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A New Method of Spectrum Sensing in Cognitive Radio Based on Statistical Covariance Matrix

机译:基于统计协方差矩阵的认知无线电频谱感应的一种新方法

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Spectrum sensing is a significant part of technique in a cognitive radio that detecting the presence of primary users in an authorized spectrum, the method that based on the statistical covariance matrix is one of main spectrum sensing techniques, using the difference of statistical covariance between the received signal and noise. In this paper, the new sensing method we proposed is also based on the statistical covariance. The new method compare to some traditional covariance algorithms has decrease the complexity of algorithm, at the same time, ensured the accuracy of detection. We give the statistics of detection, and we also find the threshold of the method when the probability of false alarm is given. The analysis and derivation process of threshold are provided in behind. Using Matlab for simulation to validate the correctness of the method and making the comparison with some typical detection method.
机译:频谱感测是在认知无线电中的技术中的重要部分,其在授权频谱中检测主要用户的存在,基于统计协方差矩阵的方法是主要频谱传感技术之一,使用所接收的统计协方差差异信号和噪声。在本文中,我们提出的新感测方法也基于统计协方差。与某些传统的协方差算法进行比较的新方法降低了算法的复杂性,同时确保了检测的准确性。我们给出了检测统计数据,我们还发现了误报的概率时找到方法的阈值。阈值的分析和推导过程在后面提供。使用MATLAB进行仿真以验证方法的正确性,并与一些典型检测方法进行比较。

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