Theses / Dissertations >
College of Engineering >
Please use this identifier to cite or link to this item:
|Title: ||Short-Term Traffic Volume Prediction In Umts Networks: Validation of Kalman Filter-Based Model.|
|Authors: ||Dorgbefu, Maxwell Jnr.|
|Issue Date: ||20-Sep-2012|
|Abstract: ||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 study explores traffic volume prediction and, adapts and validates the Kalman
filter-based short-term traffic volume prediction model for UMTS networks. In this
study, we adapt and validate the Kalman filter-based traffic volume prediction model
which is used more in transportation engineering.
The model was adapted based on two key assumptions that make it possible for us to
characterize the short-term traffic volume patterns for UMTS networks to suit the
Kalman filter algorithm. The model so adapted was carefully fine-tuned and
implemented in MATLAB. The model was then validated with traffic volume data
collected from a live 3G network using the graphical and r2 (coefficient of
determination) approaches to model validation.
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. The r2 approach
resulted in r2 values in the range of 0.87 to 0.99 which compare very well with the
observed traffic volumes. A little was done on sensitivity analysis of the model
parameters, and this has been recommended for future research. The result obtained in
this study brings out the fact that, the Kalman filter algorithm is very useful in predicting
short-term traffic volumes for UMTS networks.|
|Description: ||A Thesis submitted to the Department of Electrical and
Electronics Engineering, Kwame Nkrumah University of
Science and Technology
in partial fulfilment of the requirements for the degree of Master of Science, September-2012|
|Appears in Collections:||College of Engineering|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.