• Here we have coded a state-of-the-art mobility management algorithms for 5G networks using Deep Reinforcement Learning (BCQ, DQN, DDPG) implemented by Python Torch and TensorFlow with 20% improvement in the overall handover KPIs;

• The developed algorithm uses generative AI to construct synthetic experience replay data and train itself on this data in an offline fashion, resulting in a significant reduction in the online training time.

• The code requires communication with the simulator of Nokia Bell Labs which emulates a near-real-world environment for mobility management and other network layer design tasks.