A framework for modelling mobile radio access networks for intelligent fault management

The increased level of heterogeneity among the network components of current mobile Radio Access Networks (RANs), has meant that conventional network troubleshooting techniques are no longer sustainable; impacting negatively on customer experience and Quality of Service (QoS). Intelligent Fault Management (IFM) is a promising approach that utilizes the power of data mining in addressing emerging and future challenges in RAN network troubleshooting and performance management. This paper provides a comprehensive integrated RAN modelling framework in order to reflect protocol, topology, service inventory, and correlations between Alarms in a typical Mobile Radio Access Network (RAN). It proposes and presents results from a RAN model leading towards an effective Network Management System (NMS) datasets that could be analysed to discover alarm rules, associations and core drivers using different data mining techniques, graph theory measures and data benchmarking methodologies.