Efficient detection of primary users in cognitive radio Networks

Xuetao Chen, Tamal Bose, S. M. Hasan, Jeffrey H. Reed

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper proposes an approach to detect the primary user during the communication of the secondary users, using the concept of interference detection in the presence of a desired signal. The detection problem is first formulated as a multi-class classification problem. The pattern with medium bit error rate (BER) and low interference to signal power ratio (ISR) is identified as the most difficult case. A classifier based on a support vector machine (SVM) is proposed to solve this problem. Simulation results yield 76% classification accuracy with ISR larger than -10 dB and a heterogenous channel condition between the primary link and secondary link. Both the channel vacation time and the usage of idle time can be reduced by the proposed approach.

Original languageEnglish (US)
Pages (from-to)267-285
Number of pages19
JournalInternational Journal of Communication Networks and Distributed Systems
Volume8
Issue number3-4
DOIs
StatePublished - Apr 2012
Externally publishedYes

Fingerprint

Cognitive radio
Bit error rate
Support vector machines
Classifiers
Communication

Keywords

  • Channel vacation time
  • DSA
  • Dynamic spectrum access
  • Interference measurement
  • Support vector machine
  • SVM

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Efficient detection of primary users in cognitive radio Networks. / Chen, Xuetao; Bose, Tamal; Hasan, S. M.; Reed, Jeffrey H.

In: International Journal of Communication Networks and Distributed Systems, Vol. 8, No. 3-4, 04.2012, p. 267-285.

Research output: Contribution to journalArticle

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