University of Oulu

H. Hilleshein, H. M. Carlos de Lima, H. Alves and M. Latva-aho, "Iterative Bayesian-based Localization Mechanism for Industry Verticals," 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), Antwerp, Belgium, 2020, pp. 1-5, doi: 10.1109/VTC2020-Spring48590.2020.9128442

Iterative Bayesian-based localization mechanism for industry verticals

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Author: Hilleshein, Henrique1; de Lima, Carlos H. M.1; Alves, Hirley1;
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-08-12


We propose and evaluate an iterative localization mechanism employing Bayesian inference to estimate the position of a target using received signal strength measurements. The probability density functions of the target’s coordinates are estimated through a Bayesian network. Herein, we consider an iterative procedure whereby our predictor (posterior distribution) is updated in a sequential order whenever new measurements are made available. The performance of the mechanism is assessed in terms of the respective root mean square error and kernel density estimation of the target coordinates. Our numerical results showed the proposed iterative mechanism achieves increasingly better estimation of the target node position each updating round of the Bayesian network with new input measurements.

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Series: IEEE Vehicular Technology Conference
ISSN: 1090-3038
ISSN-L: 1090-3038
ISBN: 978-1-7281-5207-3
ISBN Print: 978-1-7281-4053-7
Pages: 1 - 5
Article number: 9128442
DOI: 10.1109/VTC2020-Spring48590.2020.9128442
Host publication: 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)
Conference: Vehicular Technology Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: The research leading to these results has received funding from the Academy of Finland through the projects 6Genesis Flagship (Grant No. 318927).
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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