Cognitive Radio Oriented Wireless Networks. 12th International Conference, CROWNCOM 2017, Lisbon, Portugal, September 20-21, 2017, Proceedings

Research Article

Autonomous Spectrum Assignment of White Space Devices

Download
174 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-76207-4_4,
        author={Chaitali Diwan and Srinath Srinivasa and Bala Krishna},
        title={Autonomous Spectrum Assignment of White Space Devices},
        proceedings={Cognitive Radio Oriented Wireless Networks. 12th International Conference, CROWNCOM 2017, Lisbon, Portugal, September 20-21, 2017, Proceedings},
        proceedings_a={CROWNCOM},
        year={2018},
        month={3},
        keywords={White spaces Dynamic spectrum access Multi-agent systems Evolutionary game theory White space database Optimising spectrum utilisation},
        doi={10.1007/978-3-319-76207-4_4}
    }
    
  • Chaitali Diwan
    Srinath Srinivasa
    Bala Krishna
    Year: 2018
    Autonomous Spectrum Assignment of White Space Devices
    CROWNCOM
    Springer
    DOI: 10.1007/978-3-319-76207-4_4
Chaitali Diwan1,*, Srinath Srinivasa1,*, Bala Krishna1,*
  • 1: International Institute of Information Technology
*Contact email: chaitali.diwan@iiitb.org, sri@iiitb.ac.in, balamurali.krishna@iiitb.org

Abstract

White-space spectrum has temporal and spatial variations, and fragmentation, making the spectrum assignment for devices in this space challenging. In this paper, we propose an autonomous agent model for spectrum assignment of white space devices at a given location. Each white space device (WSD) acts autonomously out of self-interest, choosing a strategy from its bag of strategies. It obtains a payoff based on its choice and choices made by all other WSDs. Based on the payoffs received by different strategies, WSDs evolve their strategic profile over time. This has the effect of demographic changes in the population which is published as demographic profile by the Master. WSDs are expected to choose a strategy with a probability distribution based on this, for optimising network utilisation. In evaluation runs, network utilisation levels in such an approach are found to be high, and approaching optimal values computed in a centralised fashion.