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›› 2020, Vol. 37 ›› Issue (3): 379-386.DOI: 10.7523/j.issn.2095-6134.2020.03.011

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Cooperative spectrum sensing based on neural network in cognitive radio

XUE Jianwei1,2,3, TANG Liang1,2, BU Zhiyong1,2   

  1. 1. Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. School of Information Science & Technology, ShanghaiTech University, Shanghai 201210, China
  • Received:2018-08-30 Revised:2019-01-21 Online:2020-05-15

Abstract: Cognitive radio is a technology that can be used to effectively alleviate the current strain of spectrum resources, and spectrum sensing is the prerequisite of cognitive radio. To overcome the poor performance under the condition of low SNR, a cooperative spectrum sensing algorithm combining the high-order cumulants of signal and the eigenvalue of covariance matrix with the neural network is proposed. The algorithm takes into account the channel fading between the cognitive users and primary users and utilizes the strong multi-classification ability of neural networks. The ratio of maximum-minimum eigenvalues, the ratio of average-minimum eigenvalues, and high-order cumulants are used as the inputs of neural networks to realize the spectrum sensing. The simulation results show that the proposed algorithm not only has higher spectrum detection rate than other algorithms at low SNR, but also identifies the modulation type of the signal.

Key words: cognitive radio, spectrum sensing, neural network

CLC Number: