6G-XR

The proposed experiment, xDRL-RCS (eXplainable Deep Reinforcement Learning Assisted 5G/6G RAN and Core Slicing), aims to significantly enhance the management and operational efficiency of 5G/6G networks through advanced AI-driven techniques. This initiative addresses the critical demand for high-bandwidth and low-latency communications and taps into the transformative potential of 5G/6G technologies. The project's foundation involves comprehensive dataset preparation using open-source datasets and real data from the UOULU 5GTN research infrastructure.

This robust groundwork will support the development of sophisticated deep reinforcement learning (DRL) algorithms, which are set to be integrated into the FlexRIC system and OAI core network platform for improved real-time network slice management. The framework will be tested using the UOULU 5GTN testbed, demonstrating practical RAN and core slicing. The project will focus on adjusting critical network parameters, such as slice configuration, to enhance network performance and responsiveness.