9th International Conference on Cognitive Radio Oriented Wireless Networks

Research Article

Reconfigurable Antenna Based DoA Estimation and Localization in Cognitive Radios: Low Complexity Algorithms and Practical Measurements

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  • @INPROCEEDINGS{10.4108/icst.crowncom.2014.255730,
        author={Aki Hakkarainen and Janis Werner and Nikhil Gulati and Damiano Patron and Doug Pfeil and Henna Paaso and Aarne Mammela and Kapil Dandekar and Mikko Valkama},
        title={Reconfigurable Antenna Based DoA Estimation and Localization in Cognitive Radios: Low Complexity Algorithms and Practical Measurements},
        proceedings={9th International Conference on Cognitive Radio Oriented Wireless Networks},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2014},
        month={7},
        keywords={cognitive radio direction-of-arrival estimation leaky-wave antennas localization low complexity measurements reconfigurable antennas stansfield algorithm},
        doi={10.4108/icst.crowncom.2014.255730}
    }
    
  • Aki Hakkarainen
    Janis Werner
    Nikhil Gulati
    Damiano Patron
    Doug Pfeil
    Henna Paaso
    Aarne Mammela
    Kapil Dandekar
    Mikko Valkama
    Year: 2014
    Reconfigurable Antenna Based DoA Estimation and Localization in Cognitive Radios: Low Complexity Algorithms and Practical Measurements
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2014.255730
Aki Hakkarainen1,*, Janis Werner1, Nikhil Gulati2, Damiano Patron2, Doug Pfeil2, Henna Paaso3, Aarne Mammela3, Kapil Dandekar2, Mikko Valkama1
  • 1: Tampere University of Technology
  • 2: Drexel University
  • 3: VTT Technical Research Centre of Finland
*Contact email: aki.hakkarainen@tut.fi

Abstract

This paper addresses low-complexity algorithms and evaluates the practical performance of low-complexity primary user (PU) direction of arrival (DoA) estimation and PU localization with real world indoor measurement data. More specifically, we use a type of reconfigurable antenna known as leaky-wave antennas to sense the spatial distribution of the PU signal power. By deploying a very low-complexity algorithm, called MaxE, the secondary user (SU) sensors are then able to estimate their respective PU DoAs. Finally, a central fusion center combines the DoAs into a PU location estimate. The results of the practical measurements reveal that it is possible to implement a localization system with very low complexity and fairly good PU location capabilities in a cognitive radio network. Such PU localization capabilities can then be used, e.g. for enhanced PU interference management.