Automated Troubleshooting of Mobile Networks Using Bayesian Networks

In the current telecommunication scenarios operators have to cope with fast technological changes while increasing operational efficiency, i.e. diminishing operational expenditures and, at the same time, maximising performance of the networks. In this paper we present an automated troubleshooting tool for cellular networks, based on Bayesian networks, which will contribute to improve operational efficiency. We propose some Bayesian models for diagnosis in mobile networks and we present a troubleshooting tool, which uses those models to diagnose the cause of problems. A knowledge acquisition tool is also presented, which converts the knowledge of troubleshooting experts into Bayesian models by means of a friendly user interface. The models and tools have been tested in real mobile networks and some results and conclusions are also outlined in this paper.