5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Fuzzy logic based signal classification with cognitive radios for standard wireless technologies

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  • @INPROCEEDINGS{10.4108/ICST.CROWNCOM2010.9239,
        author={Kaleem Ahmad and Uwe Meier and Halina Kwasnicka},
        title={Fuzzy logic based signal classification with cognitive radios for standard wireless technologies},
        proceedings={5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2010},
        month={9},
        keywords={Frequency measurement Frequency shift keying Object recognition Power measurement Wireless LAN},
        doi={10.4108/ICST.CROWNCOM2010.9239}
    }
    
  • Kaleem Ahmad
    Uwe Meier
    Halina Kwasnicka
    Year: 2010
    Fuzzy logic based signal classification with cognitive radios for standard wireless technologies
    CROWNCOM
    IEEE
    DOI: 10.4108/ICST.CROWNCOM2010.9239
Kaleem Ahmad1,*, Uwe Meier1,*, Halina Kwasnicka2,*
  • 1: Institute Industrial IT, OWL University of Applied Sciences, 32657 Lemgo, Germany
  • 2: Wrocław University of Technology, 50-370 Wrocław, Poland
*Contact email: kaleem.ahmad@hs-owl.de, uwe.meier@hs-owl.de, halina.kwasnicka@pwr.wroc.pl

Abstract

Cognitive radio (CR) is being considered as a promising technology to improve the spectral usage and coexistence behavior of radio systems. The CR can work as a secondary user (SU) in coexistence with primary user (PU) systems without generating harmful interference for them. However, the performance of a SU greatly depends on its abilities to become aware of its radio environment. The more knowledge a CR can acquire from PU systems, the better it will be equipped to optimize its performance in a coexistence environment. Ideally, it would like to classify the PU systems with respect to existing `known standards'. Research has been done in the area of signal classification with respect to modulations. We present a novel approach based on fuzzy logic (FL) to classify signals with respect to standards on the basis of known radio parameters.