8th International Conference on Cognitive Radio Oriented Wireless Networks

Research Article

Statistical Modeling Framework of Live Spectrum Observation data for Opportunistic Spectrum Sharing

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  • @INPROCEEDINGS{10.4108/icst.crowncom.2013.252080,
        author={Tanim Taher and Dennis Roberson and Kenneth Zdunek},
        title={Statistical Modeling Framework of Live Spectrum Observation data for Opportunistic Spectrum Sharing},
        proceedings={8th International Conference on Cognitive Radio Oriented Wireless Networks},
        publisher={ICST},
        proceedings_a={CROWNCOM},
        year={2013},
        month={11},
        keywords={statistical model cognitive radio dynamic spectrum access networks (dsa) voice traffic land mobile radio (lmr) public safety radio listen-before-talk (lbt) spectrum sharing spectrum observatory},
        doi={10.4108/icst.crowncom.2013.252080}
    }
    
  • Tanim Taher
    Dennis Roberson
    Kenneth Zdunek
    Year: 2013
    Statistical Modeling Framework of Live Spectrum Observation data for Opportunistic Spectrum Sharing
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2013.252080
Tanim Taher1,*, Dennis Roberson1, Kenneth Zdunek1
  • 1: Illinois Institute of Technology
*Contact email: tahetan@hawk.iit.edu

Abstract

A statistical model of land mobile radio (LMR) voice traffic is developed from empirical RF Spectrum measurement data. This model builds upon previous work, and is used to generate synthetic voice traffic that closely follows the daily and weekly patterns of the measured traffic. The model is applied to a Dynamic Spectrum Access (DSA) simulation. A coexistence algorithm that takes advantage of the modeled channel statistics is presented that allows an opportunistic secondary user (SU) to share a channel with a primary user (PU). The algorithm shows a clear improvement compared to the basic Listen-before-talk scheme that has no knowledge of a PU’s statistical traffic characteristics. Spectrum Opportunity Accessed and collision rate are used as metrics to compare the DSA coexistence techniques. We demonstrate the utility of a spectrum observatory system as being the integral part of this DSA framework, where the observatory continually monitors and models PU channel activity in order to provide the SU with useful statistical information about the PU’s traffic characteristics.