eprintid: 11637
rev_number: 24
eprint_status: archive
userid: 1903
dir: disk0/00/01/16/37
datestamp: 2012-12-05 11:48:42
lastmod: 2023-03-21 17:35:14
status_changed: 2023-03-21 17:35:14
type: conference_item
metadata_visibility: show
item_issues_count: 0
creators_name: Tarrío Alonso, Paula
creators_name: Bernardos Barbolla, Ana M.
creators_name: Xian, Wan
creators_name: Casar Corredera, José Ramón
title: Dynamic chanel model LMS updating for RSS-based localization
ispublished: pub
subjects: telecomunicaciones
keywords: Indoor localization, RSS, calibration, channel model, LMS
abstract: Received signal strength-based localization systems usually rely on a calibration process that aims at characterizing the propagation channel. However, due to the changing environmental dynamics, the behavior of the channel may change after some time, thus, recalibration processes are necessary to maintain the positioning accuracy. This paper proposes a dynamic calibration method to initially calibrate and subsequently update the parameters of the propagation channel model using a Least Mean Squares approach. The method assumes that each anchor node in the localization infrastructure is characterized by its own propagation channel model. In practice, a set of sniffers is used to collect RSS samples, which will be used to automatically calibrate each channel model by iteratively minimizing the positioning error. The proposed method is validated through numerical simulation, showing that the positioning error of the mobile nodes is effectively reduced. Furthermore, the method has a very low computational cost; therefore it can be used in real-time operation for wireless resource-constrained nodes.
date: 2011
date_type: published
publisher: Springer Verlag
official_url: http://hais.pwr.wroc.pl/
full_text_status: public
pres_type: paper
place_of_pub: Berlin, Alemania
event_title: 6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011
event_location: Wroclaw, Polonia
event_dates: 23/05/2011 - 25/05/2011
event_type: conference
institution: Telecomunicacion
department: Senales
refereed: TRUE
isbn: 978-3-642-21221-5
book_title: Proceedings of he 6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011
rights: by-nc-nd
citation:   Tarrío Alonso, Paula and Bernardos Barbolla, Ana M. and Xian, Wan and Casar Corredera, José Ramón  (2011).  Dynamic chanel model LMS updating for RSS-based localization.  In: "6th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2011", 23/05/2011 - 25/05/2011, Wroclaw, Polonia. ISBN 978-3-642-21221-5.    
document_url: https://oa.upm.es/11637/2/INVE_MEM_2011_102941.pdf