Enhanced Asynchronous Cooperative Spectrum Sensing Based on Dempster-Shafer Theory
Enhanced Asynchronous Cooperative Spectrum Sensing Based on Dempster-Shafer Theory
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DOI：
10.1109/glocom.2011.6134041
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发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
Jian Liu;Jing Li;Keping Long
中科院分区：
文献类型：
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作者：
Jian Liu;Jing Li;Keping Long
在认知无线电（CR）网络中，协作频谱感知可以极大地提高感知性能。然而，现有的几种协作频谱感知方法均存在时间异步假设，这不可避免地会带来等待时间的浪费，在实际应用中会造成诸多限制。在本文中，我们提出了一种基于 Dempster-Shafer (D-S) 理论的增强型异步协作频谱感知框架。在这样的框架内，每个SU采用双阈值频谱感知方法计算信任函数，提高了本地感知结果的可靠性。在融合中心（FC）中，采用滑动窗口方法保证融合数据的实时性和异步性。此外，为了减少FC中的数据融合量，我们提出了一种利用信任函数相关性的节点选择算法。我们的分析和仿真结果表明，该方法可以显着减少感知节点数量，显着提高频谱感知效率。
In cognitive radio (CR) networks, the cooperative spectrum sensing can greatly improve the sensing performance. However, several existing cooperative spectrum sensing methods have time asynchronization assumption, which will inevitably bring the waste of waiting time, and will cause many limitations in the practical application. In this paper, we propose an enhanced asynchronous cooperative spectrum sensing framework based on the Dempster-Shafer (D-S) theory. Within such a framework, each SU calculates the trust functions with the double threshold spectrum sensing method, which improves the reliability of the local sensing results. In fusion center (FC), it uses the sliding-window method to ensure the real- time performance and the asynchronism of the fusion data. In addition, to reduce the amount of data fusion in FC, we propose a node selection algorithm using the correlations of trust functions. Our analysis and simulation results show that this method can reduce the number of sensing nodes remarkably and improve the spectrum sensing efficiency significantly.