A proactive indoor positioning system in randomly deployed dense WiFi networks

Chun Hsien Ko, Sau-Hsuan Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

A new approach for indoor positioning is presented, aimed at designing a WiFi positioning system that is feasible and convenient for both service providers and end users. In the proposed approach, only access points (APs) need to collect the received signal strengthes (RSS) of mobile devices, and use these RSS samples to jointly estimate the devices' locations. To enhance the accuracy of positioning, the relationship between the RSS samples and their geometrical locations is explored, leading to a sparse Bayesian model for the radio power map of the RSS observations of each AP. With more than 20 training anchors, the accuracy of the proposed model-based positioning method can be lower than 3.4 meters in an indoor space with only 4 randomly deployed APs, which outperforms the fingerprinting method by 0.4 meter. Extensive experimental results also verify that the proposed positioning service can offer considerable accuracy with only limited efforts in training, suggesting that the prototype is realistic for randomly deployed dense WiFi networks.

Original languageEnglish
Title of host publication2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013289
DOIs
StatePublished - 1 Jan 2016
Event59th IEEE Global Communications Conference, GLOBECOM 2016 - Washington, United States
Duration: 4 Dec 20168 Dec 2016

Publication series

Name2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings

Conference

Conference59th IEEE Global Communications Conference, GLOBECOM 2016
CountryUnited States
CityWashington
Period4/12/168/12/16

Keywords

  • Indoor Positioning
  • Location Based Service (LBS)
  • Radio Power Map (PRM)
  • Sparse Bayesian Learning
  • WiFi

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  • Cite this

    Ko, C. H., & Wu, S-H. (2016). A proactive indoor positioning system in randomly deployed dense WiFi networks. In 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings [7841536] (2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2016.7841536