An Information-Based Approach to Precision Analysis of Indoor WLAN Localization Using Location Fingerprint
1
Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2
China Internet Research Lab, Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Academic Editor: Raúl Alcaraz Martínez
Entropy 2015, 17(12), 8031-8055; https://doi.org/10.3390/e17127859
Received: 31 October 2015 / Accepted: 30 November 2015 / Published: 5 December 2015
(This article belongs to the Section Information Theory, Probability and Statistics)
In this paper, we proposed a novel information-based approach to precision analysis of indoor wireless local area network (WLAN) localization using location fingerprint. First of all, by using the Fisher information matrix (FIM), we derive the fundamental limit of WLAN fingerprint-based localization precision considering different signal distributions in characterizing the variation of received signal strengths (RSSs) in the target environment. After that, we explore the relationship between the localization precision and access point (AP) placement, which can provide valuable suggestions for the design of the highly-precise localization system. Second, we adopt the heuristic simulated annealing (SA) algorithm to optimize the AP locations for the sake of approaching the fundamental limit of localization precision. Finally, the extensive simulations and experiments are conducted in both regular line-of-sight (LOS) and irregular non-line-of-sight (NLOS) environments to demonstrate that the proposed approach can not only effectively improve the WLAN fingerprint-based localization precision, but also reduce the time overhead.
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Keywords:
WLAN localization; access point placement; location fingerprint; Fisher information; simulated annealing
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MDPI and ACS Style
Zhou, M.; Qiu, F.; Tian, Z.; Wu, H.; Zhang, Q.; He, W. An Information-Based Approach to Precision Analysis of Indoor WLAN Localization Using Location Fingerprint. Entropy 2015, 17, 8031-8055.
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