Mobile Radio Communications
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Artificial Neural Networks: An Introduction to Ann Theory and Practice
Artificial Neural Networks: An Introduction to Ann Theory and Practice
An Introduction to GSM
Mobile Communication Systems
Position location using wireless communications on highways of the future
IEEE Communications Magazine
GSM Mobile Station Location Using Reference Stations and Artificial Neural Networks
Wireless Personal Communications: An International Journal
Controlling Uncertainty in Personal Positioning at Minimal Measurement Cost
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
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In this paper, we describe a novelapproach to mobile station positioning using a GSMmobile phone. The approach is based on the use of aninherent feature of the GSM cellular system (themobile phone continuously measures radio signalstrengths from a number of the nearest base stations(antennas)) and on the use of this information to estimatethe phone's location. The current values of the signalstrengths are processed by a trained artificial neuralnetwork executed at the computer attached to themobile phone to estimate the position of the mobilestation in real time. The neural network configurationis obtained by using a genetic algorithm that searchesthe space of specific neural network types anddetermines which one provides the best locationestimation results. Two general methods are explored:the first is based on using a neural network forclassification and the second uses functionapproximation. The experimental results are reportedand discussed.