Transfer Entropy and Granger Causality in Real-world Telecommunication Networks

Abstract Telecommunication networks are highly intricate, with numerous interacting components influenced by various known and unknown factors. Among these, Radio Access Networks (RANs) play a critical role in wireless communication. Unraveling causal relationships within such complex systems is essential for their improvement and optimization through statistical and data analysis techniques. This study pioneers the application of Transfer Entropy (TE) and Granger Causality (GC) to real-world telecommunication networks, marking the first exploration of these methods in this context. We assess their effectiveness in identifying relationships among key network attributes, offering insights for potential system optimization in practical scenarios. Furthermore, our research extends to a comparative analysis of TE and GC under varying network load conditions, utilizing live data collected from multiple base stations to uncover common patterns across identified network attributes.