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Cooperative cognitive spectrum sensing using optimized DFT filter banks

机译:使用优化的DFT滤波器组进行合作认知频谱感知

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Spectrum sensing is used in cognitive radio to detect the free portions of spectrum in a licensed frequency band. In this paper, we consider a cooperative spectrum sensing scenario in which the decisions from the secondary users are combined for better sensing accuracy. Each secondary user sends its decision or data to a central node which combines all individual data or decisions. A DFT filter bank based architecture is used by each secondary user for efficient detection of a primary user signal in a desired time-frequency slot. The prototype filters underlying the DFT filter banks are optimized to provide maximum time-frequency resolution. The optimization is done using the concepts of time-frequency analysis and convex optimization. We formulate an objective function to represent the time-frequency distribution of signal energy and use numerical methods to obtain optimized prototypes. The simulation results show that the use of optimized DFT filter banks and cooperation between the sensing nodes give us better performance as compared to other sensing techniques.
机译:频谱感测用于认知无线电中,以检测许可频段中频谱的自由部分。在本文中,我们考虑了一种协作频谱感知方案,其中结合了次要用户的决策以提高感知精度。每个辅助用户将其决策或数据发送到中央节点,该中央节点将所有单独的数据或决策组合在一起。每个次要用户都使用基于DFT滤波器组的体系结构来有效检测所需时频时隙中的主要用户信号。 DFT滤波器组下面的原型滤波器经过优化,以提供最大的时频分辨率。使用时频分析和凸优化的概念来完成优化。我们制定了一个目标函数来表示信号能量的时频分布,并使用数值方法来获得优化的原型。仿真结果表明,与其他传感技术相比,使用优化的DFT滤波器组以及传感节点之间的协作可为我们提供更好的性能。

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