Mobility tracking in cellular networks with sequential Monte Carlo filters

LS Mihaylova; DR Bull; D Angelova; CN Canagarajah

doi:10.1109/ICIF.2005.1591843

Mobility tracking in cellular networks with sequential Monte Carlo filters

LS Mihaylova, DR Bull, D Angelova, CN Canagarajah

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

5 Citations (Scopus)

415 Downloads (Pure)

Abstract

This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector. The command is modeled as a first-order Markov process which can take values from a finite set of acceleration levels, in order to cover the wide range of acceleration changes, a set of acceleration values is pre-determined. Sequential Monte Carlo algorithms-a particle filter (PF) and a Rao-Blackwellised particle filter (RBPF) is proposed and their performance evaluated over a synthetic data example.

Translated title of the contribution	Mobility tracking in cellular networks with sequential Monte Carlo filters
Original language	English
Title of host publication	2005 7th International Conference on Information Fusion (FUSION) Philadelphia, PA, United States
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	107 - 114
Number of pages	8
Volume	1
ISBN (Print)	0780392868
DOIs	https://doi.org/10.1109/ICIF.2005.1591843
Publication status	Published - Jul 2005
Event	8th International Conference on Information Fusion - Philadelphia, PA, United States Duration: 1 Jul 2005 → …

Conference

Conference	8th International Conference on Information Fusion
Country/Territory	United States
City	Philadelphia, PA
Period	1/07/05 → …

Bibliographical note

Rose publication type: Conference contribution

Sponsorship: This research is supported by the the UK MOD Data and Information
Fusion Defence Technology Center and in part by the
Bulgarian Foundation for Scientific Investigations under grants I-
1202/02 and 1-1205/02.

Terms of use: Copyright © 2005 IEEE. Reprinted from 8th International Conference on Information Fusion, 2005.

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 the University of Bristol'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

mobility tracking
Monte Carlo methods
wireless networks
hybrid systems
Rao-Blackwellisation
Singer model

Access to Document

10.1109/ICIF.2005.1591843

Mihaylova IEEE infofusion 2005Accepted author manuscript, 1.7 MB

http://hdl.handle.net/1983/1395

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Cite this

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title = "Mobility tracking in cellular networks with sequential Monte Carlo filters",

abstract = "This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector. The command is modeled as a first-order Markov process which can take values from a finite set of acceleration levels, in order to cover the wide range of acceleration changes, a set of acceleration values is pre-determined. Sequential Monte Carlo algorithms-a particle filter (PF) and a Rao-Blackwellised particle filter (RBPF) is proposed and their performance evaluated over a synthetic data example.",

keywords = "mobility tracking, Monte Carlo methods, wireless networks, hybrid systems, Rao-Blackwellisation, Singer model",

author = "LS Mihaylova and DR Bull and D Angelova and CN Canagarajah",

note = "Rose publication type: Conference contribution Sponsorship: This research is supported by the the UK MOD Data and Information Fusion Defence Technology Center and in part by the Bulgarian Foundation for Scientific Investigations under grants I- 1202/02 and 1-1205/02. Terms of use: Copyright {\textcopyright} 2005 IEEE. Reprinted from 8th International Conference on Information Fusion, 2005. 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 the University of Bristol'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. ; 8th International Conference on Information Fusion ; Conference date: 01-07-2005",

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language = "English",

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booktitle = "2005 7th International Conference on Information Fusion (FUSION) Philadelphia, PA, United States",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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}

Mihaylova, LS, Bull, DR, Angelova, D & Canagarajah, CN 2005, Mobility tracking in cellular networks with sequential Monte Carlo filters. in 2005 7th International Conference on Information Fusion (FUSION) Philadelphia, PA, United States. vol. 1, Institute of Electrical and Electronics Engineers (IEEE), pp. 107 - 114, 8th International Conference on Information Fusion, Philadelphia, PA, United States, 1/07/05. https://doi.org/10.1109/ICIF.2005.1591843

Mobility tracking in cellular networks with sequential Monte Carlo filters. / Mihaylova, LS; Bull, DR; Angelova, D et al.
2005 7th International Conference on Information Fusion (FUSION) Philadelphia, PA, United States. Vol. 1 Institute of Electrical and Electronics Engineers (IEEE), 2005. p. 107 - 114.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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N1 - Rose publication type: Conference contribution Sponsorship: This research is supported by the the UK MOD Data and Information Fusion Defence Technology Center and in part by the Bulgarian Foundation for Scientific Investigations under grants I- 1202/02 and 1-1205/02. Terms of use: Copyright © 2005 IEEE. Reprinted from 8th International Conference on Information Fusion, 2005. 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 the University of Bristol'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 - 2005/7

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N2 - This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector. The command is modeled as a first-order Markov process which can take values from a finite set of acceleration levels, in order to cover the wide range of acceleration changes, a set of acceleration values is pre-determined. Sequential Monte Carlo algorithms-a particle filter (PF) and a Rao-Blackwellised particle filter (RBPF) is proposed and their performance evaluated over a synthetic data example.

AB - This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector. The command is modeled as a first-order Markov process which can take values from a finite set of acceleration levels, in order to cover the wide range of acceleration changes, a set of acceleration values is pre-determined. Sequential Monte Carlo algorithms-a particle filter (PF) and a Rao-Blackwellised particle filter (RBPF) is proposed and their performance evaluated over a synthetic data example.

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KW - Rao-Blackwellisation

KW - Singer model

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SP - 107

EP - 114

BT - 2005 7th International Conference on Information Fusion (FUSION) Philadelphia, PA, United States

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 8th International Conference on Information Fusion

Y2 - 1 July 2005

ER -

Mobility tracking in cellular networks with sequential Monte Carlo filters

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Bibliographical note

Keywords

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