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Knowledge based cooperative spectrum sensing using polynomial classifiers in cognitive radio networks

  • American University of Sharjah

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

2 Scopus citations

Abstract

This paper proposes a cooperative spectrum sensing scheme for cognitive radio networks using a polynomial classifier. The proposed scheme utilizes either coherent or cyclostationary features in the received signal at each node and the extracted features are used by a central node to make to a global decision about the availability of spectrum holes for use by the cognitive radio network. The paper presents a system model and simulation results for the detection probability of spectrum holes under fading channel conditions. The system is optimized to maximize the detection probability while keeping the false alarm at a fixed rate leading to improved spectrum utilization by the cognitive network while minimizing the interference to primary users.

Original languageEnglish
Title of host publication4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings
DOIs
StatePublished - 2010
Externally publishedYes
Event4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Gold Coast, QLD, Australia
Duration: 13 Dec 201015 Dec 2010

Publication series

Name4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings

Conference

Conference4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010
Country/TerritoryAustralia
CityGold Coast, QLD
Period13/12/1015/12/10

Keywords

  • Classifiers
  • Cognitive radio
  • Coherent
  • Cyclostationary

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