NDLI: Deconvolution-based indoor localization with WLAN signals and unknown access point locations

Content Provider	IEEE Xplore Digital Library
Author	Shrestha, S. Talvitie, J. Lohan, E.S.
Copyright Year	2013
Description	Author affiliation: Dept. of Electron. & Commun. Eng., Tampere Univ. of Technol., Tampere, Finland (Shrestha, S.; Talvitie, J.; Lohan, E.S.)
Abstract	In this paper, the problem of Received Signal Strength (RSS)-based WLAN positioning is newly formulated as a deconvolution problem and three deconvolution methods (namely Least Squares, Weighted Least Squares and Minimum Mean Square Error) are investigated with several RSS path loss models. The deconvolution approaches are compared with the fingerprinting approach in terms of performance and complexity. The main advantage of the deconvolution-based approaches versus the fingerprinting methods is the significant reduction in the size of the training database that need to be stored at the server side (and transferred to the mobile device) for the WLAN-based positioning. We will show that the deconvolution based estimation can decrease of the order of ten times the size of the training database, while still being able to achieve comparable root mean square errors in the distance estimation.
Starting Page	1
Ending Page	6
File Size	219577
Page Count	6
File Format	PDF
ISBN	9781479904846
ISSN	23250771
e-ISBN	9781479904860
DOI	10.1109/ICL-GNSS.2013.6577256
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Buildings Estimation Indoor localization Minimum Mean Square Error (MMSE) Weighted Least Squares (WLS) Mobile communication Educational institutions Access Point (AP) estimation WLAN positioning Training Deconvolution Databases Least Squares (LS)
Content Type	Text
Resource Type	Article

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