Anomaly Detection and Root Cause Analysis for LTE Radio Base Stations

Abstract: This project aims to detect possible anomalies in the resource consumption of radio base stations within the 4G LTE Radio architecture. This has been done by analyzing the statistical data that each node generates every 15 minutes, in the form of "performance maintenance counters". In this thesis, we introduce methods that allow resources to be automatically monitored after software updates, in order to detect any anomalies in the consumption patterns of the different resources compared to the reference period before the update. Additionally, we also attempt to narrow down the origin of anomalies by pointing out parameters potentially linked to the issue.