Traffic Congestion Forecasting in WCDMA Networks

Kejing Zhang; Laurie Cuthbert

ChinaCom2008-Wireless Communications and Networking Symposium

Research Article

Traffic Congestion Forecasting in WCDMA Networks

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1109/CHINACOM.2008.4685191,
    author={Kejing Zhang and Laurie Cuthbert},
    title={Traffic Congestion Forecasting in WCDMA Networks},
    proceedings={ChinaCom2008-Wireless Communications and Networking Symposium},
    publisher={IEEE},
    proceedings_a={CHINACOM2008-WCN},
    year={2008},
    month={11},
    keywords={Traffic prediction maximum likelihood estimation radio resource management congestion control},
    doi={10.1109/CHINACOM.2008.4685191}
}

Kejing Zhang
Laurie Cuthbert
Year: 2008
Traffic Congestion Forecasting in WCDMA Networks
CHINACOM2008-WCN
IEEE
DOI: 10.1109/CHINACOM.2008.4685191

Kejing Zhang¹^,*, Laurie Cuthbert²^,*

1: Department of Electronic Engineering Queen Mary, University of London Mile End Road, London E1 4NS, UK +44 20 7882 5356
2: Department of Electronic Engineering Queen Mary, University of London Mile End Road, London E1 4NS, UK +44 20 7882 5333

*Contact email: kejing.zhang@elec.qmul.ac.uk, laurie.cuthbert@elec.qmul.ac.uk

Abstract

Congestion control is considered as a key factor in radio resource management. Early detection and rapid resolution network congestion can considerably improve network capacity. Consequently, much research has been carried out on predicting traffic patterns in 3G networks. This paper introduces a traffic forecasting method based on maximum likelihood estimation, which is able to predict traffic patterns when there is random movement of users.

Keywords: Traffic prediction maximum likelihood estimation radio resource management congestion control

Published: 2008-11-21
Publisher: IEEE
Modified: 2010-05-16

: http://dx.doi.org/10.1109/CHINACOM.2008.4685191