Journal of Jishou University(Natural Sciences Edition)

• Information and communication • Previous Articles     Next Articles

An Improved Blind Spectrum Sensing Algorithm Based on the Ratio of Eigenvalues of the Sample Covariance Matrix

WANG Hanrui,HUANG Xiaoyu,JIANG Wei,ZHAI Fengyun,LEI Kejun   

  1. (College of Information Science and Engineering,Jishou University,Jishou 416000,Hunan China)
  • Online:2017-11-25 Published:2017-12-29
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (No.61362018),the key projects of Hunan Provincial Department of Education (No.16A174),the Jishou University Doctoral Talent Introduction Project,and the project for Inquiry Learning and Innovative Experiment for College Students of Hunan Province (2016[283])


The blind spectrum sensing algorithm based on the ratio of the maximum and minimum eigenvalues (MME) has attracted much attention in cognitive radio (CR).One of the main advantages of this method is that no prior information of the wireless channel,the noise variance and the primary signal pattern is needed in the process of spectrum sensing.However,the determination of the corresponding decision threshold for MME method is still a difficult problem in practical applications.In this paper,a new MME method based on the improved decision threshold has been proposed.The proposed MME algorithm can obtain more reliable detection performance than the original algorithms.Simulation results verify the effectiveness of the proposed MME method.

Key words: Cognitive radio, blind spectrum sensing, the ratio of the maximum and minimum eigenvalues (MME), the sample covariance matrix (SCM), random matrix theory (RMT)

WeChat e-book chaoxing Mobile QQ