Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/16514
Title: The application of self-organising neural networks to location detection in 3G systems
Authors: Debono, Carl James
Buhagiar, Julian K.
Keywords: Neural networks (Computer science)
Telecommunication
Wireless localization
Self-organizing systems
Issue Date: 2005
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Debono, C. J., & Buhagiar, J. K. (2005). The application of self-organising neural networks to location detection in 3G systems. 6th IEE International Conference on 3G and Beyond, London. 1-5.
Abstract: A solution to mobile user location identification in 3G wireless systems based on a self-organising neural network architecture is presented. Radio signals from the mobile terminal's serving base stations are captured by the terminal, encapsulated and transmitted to the location detection server. These signals are fed to the neural network which translates the radio signals into neural coordinates, which are then triangulated to determine the user's location. Simulation results demonstrate that allowing a two meter error, the algorithm is capable of locating the user's position in 92% of the cases.
URI: https://www.um.edu.mt/library/oar//handle/123456789/16514
Appears in Collections:Scholarly Works - FacICTCCE

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