Research on cooperative spectrum sensing algorithm based on data fusion

Xinmiao Lu, Qiong Wu, Lei Wu
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引用次数: 4

Abstract

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.
基于数据融合的协同频谱感知算法研究
针对实际无线通信环境,不同位置的认知无线电频谱感知节点之间存在差异。本文研究了在不同接收信噪比条件下认知水平各节点频谱感知的优良检测性能。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,存在信噪比较低的认知融合节点汇合,反而会降低整体检测性能。为此,提出了基于混合数据融合的协同频谱感知算法,该算法基于不同信噪比对认知节点进行分类。根据不同类型的特征采取不同的数据融合准则。通过MATLAB在不同信道环境下的仿真,可以有效地提高整个系统的检测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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