一种信任度模糊分配的合作频谱感知算法

A Cooperative Spectrum Sensing Algorithm Based on Fuzzy Credibility

  • 摘要: 由于无线信道的多径衰落和阴影效应等因素,单个认知用户无法区分频段空闲还是授权用户的信号处于深度衰落中。合作频谱感知运用信息融合技术,通过融合多个认知用户的结果来提高频谱感知的性能。证据理论作为一种有效的不确定性推理方法,在合作频谱感知中已有较好的应用。本文将模糊集与证据理论相结合,提出一种信任度模糊分配的合作频谱感知的算法。各个认知用户首先进行本地能量检测,然后使用正态形隶属函数进行基本概率赋值,根据认知用户的检测结果分配信任度。融合中心接收所有认知用户的证据,按照Dempster组合规则进行融合,最后进行判决。仿真结果表明,信任度模糊分配的合作频谱感知算法在感知性能上或者在算法复杂度上要优于现有的证据理论合作频谱感知算法。

     

    Abstract: Due to multipath fading and shadow effect etc factors, single cognitive user can’t distinguish between the unused bands and license user’s signal in deep fade. Cooperative spectrum sensing uses information fusion technology to improve spectrum sensing performance by combining multi-cognitive users sensing results. Theory of evidence is an effective way of uncertainty reasoning, which has been used in cooperative spectrum sensing well. In this paper it integrates fuzzy set with theory of evidence and puts forward a cooperative spectrum sensing algorithm based on fuzzy credibility. Each cognitive user first makes local energy detection. Then it uses normal-shaped membership function as basic probability assignment which assigns credibility by cognitive user’s detection result. The fusion center receives all cognitive users’ evidence and combines them by Dempster rule. At last the fusion center draws a conclusion. As simulation results shown, the cooperative spectrum sensing algorithm based on fuzzy credibility has a better sensing performance or algorithm complexity than existing cooperative spectrum sensing algorithm based on theory of evidence.

     

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