On the use of blind source separation for peak detection in spectrum sensing

Zahid Saleem*, Samir Al-Ghadhban, Tareq Al-Naffouri

*Corresponding author for this work

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

4 Scopus citations

Abstract

Applying wavelet edge detection technique on observed wideband spectrum, results in a signal which contains frequency band boundaries information. Resultant signal contains peaks at locations corresponding to frequency band boundaries i.e. start and end locations of frequency bands. In the presence of noise resultant signal contains mixture of true peaks and noisy peaks. A threshold value is required to extract true peaks efficiently from mixture. In this paper calculation of threshold value is performed using blind source separation technique. Probability of detection and success ratio plots are used to evaluate proposed technique. Success ratio plot shows improvement of 4 dB and probability of detection plot shows improvement of 8 dB. Moreover, the proposed algorithm is based on the received signal and does not require any apriori information.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012
Pages66-71
Number of pages6
DOIs
StatePublished - Apr 15 2013
Event2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012 - Penang, Malaysia
Duration: Nov 23 2012Nov 25 2012

Publication series

NameProceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012

Other

Other2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012
CountryMalaysia
CityPenang
Period11/23/1211/25/12

Keywords

  • Blind Source Separation
  • Cognitive Radio
  • Edge Detection

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Control and Systems Engineering

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