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Cluster mechanism for sensing data report using robust collaborative distributed spectrum sensing

机译:基于鲁棒协同分布式频谱感知的感知数据上报集群机制

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摘要

In cooperative mobile communications, spectrum sensing performance may encounter difficulties, which alert with many reporting errors, especially in dense network scenarios. In such networks, the decision fusion process for cooperating users becomes very complex, which requires sensing heavy traffic that needs a large bandwidth. To enhance the reliability of robust cooperative spectrum sensing, the paper proposed a new data fusion scheme based on clustering algorithm and distributed detection, in addition to an adapted threshold based on controlled false alarm probability. The proposed algorithm is dedicated to a highly Rayleigh faded environment to improves the channel errors. The results show that the use of two stages process of distribution clusters and selection fusion node (FN)s gives 0.42 error improvement. The results of the receiver operating characteristic (ROC) curve show an improvement in both false alarms and detection probabilities. Moreover, the sensitivity is also enhanced by 0.95.
机译:在协同移动通信中,频谱感知性能可能会遇到困难,这会导致许多报告错误,尤其是在密集网络场景中。在这样的网络中,合作用户的决策融合过程变得非常复杂,这需要感知需要大带宽的大量流量。为了提高鲁棒协同频谱感知的可靠性,除了基于受控虚警概率的自适应阈值外,该文还提出了一种基于聚类算法和分布式检测的数据融合方案。该算法专用于高度瑞利衰落的环境,以改善信道误差。结果表明,采用分布聚类和选择融合节点(FN)两阶段过程可使误差提高0.42;受试者工作特征(ROC)曲线的结果显示,误报率和检测概率都有所改善。此外,灵敏度也提高了 0.95。

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