Bayesian tracking in cooperative localization for cognitive radio networks

Sithamparanathan Kandeepan; Sam Reisenfeld; Tuncer Can Aysal; David Lowe; Radoslaw Piesiewicz

doi:10.1109/VETECS.2009.5073417

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 proceeding › Conference proceeding contribution › peer-review

27 Citations (Scopus)

66 Downloads (Pure)

Abstract

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 language	English
Title of host publication	IEEE 69th Vehicular Technology Conference, VTC Spring 2009
Editors	J. Nasreddine, J. Perez-Romero, J. Sallent
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1-5
Number of pages	5
ISBN (Print)	9781424425174
DOIs	https://doi.org/10.1109/VETECS.2009.5073417
Publication status	Published - 2009
Externally published	Yes
Event	VTC Spring 2009 - IEEE 69th Vehicular Technology Conference - Barcelona, Spain Duration: 26 Apr 2009 → 29 Apr 2009

Other

Other	VTC Spring 2009 - IEEE 69th Vehicular Technology Conference
Country/Territory	Spain
City	Barcelona
Period	26/04/09 → 29/04/09

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 Universityâ€™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 [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Keywords

Bayesian phase tracking
Cognitive radios
Cooperative localization and tracking
Particle filter

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10.1109/VETECS.2009.5073417

Publisher version (open access).pdfFinal published version, 223 KB

Cite this

Kandeepan, S., Reisenfeld, S., Aysal, T. C., Lowe, D., & Piesiewicz, R. (2009). Bayesian tracking in cooperative localization for cognitive radio networks. In J. Nasreddine, J. Perez-Romero, & J. Sallent (Eds.), IEEE 69th Vehicular Technology Conference, VTC Spring 2009 (pp. 1-5). Article 5073417 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/VETECS.2009.5073417

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abstract = "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.",

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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{\^a}€{\texttrademark}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 [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.; VTC Spring 2009 - IEEE 69th Vehicular Technology Conference ; Conference date: 26-04-2009 Through 29-04-2009",

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Kandeepan, S, Reisenfeld, S, Aysal, TC, Lowe, D & Piesiewicz, R 2009, Bayesian tracking in cooperative localization for cognitive radio networks. in J Nasreddine, J Perez-Romero & J Sallent (eds), IEEE 69th Vehicular Technology Conference, VTC Spring 2009., 5073417, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 1-5, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference, Barcelona, Spain, 26/04/09. https://doi.org/10.1109/VETECS.2009.5073417

Bayesian tracking in cooperative localization for cognitive radio networks. / Kandeepan, Sithamparanathan; Reisenfeld, Sam; Aysal, Tuncer Can et al.
IEEE 69th Vehicular Technology Conference, VTC Spring 2009. ed. / J. Nasreddine; J. Perez-Romero; J. Sallent. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2009. p. 1-5 5073417.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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T1 - Bayesian tracking in cooperative localization for cognitive radio networks

AU - Kandeepan, Sithamparanathan

AU - Reisenfeld, Sam

AU - Aysal, Tuncer Can

AU - Lowe, David

AU - Piesiewicz, Radoslaw

N1 - 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 Universityâ€™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 [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

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SN - 9781424425174

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EP - 5

BT - IEEE 69th Vehicular Technology Conference, VTC Spring 2009

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CY - Piscataway, NJ

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ER -

Kandeepan S, Reisenfeld S, Aysal TC, Lowe D, Piesiewicz R. Bayesian tracking in cooperative localization for cognitive radio networks. In Nasreddine J, Perez-Romero J, Sallent J, editors, IEEE 69th Vehicular Technology Conference, VTC Spring 2009. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2009. p. 1-5. 5073417 doi: 10.1109/VETECS.2009.5073417

Bayesian tracking in cooperative localization for cognitive radio networks

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