Maximum eigenvalue and energy combined spectrum sensing algorithm

Wenjing Zhao, He Li, Minglu Jin, Sang Jo Yoo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Energy detection (ED) method for spectrum sensing does not require any information of the source signal and channel, as well as it is suitable for detecting independent identically distributed signals. Covariance matrix catches the signal correlations and the maximum eigenvalue detection (MED) method is better than the ED for correlated signals. In this paper, taking the advantages of the two algorithms, a combined method of the maximum eigenvalue and energy of the signal is proposed to achieve detection performance improvements. The proposed method is a generalization of the ED and MED methods, which takes the ED and MED algorithms as special cases. The theoretical analysis on detection probability, false alarm probability and threshold are given, and the optimum parameter selection of the proposed method is discussed. Finally, simulation results show the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publication2019 International Conference on Engineering and Telecommunication, EnT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728135649
DOIs
StatePublished - Nov 2019
Event2019 International Conference on Engineering and Telecommunication, EnT 2019 - Dolgoprudny, Russian Federation
Duration: 20 Nov 201921 Nov 2019

Publication series

Name2019 International Conference on Engineering and Telecommunication, EnT 2019

Conference

Conference2019 International Conference on Engineering and Telecommunication, EnT 2019
Country/TerritoryRussian Federation
CityDolgoprudny
Period20/11/1921/11/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Cognitive radio network
  • Energy
  • Maximum eigenvalue
  • Random matrix theory
  • Spectrum sensing

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