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Erschienen in:
2018 | OriginalPaper | Buchkapitel
A New Method of Spectrum Sensing in Cognitive Radio Based on Statistical Covariance Matrix
verfasst von : Zhaocong Sun, Xiaojun Jing, Jia Li
Erschienen in: Signal and Information Processing, Networking and Computers
Verlag: Springer Singapore
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Abstract
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.