RT Journal Article
T1 Online Anomaly Detection System for Mobile Networks
A1 Burgueño Romero, Jesús
A1 De la Bandera Cascales, Isabel
A1 Mendoza, Jessica
A1 Palacios, David
A1 Morillas, Cesar
A1 Barco-Moreno, Raquel
K1 Sistemas de comunicaciones inalámbricos
AB The arrival of the Fifth-Generation (5G) standard has further accelerated the need foroperators to improve the network capacity. With this purpose, mobile network topologies withsmaller cells are being currently deployed to increase the frequency reuse. In this way, the number ofnodes that collect performance data is being further risen, so the amount of metrics to be managedand analyzed is being highly increased. Therefore, it is fundamental to have tools that automatethese tasks and inform the network operator of the relevant information within the vast amountof metrics collected. In this manner, it is particularly important the continuous monitoring of theperformance indicators and the automatic detection of anomalies for network operators to preventthe network degradation and users’ complaints. Therefore, in this paper a methodology to detectand track anomalies in the mobile networks performance indicators in real time is proposed. Thefeasibility of this system is evaluated with several performance metrics and a real LTE-Advanceddataset. In addition, it is also compared with the performance of other state-of-the-art anomalydetection systems.
PB MDPI
YR 2020
FD 2020
LK https://hdl.handle.net/10630/30174
UL https://hdl.handle.net/10630/30174
LA eng
NO Burgueño, J.; de-la-Bandera, I.; Mendoza, J.; Palacios, D.; Morillas, C.; Barco, R. Online Anomaly Detection System for Mobile Networks. Sensors 2020, 20, 7232.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026