CIPAT: A Two-stage Configuration Impact Prediction Analysis Toolkit for Cellular Networks

Improving network performance and user experience by tuning network configurations is crucial to cellular service providers (CSPs). However, predicting the performance impacts of configuration changes is non-trivial. The large scale, diversity and complexity of configuration parameters and base station deployments, and more importantly, the uncontrollable external factors ( e.g. , weather, called latents ), lead to confounding effects between configurations and performance metrics. In this paper, we show that the effects of latents can be properly mitigated by considering intermediates, called Mobility, Access, and Traffic (MAT) metrics , which separate the configurations and latents from performance metrics. Then, we propose the Configuration Impact Prediction Analysis Toolkit (CIPAT), a novel two-stage toolkit, driven by a large real-world dataset from live LTE and 5G networks. Our extensive evaluation shows that CIPAT enables network operators to confidently predict the performance impact of candidate configuration settings with an accuracy of up to 86% and an efficacy of up to 85%.