Motoharu Sasaki

Retraining-Free Cross-Environment Adaptation in Mobile Networks via a Learned-Gating Mixture-ofExperts: Application to UL Throughput Prediction

This paper proposes a learned-gating Mixture-of-Experts (MoE) framework that integrates multiple pretrained throughput prediction models without retraining for crossenvironment adaptation in commercial mobile networks. The framework retains global experts and cluster-specific experts trained in urban and suburban areas...