6G-XR

5G-slAIce aims to implement an AI/ML-based system to allocate resources dynamically in a 5G network core. It will manage the scaling of User Plane Functions (UPFs) and reallocate physical resources to virtual slices based on network saturation. The system will use Incremental Learning (IL) for forecasting and a Reinforcement Learning (RL) agent for optimal resource management. By integrating these algorithms, 5G-slAIce seeks to enhance 5G and support future 6G networks, ensuring efficient resource management, preventing over-saturation, and maintaining service level agreements (SLAs) for an improved user experience.