DocumentCode :
3770864
Title :
Cluster-based RF fingerprint positioning using LTE and WLAN outdoor signals
Author :
Riaz Uddin Mondal;Tapani Ristaniemi;Jussi Turkka
Author_Institution :
Department of Mathematical Information Technology, University of Jyvaskyla, Jyvaskyla, Finland
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper we evaluate user-equipment (UE) positioning performance of three cluster-based RF fingerprinting methods using LTE and WLAN signals. Real-life LTE and WLAN data were collected for the evaluation purpose using consumer cellular-mobile handset utilizing `Nemo Handy´ drive test software tool. Test results of cluster-based methods were compared to the conventional grid-based RF fingerprinting. The cluster-based methods do not require grid-cell layout and training signature formation as compared to the grid-based method. They utilize LTE cell-ID searching technique to reduce the search space for clustering operation. Thus UE position estimation is done in short time with less computational cost. Among the cluster-based methods Agglomerative Hierarchical Cluster based RF fingerprinting provided best positioning accuracy using a single LTE and six WLAN signal strengths. This method showed an improvement of 42.3 % and 39.8 % in the 68th percentile and 95th percentile of positioning error (PE) over the grid-based RF fingerprinting.
Keywords :
"Wireless LAN","Fingerprint recognition","Radio frequency","Training","IEEE 802.11 Standard","Euclidean distance","Long Term Evolution"
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing (ICICS), 2015 10th International Conference on
Type :
conf
DOI :
10.1109/ICICS.2015.7459987
Filename :
7459987
Link To Document :
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