Predicting Outages in Radio Networks with Alarm Data

Modern cellular networks are complex systems offering a wide range of services and present challenges in detecting anomalous events when they do occur. The networks are engineered for high reliability and, hence, the data from these networks is predominantly normal with a small proportion being anomalous. From an operations perspective, it is important to detect these anomalies in a timely manner in order to mitigate them and preclude the occurrence of major failure events. In telecommunications diverse set of data such as KPIs, logs and alarms are generated to monitor the health and stability of the network element and the services carried over it [1]–[4].