Research on Meta-Learning Bayesian Hierarchical Model with Application in Telecommunication System

Telecommunication systems may have different states, such as normal, warning, etc. Predicting key performance indicators for telecommunication systems in different states is important for monitoring and anomaly detection. However, there are challenges due to the different data evolution mechanisms in different cells and the unbalanced data sizes in different states. To address this, we propose a Meta-Learning Bayesian Hierarchical Model (ML-BHM) that incorporates knowledge sharing between cells and states. We apply this model to a real case study for cell KPI prediction and show that its effectiveness and efficiency.