1st International ICST Workshop on Cognitive Wireless Networks

Research Article

HOS-based mode classification for infomobility framework

  • @INPROCEEDINGS{10.1145/1577382.1577388,
        author={Andrea F. Cattoni and Marina Ottonello and Mirco Raffetto and Carlo S. Regazzoni},
        title={HOS-based mode classification for infomobility framework},
        proceedings={1st International ICST Workshop on Cognitive Wireless Networks},
        publisher={ACM},
        proceedings_a={CWNETS},
        year={2007},
        month={8},
        keywords={Cognitive Radio SVM Mode Identification},
        doi={10.1145/1577382.1577388}
    }
    
  • Andrea F. Cattoni
    Marina Ottonello
    Mirco Raffetto
    Carlo S. Regazzoni
    Year: 2007
    HOS-based mode classification for infomobility framework
    CWNETS
    ACM
    DOI: 10.1145/1577382.1577388
Andrea F. Cattoni1,*, Marina Ottonello1,*, Mirco Raffetto1,*, Carlo S. Regazzoni1,*
  • 1: Department of Biophysical and Electronic Engineering - DIBE University of Genova via Opera Pia 11A I-16145, Genova, Italy
*Contact email: cattoni@dibe.unige.it, ottonello@dibe.unige.it, raffetto@dibe.unige.it, carlo@dibe.unige.it

Abstract

The growing number of new emerging wireless standards is creating regulatory problems in allocating the unlicensed frequencies. A possible solution for increasing the frequency reusage within the framework of info-mobility cellular systems is the joint exploitation of Smart Antennas and Cognitive Radio. Inside this framework a key-role is played by Mode Identification and Spectrum monitoring algorithms, useful to provide awareness about the channel conditions. In the paper a Mode Identification algorithm, based on the extraction of higher order statistics from frequency distribution of the involved communication modalities and multiple support vector machine classifiers, for a Cognitive Base Transceiver Station is presented. Simulated results, obtained in a simplified framework, will prove the effectiveness of the proposed approach.