基于证据折扣优化DSmT的协同频谱感知器

Cooperative Spectrum Sensing Using Discounted DSmT

  • 摘要: 协同频谱感知器通过充分利用多个认知无线电用户的空间分集增益,对抗单用户深度衰落和阴影效应问题,降低了感知系统对本地感知用户的灵敏度要求,减少由于单用户检测不确定性带来的系统误判。利用D-S方法进行协同频谱感知,通过在本地提取置信指派,再上传至融合中心进行证据推理与判决,占用较窄的控制信道带宽,达到优于传统方法的检测性能,如“或”、“与”和“最优融合”感知方法。但低信噪用户带来的冲突数据会限制D-S方法性能,使其信噪鲁棒性较差。本文首先定义感知用户基本置信指派函数,基于DSmT提出证据折扣优化 DSmT协同频谱感知器。该感知器根据不同认知用户数据的可靠性,对其置信指派函数进行折扣,加强高可靠性数据对融合结果的贡献,降低不可靠数据对融合结果的干扰,有效解决冲突数据下的协同频谱感知信息融合问题。仿真结果表明,证据折扣优化DSmT协同频谱感知器具有良好的检测性能和信噪比鲁棒性。

     

    Abstract: When cognitive radio system is under the deep shadowing and fading environment, cooperative spectrum sensing can improve the performance of spectrum sensing by fully using multiple cognitive radio user’s spatial diversity gain. The cooperative spectrum sensing can reduce the demand of single cognitive user’s sensitivity and decrease the system misjudgment resulted from the single detection uncertainty. Some studies show that cooperative spectrum sensing based on the D-S evidence theory has better SNR robustness and the detection performance than traditional sensing method, e.g. OR rule, AND rule and Optimal fusion rule. However, the conflicts information limits the performance of D-S method. In this paper, a novel scheme of cooperative spectrum sensing based on discounted DSmT was proposed to treat the conflicts information, which discounts the basic probability assignment of the terminals according to the credible degree of data from each local spectrum sensing terminal. Our method can add the fusing contribution of high reliability data, and reduce the interference of the low reliability data to the fusion results. Simulation results show that our method has the best detection performance than the traditional combination rule for cooperative spectrum sensing.

     

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