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Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

arXiv 1705.02723 ↗First posted 8 May 2017cs.IT math.DS math.ITcited by 31

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Abstract (arXiv)

Unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication due to their high maneuverability, flexible deployment, and low cost. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations (BSs) are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAVs' trajectory and power control. The formulated problem is a mixed integer non-convex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the non-convex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge to at least a locally optimal solution. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 May 2017.

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Citing papers per year: 2021: 5; 2022: 1; 2023: 9; 2024: 5; 2025: 3; 2026: 8.

31 papers.

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  1. 20213D UAV Trajectory and Data Collection Optimisation via Deep Reinforcement Learningcited by 8
  2. 2025Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learningcited by 5
  3. 2025Scalable UAV Multi-Hop Networking via Multi-Agent Reinforcement Learning with Large Language Modelscited by 4
  4. 2021UAV-Assisted Communication in Remote Disaster Areas using Imitation Learningcited by 3
  5. 2021Energy-aware optimization of UAV base stations placement via decentralized multi-agent Q-learningcited by 3
  6. 2022UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithmscited by 3
  7. 2024Latency Minimization for UAV-Enabled Federated Learning: Trajectory Design and Resource Allocationcited by 3
  8. 2023A2-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systemscited by 2
  9. 2023Collaborative Learning with a Drone Orchestratorcited by 2
  10. 2023Joint Path planning and Power Allocation of a Cellular-Connected UAV using Apprenticeship Learning via Deep Inverse Reinforcement Learningcited by 2
  11. 2024Graph Attention-based Reinforcement Learning for Trajectory Design and Resource Assignment in Multi-UAV Assisted Communicationcited by 2
  12. 2024Non-iterative Optimization of Trajectory and Radio Resource for Aerial Networkcited by 2
19 more
  1. 2021Optimization for Master-UAV-powered Auxiliary-Aerial-IRS-assisted IoT Networks: An Option-based Multi-agent Hierarchical Deep Reinforcement Learning Approachcited by 1
  2. 2023Physics-Based Trajectory Design for Cellular-Connected UAV in Rainy Environments Based on Deep Reinforcement Learningcited by 1
  3. 2024Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless IIoT Networkscited by 1
  4. 2026Plasticity-Enhanced Multi-Agent Mixture of Experts for Dynamic Objective Adaptation in UAVs-Assisted Emergency Communication Networkscited by 1
  5. 2021Responsive Regulation of Dynamic UAV Communication Networks Based on Deep Reinforcement Learningcited by 0
  6. 2023UAV aided Metaverse over Wireless Communications: A Reinforcement Learning Approachcited by 0
  7. 2023AI-based Radio and Computing Resource Allocation and Path Planning in NOMA NTNs: AoI Minimization under CSI Uncertaintycited by 0
  8. 2023Federated Multi-Agent Deep Reinforcement Learning for Dynamic and Flexible 3D Operation of 5G Multi-MAP Networkscited by 0
  9. 2023UAV-assisted Semantic Communication with Hybrid Action Reinforcement Learningcited by 0
  10. 2023On Designing Multi-UAV aided Wireless Powered Dynamic Communication via Hierarchical Deep Reinforcement Learningcited by 0
  11. 2024Collaborative Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Trajectory Design for 3D UAV Trackingcited by 0
  12. 2025Energy Efficient Task Offloading in UAV-Enabled MEC Using a Fully Decentralized Deep Reinforcement Learning Approachcited by 0
  13. 2026Hybrid Belief Reinforcement Learning for Efficient Coordinated Spatial Explorationcited by 0
  14. 2026Networking-Aware Energy Efficiency in Agentic AI Inference: A Surveycited by 0
  15. 2026RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modelingcited by 0
  16. 2026PRIME: Plasticity Recovery in Multi-Agent Environments for UAV-Assisted Emergency Communication Networkscited by 0
  17. 2026Arm2Air: Cross-Embodiment Skeleton Transfer for 3D Relay Formationcited by 0
  18. 2026The Operable Pareto Front: Distilling Offline Search into Run-Time Control for Multi-Objective UAV Edge-Computing Schedulingcited by 0
  19. 2026Threat-Aware Energy-Efficient Deployment for Dynamic UAV Networks: A Multi-Agent RL Approachcited by 0