基于证据可信度的D-S理论协作频谱感知方法

D-S证据理论频谱感知算法中,针对当协作用户数增加时所引起的报告数据量迅速增大、带宽开销增加问题,将本地测量统计量中不确定度分配到确定信息中,减少了向融合中心发送的数据量,有效降低了带宽开销。其次,针对高冲突数据对D-S证据理论融合结果影响大的问题,通过评估每个证据的可信度,将可信度作为权重来计算加权平均证据,降低了高冲突证据对融合结果的影响。仿真结果表明,所提方法在有效降低了报告带宽开销的同时,能够减少高冲突证据对融合结果的影响。

D-S theory and evidence reliability based cooperative spectrum sensing method

In the cooperative sensing algorithms based on D-S evidence theory, the reporting data and bandwidth cost will rapidly increase with the increasing of cooperative user numbers. To solve this problem, the uncertainty of detected information is assigned into the certainty, and the reporting data and bandwidth cost are effectively reduced. Then focus on the large-influenced fusion result caused by highly conflicting data, the reliability of every evidence is used as a weight to calculate the weighted average evidence, and the influence of high conflicting data is reduced. The simulation results show that the method proposed can effectively reduce the bandwidth and the impact from high conflicting evidence on the fusion results.