AI/ML-Based QoS Recommendations for Energy Optimization in 6G Networks

The evolution of 5G networks toward 6G introduces new challenges in simultaneously meeting stringent QoS requirements and improving energy efficiency. In this letter, we propose an AI/ML-based framework that leverages 3GPP-defined functions—specifically, NWDAF, EIF, and SSF—to generate customized per-UE latency recommendations. These recommendations are incorporated into an optimization framework that jointly performs energy-aware UP-path adjustment and transmit-power control. Through simulations, we demonstrate that this method achieves superior energy—latency performance compared to traditional baselines, positioning it as a strong candidate for 6G networks.