Non-asymptotic analysis of scaled largest eigenvalue based spectrum sensing

Lu Wei*

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

In this paper, we analyze the non-asymptotic performance of scaled largest eigenvalue based detection, which is an optimal detector in the presence of a single primary user. Exact distributions of the test statistics have been derived, which lead to finite-dimensional characterizations of the false alarm probability. These results are obtained by taking advantage of the properties of the Mellin transform for products of independent random variables. Simulations are provided to verify the derived results, and to compare with the asymptotic result in literature.

Original languageEnglish
Title of host publication4th International Congress on Ultra Modern Telecommunications and Control Systems 2012, ICUMT 2012
Pages955-958
Number of pages4
DOIs
Publication statusPublished - 2012
MoE publication typeA4 Article in a conference publication
EventInternational Congress on Ultra Modern Telecommunications and Control Systems - St. Petersburg, Russian Federation
Duration: 3 Oct 20125 Oct 2012
Conference number: 4

Conference

ConferenceInternational Congress on Ultra Modern Telecommunications and Control Systems
Abbreviated titleICUMT
CountryRussian Federation
CitySt. Petersburg
Period03/10/201205/10/2012

Keywords

  • Cognitive radio
  • multi-antenna spectrum sensing
  • multivariate analysis
  • the Mellin transform

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