When Learning Meets Dynamics: Distributed User Connectivity Maximization in UAV-Based Communication Networks
<|reference_start|>When Learning Meets Dynamics: Distributed User Connectivity Maximization in UAV-Based Communication Networks: Distributed management over Unmanned Aerial Vehicle (UAV) based communication networks (UCNs) has attracted increasing research attention. In this work, we study a distributed user connectivity maximization problem in a UCN. The work features a horizontal study over different levels of information exchange during the distributed iteration and a consideration of dynamics in UAV set and user distribution, which are not well addressed in the existing works. Specifically, the studied problem is first formulated into a time-coupled mixed-integer non-convex optimization problem. A heuristic two-stage UAV-user association policy is proposed to faster determine the user connectivity. To tackle the NP-hard problem in scalable manner, the distributed user connectivity maximization algorithm 1 (DUCM-1) is proposed under the multi-agent deep Q learning (MA-DQL) framework. DUCM-1 emphasizes on designing different information exchange levels and evaluating how they impact the learning convergence with stationary and dynamic user distribution. To comply with the UAV dynamics, DUCM-2 algorithm is developed which is devoted to autonomously handling arbitrary quit's and join-in's of UAVs in a considered time horizon. Extensive simulations are conducted i) to conclude that exchanging state information with a deliberated task-specific reward function design yields the best convergence performance, and ii) to show the efficacy and robustness of DUCM-2 against the dynamics.<|reference_end|>
@article{li2024when,
    title={When Learning Meets Dynamics: Distributed User Connectivity Maximization
  in UAV-Based Communication Networks},
    author={Bowei Li, Saugat Tripathi, Salman Hosain, Ran Zhang, Jiang (Linda)
  Xie, Miao Wang},
    journal={arXiv preprint arXiv:2409.06010},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.06010},
    primaryClass={cs.NI cs.SY eess.SY}
}