Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals
Mondal, R., Ristaniemi, T., & Turkka, J. (2015). Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Outdoor Signals. In ICICS 2015 : Proceedings of the 10th International conference on information, communications and signal processing, December 2-4, 2015, Singapore (pp. 1-5). IEEE. https://doi.org/10.1109/ICICS.2015.7459987
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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 gridbased 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. ...
Parent publication ISBN978-1-4673-7216-9
ConferenceInternational conference on information, communications and signal processing
Is part of publicationICICS 2015 : Proceedings of the 10th International conference on information, communications and signal processing, December 2-4, 2015, Singapore
Publication in research information system
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Cluster-based RF fingerprint positioning using LTE and WLAN signal strengths Mondal, Riaz; Ristaniemi, Tapani; Turkka, Jussi (Springer New York LLC, 2017)Wireless Local Area Network (WLAN) positioning has become a popular localization system due to its low-cost installation and widespread availability of WLAN access points. Traditional grid-based radio frequency (RF) ...
An efficient cluster-based outdoor user positioning using LTE and WLAN signal strengths Mondal, Riaz; Turkka, Jussi; Ristaniemi, Tapani (Institute of Electrical and Electronic Engineers, 2015)In this paper we propose a novel cluster-based RF fingerprinting method for outdoor user-equipment (UE) positioning using both LTE and WLAN signals. It uses a simple cost effective agglomerative hierarchical clustering ...
Radio frequency fingerprinting for outdoor user equipment localization Mondal, Riaz Uddin (University of Jyväskylä, 2017)The recent advancements in cellular mobile technology and smart phone usage have opened opportunities for researchers and commercial companies to develop ubiquitous low cost localization systems. Radio frequency (RF) ...
Genetic Algorithm Optimized Grid-based RF Fingerprint Positioning in Heterogeneous Small Cell Networks Mondal, Riaz; Ristaniemi, Tapani; Turkka, Jussi (IEEE, 2015)In this paper we propose a novel optimization algorithm for grid-based RF fingerprinting to improve user equipment (UE) positioning accuracy. For this purpose we have used Multi-objective Genetic Algorithm (MOGA) which ...
An efficient grid-based RF fingerprint positioning algorithm for user location estimation in heterogeneous small cell networks Mondal, Riaz; Turkka, Jussi; Ristaniemi, Tapani (IEEE, 2014)This paper proposes a novel technique to enhance the performance of grid-based Radio Frequency (RF) fingerprint position estimation framework. First enhancement is an introduction of two overlapping grids of training ...