5th International Workshop on Spatial Stochastic Models for Wireless Networks

Research Article

A Fast Bayesian Model for Latent Radio Signal

  • @INPROCEEDINGS{10.1109/WIOPT.2009.5291568,
        author={Brett Houlding and Arnab Bhattacharya and Simon Wilson and Tim Forde},
        title={A Fast Bayesian Model for Latent Radio Signal},
        proceedings={5th International Workshop on Spatial Stochastic Models for Wireless Networks},
        publisher={IEEE},
        proceedings_a={SPASWIN},
        year={2009},
        month={10},
        keywords={Dynamic spectrum access latent radio signal Bayesian estimation integrated nested Laplace approximation},
        doi={10.1109/WIOPT.2009.5291568}
    }
    
  • Brett Houlding
    Arnab Bhattacharya
    Simon Wilson
    Tim Forde
    Year: 2009
    A Fast Bayesian Model for Latent Radio Signal
    SPASWIN
    IEEE
    DOI: 10.1109/WIOPT.2009.5291568
Brett Houlding1,*, Arnab Bhattacharya1,*, Simon Wilson1,*, Tim Forde1,*
  • 1: CTVR, Department of Statistics, Trinity College Dublin, Ireland
*Contact email: houldinb@tcd.ie, bhattaca@tcd.ie, swilson@tcd.ie, timforde@mee.tcd.ie

Abstract

This paper considers the use of a recently developed Bayesian statistical approximation technique that leads to very fast determination of highly accurate estimates for latent radio signal power. Following suitable data analysis, a first order non-stationary auto-regressive process is considered for latent radio signal and the fast approximation technique is then used to provide accurate estimates of the hidden model parameters. These estimates are based on having received several noisy, but spatially correlated, observations of the true latent signal. The implication of this technique for real time decision analysis and the problem of finding, and making use of, so-called radio spectrum holes is also discussed.