cooperative sensing algorithm of handling by clustering based on trust factor.It gave the new trust factor of the composition of the sampling signal relative error,SNR,average sampling signal based on the double-threshold energy sensing algorithm.It assessed the re-liability of cognitive nodes of the between high threshold and low threshold and corrected the sampling signal of needs to be op-timized according to it,which participated in a traditional single-threshold energy detection obtain local sensing results.Mean-while,to distribute the different contribution of judgement collaborative for the different reliability of the sensing codes,it gave the new weight value by the component of sampling signal variance and SNR and participate in collaboration judgment weigh-ted.Simulation results show that the improved algorithm has a certain improvement in perceived performance,compared with the traditional double-threshold cooperative sensing algorithm and confidence weighted fusion algorithm.