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A Robust Secure Cooperative Spectrum Sensing Scheme Based on Evidence Theory and Robust Statistics in Cognitive Radio

机译:基于证据理论和鲁棒统计的鲁棒安全合作频谱感知方案

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摘要

Spectrum sensing is a key technology within Cognitive Radio (CR) systems. Cooperative spectrum sensing using a distributed model provides improved detection for the primary user, which opens the CR system to a new security threat. This threat is the decrease of the cooperative sensing performance due to the spectrum sensing data falsification which is generated from malicious users. Our proposed scheme, based on robust statistics, utilizes only available past sensing nodes' received power data for estimating the distribution parameters of the primary signal presence and absence hypotheses. These estimated parameters are used to perform the Dempster-Shafer theory of evidence data fusion which causes the elimination of malicious users. Furthermore, in order to enhance performance, a node's reliability weight is supplemented along with the data fusion scheme. Simulation results indicate that our proposed scheme can provide a powerful capability in eliminating malicious users as well as a high gain of data fusion under various cases of channel condition.
机译:频谱感测是认知无线电(CR)系统中的一项关键技术。使用分布式模型的协作频谱感测为主要用户提供了改进的检测,这使CR系统面临新的安全威胁。这种威胁是由于恶意用户产生的频谱感知数据伪造,导致协作感知性能下降。我们基于稳健统计量提出的方案仅利用可用的过去感测节点的接收功率数据来估计主要信号存在和不存在假设的分布参数。这些估计的参数用于执行证据数据融合的Dempster-Shafer理论,从而消除了恶意用户。此外,为了提高性能,节点的可靠性权重与数据融合方案一起得到了补充。仿真结果表明,在各种信道条件下,本文提出的方案均具有强大的消除恶意用户的能力以及较高的数据融合收益。

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