Cognitive Radio-Oriented Wireless Networks. 14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11–12, 2019, Proceedings

Research Article

PoMeS: Profit-Maximizing Sensor Selection for Crowd-Sensed Spectrum Discovery

  • @INPROCEEDINGS{10.1007/978-3-030-25748-4_1,
        author={Suzan Bayhan and G\'{y}rkan G\'{y}r and Anatolij Zubow},
        title={PoMeS: Profit-Maximizing Sensor Selection for Crowd-Sensed Spectrum Discovery},
        proceedings={Cognitive Radio-Oriented Wireless Networks. 14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11--12, 2019, Proceedings},
        proceedings_a={CROWNCOM},
        year={2019},
        month={8},
        keywords={Spectrum discovery Crowdsensing Spectrum sensing},
        doi={10.1007/978-3-030-25748-4_1}
    }
    
  • Suzan Bayhan
    Gürkan Gür
    Anatolij Zubow
    Year: 2019
    PoMeS: Profit-Maximizing Sensor Selection for Crowd-Sensed Spectrum Discovery
    CROWNCOM
    Springer
    DOI: 10.1007/978-3-030-25748-4_1
Suzan Bayhan1,*, Gürkan Gür2,*, Anatolij Zubow1,*
  • 1: TU Berlin
  • 2: Zurich University of Applied Sciences (ZHAW)
*Contact email: suzan.bayhan@tu-berlin.de, gueu@zhaw.ch, anatolij.zubow@tu-berlin.de

Abstract

In a conventional network management setting, the mobile network operator (MNO) has to account for the traffic fluctuations in its service area and over-provision its network considering the peak traffic. However, this inefficient approach results in a very high cost for the MNO. Alternatively, the MNO can expand its capacity with secondary spectrum discovered opportunistically whenever, wherever needed. While outsourcing the spectrum discovery to a crowd of sensing units may be more advantageous compared to deploying sensing infrastructure itself, the MNO has to offer incentives in the form of payments to the units participating in the sensing campaign. A key challenge for this crowdsensing environment is to decide on how many sensing units to employ given a certain budget under some performance constraints. In this paper, we present a profit-maximizing sensor selection scheme for crowd-sensed spectrum discovery (PoMeS) for MNOs who want to take sensing as a service from the crowd of network elements and pay these sensors for their service. Compared to sensor selection considering the strict sensing accuracy required by the regulations, our heuristics show that an MNO can increase its profit by deciding itself the level of sensing accuracy based on its traffic in each cell site as well as the penalty it has to pay for not satisfying the required sensing accuracy.