NDLI: Experimental decomposition of the performance of fingerprinting-based localization algorithms

Content Provider	IEEE Xplore Digital Library
Author	Lemic, F. Behboodi, A. Handziski, V. Wolisz, A.
Copyright Year	2014
Description	Author affiliation: Telecommun. Networks Group, Tech. Univ. Berlin, Berlin, Germany (Lemic, F.; Behboodi, A.; Handziski, V.; Wolisz, A.)
Abstract	Despite their popularity, the current praxis of comparative experimental evaluation of fingerprinting-based localization algorithms is lacking rigor, with studies typically following an ad-hoc evaluation process and focusing on black-box comparison of complete algorithms. In this paper we present a systematic benchmarking methodology that is focused on gaining finegrained insight about the relative contributions of the individual phases of the fingerprinting-based localization algorithms to their overall performance. To this end, we decompose the localization algorithms in common phases (collection of raw measurements, creation of fingerprints, pattern matching and post-processing) and systematically asses the performance of different procedures that can be applied in each of these phases. We illustrate the application of the proposed methodology using a comprehensive experimental case-study of 3 WiFi fingerprinting algorithms with 4 raw RSSI collection procedures, 3 fingerprint creation and pattern matching procedures, 4 different post-processing procedures in 3 testbeds and 4 evaluation scenarios, resulting in 36 individual experiments. The results demonstrate that in the evaluated scenarios, a lower number of WiFi APs and rather simple fingerprint creation and pattern matching can achieve better performance in terms of location accuracy than more sophisticated alternatives. The results also show that postprocessing steps like k-Nearest Neighbours (kNN) procedure are indeed effective in reducing the localization error variability and extremes, thus increasing the stability of the location estimation.
Starting Page	355
Ending Page	364
File Size	2451169
Page Count	10
File Format	PDF
ISBN	9781467380546
DOI	10.1109/IPIN.2014.7275503
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-27
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Wireless communication Runtime Phase measurement Fingerprinting phases Indoor localization Benchmark testing Received Signal Strength Indicator WiFi fingerprinting algorithms Pattern matching IEEE 802.11 Standard WiFi beacon packets
Content Type	Text
Resource Type	Article

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