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Low-SNR Energy Detection Based on Relevance in Power Density Spectrum

机译:基于功率密度谱相关性的低信噪比能量检测

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Energy detection is the most commonly used spectrum sensing method in cognitive radio because of its simplicity and there is no need for priori information. However, the performance of energy detection will seriously deteriorate under low-SNR condition. Various improved methods have been proposed to solve this problem, but at the expense of high complexity. This paper introduces an energy detection method based on the relevance in power density spectrum. It uses an iterative method to precisely estimate the noise power without any priori information and makes use of the relevance between occupied frequency points to detect low-SNR signals effectively. Simulation results show that the proposed method has better performance and lower complexity than traditional methods.
机译:能量检测是认知无线电中最常用的频谱感测方法,因为它简单易用,不需要先验信息。但是,在低信噪比条件下,能量检测的性能将严重下降。已经提出了各种改进的方法来解决该问题,但是以高复杂度为代价。介绍了一种基于功率密度谱相关性的能量检测方法。它使用一种迭代方法来精确估计噪声功率,而无需任何先验信息,并利用占用的频率点之间的相关性来有效地检测低SNR信号。仿真结果表明,与传统方法相比,该方法具有更好的性能和更低的复杂度。

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