Chilakala Sudhamani

Reinforcement learning-based unmanned aerial vehicle trajectory planning for ground users’ mobility management in heterogeneous networks

Simulation results demonstrate that the proposed algorithm outperforms existing benchmarks through learning-based adaptive control of UAVs’ mobility, ensuring ubiquitous network connectivity for GUs and reducing HO failures in HetNets.