Paper Info
Title
Measurement-Based Access Point Deployment Mechanism for Indoor Localization.
Abstract
In this paper, we study how to deploy new access points (AP) to achieve improved accuracy for WiFi-based indoor localization systems. Existing mechanisms in this aspect are typically simulation based and further they do not consider how to use pre-existing APs in target environment for achieving high localization performance. To overcome these issues, in this paper, we propose a measurement-based AP deployment mechanism (MAPD). MAPD takes advantage of those pre-existing APs to identify candidate positions with poor localization accuracy for deploying new APs. We then collect the fingerprints for all possible AP deployment layouts via over-deployment of APs, one at each candidate position. Finally, we present a greedy search algorithm to identify m positions out of the n candidate positions (m <= n) while minimizing the location error. Experimental results demonstrate that the localization errors can be largely reduced: Mean error distance can be reduced by 0.56 meter (26%) and 0.17 meter (10%) as compared with the case without deploying new APs and previous work, respectively; Moreover, the maximum location error can be reduced by 1.53 meter (27%) and 0.51 meter (11%), respectively.
Year
DOI
Venue
2015
10.1109/GLOCOM.2015.7417107
IEEE Global Communications Conference
Keywords
Field
DocType
Indoor localization,fingerprint based localization,AP deployment,WLAN
Software deployment,Algorithm design,Computer science,Fingerprint recognition,Computer network,Mean squared error,Real-time computing,Greedy algorithm,Metre (music),Linear programming,Wireless lan
Conference
ISSN
Citations 
PageRank 
2334-0983
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Dong Li100.68
Baoxian Zhang275767.30
Kui Huang370.91
Cheng Li428157.83