Academy & Industry Research Collaboration Center
Accurate traffic volume prediction in Universal Mobile Telecommunication System (UMTS) networks has become increasingly important because of its vital role in determining the Quality of Service (QoS) received by subscribers on these networks. This paper developed a short-term traffic volume prediction model using the Kalman filter algorithm. The model was implemented in MATLAB and validated using traffic volume dataset collected from a real telecommunication network using graphical and r2 (coefficient of determination) approaches. The results indicate that the model performs very well as the predicted traffic volumes compare very closely with the observed traffic volumes on the graphs.