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Mean spectral radius detection for cognitive radio

  • Harbin Institute of Technology

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

Abstract

In this paper, a new spectrum sensing algorithm is proposed based on the eigenvalue distribution of the covariance matrix of sensing nodes. The received signals of all the nodes can be denoted by a non-Hermitian random matrix. A recent research indicates that the eigenvalue distribution for the product of non-Hermitian random matrices follows Single Ring Theorem for the noise-only case. However, for the signal-present case, the inner radius of the eigenvalue distribution is smaller than that of the noise-only case. Then mean spectral radius (MSR) can be utilized to detect the signal. The proposed method overcomes the noise uncertainty and has higher detection performance than the maximum-minimum eigenvalue (MME) detection when the primary signals among sensing nodes are uncorrelated. Finally, Simulations are performed to verify the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509017010
DOIs
StatePublished - 2 Jul 2016
Event84th IEEE Vehicular Technology Conference, VTC Fall 2016 - Montreal, Canada
Duration: 18 Sep 201621 Sep 2016

Publication series

NameIEEE Vehicular Technology Conference
Volume0
ISSN (Print)1550-2252

Conference

Conference84th IEEE Vehicular Technology Conference, VTC Fall 2016
Country/TerritoryCanada
CityMontreal
Period18/09/1621/09/16

Keywords

  • Mean spectral radius
  • Non-hermitian random matrix
  • Single Ring Theorem
  • Spectrum sensing
  • The eigenvalue distribution

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