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Research on cooperative spectrum sensing algorithm based on data fusion

机译:基于数据融合的协作频谱感知算法研究

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In view of the actual wireless communication environment, there exists the difference between different location of the cognitive radio spectrum sensing node. This paper studies excellent detection performance of each node spectrum sensing of cognitive level in different conditions of received signal to noise ratio. The data fusion criteria which cognitive user adopt under different SNR could take directly affects the overall cooperative spectrum sensing detection performance, and there have cognitive fusion nodes with lower SNR to be in confluence, on the contrary it will reduce the overall detection performance. Therefore the hybrid data fusion based cooperative spectrum sensing algorithm is proposed, the method based on different SNR classifies cognitive nodes. The different criteria for data fusion is taken according to each type of the characteristics. It can be proved to improve the detection performance of the whole system effectively through MATLAB simulation in different channel environments.
机译:鉴于实际的无线通信环境,认知无线电频谱感测节点的不同位置之间存在差异。本文研究了在不同接收信号信噪比条件下认知水平的每个节点频谱感知的出色检测性能。认知用户在不同信噪比下采用的数据融合准则会直接影响整体协同频谱感知检测性能,并且存在具有较低信噪比的认知融合节点融合,反而会降低整体检测性能。为此,提出了一种基于混合数据融合的协作频谱感知算法,该算法基于不同的信噪比对认知节点进行分类。根据每种类型的特征采用不同的数据融合标准。通过在不同通道环境下的MATLAB仿真,可以有效地提高整个系统的检测性能。

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