An Artificial Neural Network Approach for Mechanisms of Call Admission Control in UMTS 3G Networks

CAC-RD (call admission control based on reservation and diagnosis) [1] is call admission control (CAC) for UMTS (universal mobile terrestrial system) 3G networks. It is based on two schemes: channel reservation and network diagnosis. When compared to other CAC mechanisms, CAC-RD can guarantee networ...

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Bibliographic Details
Published in2008 Eighth International Conference on Hybrid Intelligent Systems pp. 459 - 464
Main Authors Ribeiro, A.I., Duarte-Figueiredo, F., Novy, G., Storck, C., Dias, S.M., Zarate, L.E.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2008
Subjects
3G mobile communication
3G networks
admission control
Artificial neural networks
Computational modeling
Equations
Mathematical model
neural networks
Power control
QoS
simulations
Training
UMTS
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Summary:CAC-RD (call admission control based on reservation and diagnosis) [1] is call admission control (CAC) for UMTS (universal mobile terrestrial system) 3G networks. It is based on two schemes: channel reservation and network diagnosis. When compared to other CAC mechanisms, CAC-RD can guarantee network availability, reducing priority classes blocking and guarantying some network QoS requirements. Due to computational resource limits, simulations cannot answer related to admission control in big networks with thousands of users. This work presents a method to extrapolate scientific questions like CAC's behavior with thousands of users and many antennas. An artificial neural network (ANN) approach for CAC-RD in UMTS 3G networks is presented. Its main goal is ANN training with the CAC-RD behavior. It is expected that the ANN can answer questions related to real cellular 3G networks admission control.
DOI:10.1109/HIS.2008.39