The application of self-organising neural networks to location detection in 3G systems

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.