Bayesian tracking in cooperative localization for cognitive radio networks

Sithamparanathan Kandeepan*, Sam Reisenfeld, Tuncer Can Aysal, David Lowe, Radoslaw Piesiewicz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

27 Citations (Scopus)
39 Downloads (Pure)


In this paper we consider cooperative localization and tracking of primary users (PU) in a cognitive radio network using Bayesian techniques. We use particle filtering methods to track the location of a PU in the network using cooperative localization techniques and present some results for noisy measurements. The cognitive radio (CR) nodes estimate the information related to the geographical position of the PU based on existing location identification and localization techniques and forward the noisy information to a cognitive radio base station (CRB), which then fuses the information to estimate the position of the PU in the network in order to perform a radio scene analysis. We propose a particle filtering approach that is suitable for tracking Gaussian and non-Gaussian noisy signals at the CRB to estimate the position of a PU, two importance-functions relative to the particle filtering algorithm are also presented. Simulations are performed on the proposed tracking algorithm and the results are presented in terms of the mean squared error of the positional estimates.

Original languageEnglish
Title of host publicationIEEE 69th Vehicular Technology Conference, VTC Spring 2009
EditorsJ. Nasreddine, J. Perez-Romero, J. Sallent
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Print)9781424425174
Publication statusPublished - 2009
Externally publishedYes
EventVTC Spring 2009 - IEEE 69th Vehicular Technology Conference - Barcelona, Spain
Duration: 26 Apr 200929 Apr 2009


OtherVTC Spring 2009 - IEEE 69th Vehicular Technology Conference

Bibliographical note

Copyright 2009 IEEE. Reprinted from Advanced spectrum management for the downlink of WCDMA systems using genetic algorithms : IEEE Vehicular Technology Conference 2009. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.


  • Bayesian phase tracking
  • Cognitive radios
  • Cooperative localization and tracking
  • Particle filter


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