Joint UAV Movement Control and Load Balancing Based on Indirect Control in Air-Ground-Integrated Networks

C Huang, F Wang, W Xu - IEEE Wireless Communications …, 2024 - ieeexplore.ieee.org
Air–ground-integrated networks play a vital role in seamless coverage. The irregular
topologies and dynamic loads require a comprehensive cooperation between terrestrial …
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Decentralized trajectory and power control based on multi-agent deep reinforcement learning in UAV networks

B Chen, D Liu, L Hanzo - ICC 2022-IEEE International …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are capable of enhancing the coverage of existing
cellular networks by acting as aerial base stations (ABSs). Due to the limited on-board …
被引用次数：9 相关文章

Adaptive deployment of UAV-aided networks based on hybrid deep reinforcement learning

X Ma, S Hu, D Zhou, Y Zhou… - 2020 IEEE 92nd Vehicular …, 2020 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) can be used as air base stations to provide fast wireless
connections for ground users. Due to their constraints on both mobility and energy …
被引用次数：6 相关文章

Umix: Sustainable Multi-UAV Coordination for Aerial-Terrestrial Networks

T Ding, L Liu, Z Yan, L Cui - IEEE Transactions on Network …, 2024 - ieeexplore.ieee.org
The deployment of Unmanned Aerial Vehicles (UAVs) alongside wireless communication
networks as Aerial-Terrestrial Network (ATN) in vast and remote wilderness regions shows a …
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UAV-assisted 5G/6G networks: Joint scheduling and resource allocation based on asynchronous reinforcement learning

H Yang, J Zhao, J Nie, N Kumar… - IEEE INFOCOM 2021 …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) can be used as flying base stations (BSs) for providing
wireless communications and coverage enhancement in fifth/sixth-generation (5G/6G) …
被引用次数：16 相关文章

Dynamic UAV Deployment, Admission Control, and Power Control for Air-and-ground Cooperative Networks

C Wang, D Zhai, H Cao, R Zhang… - ICC 2022-IEEE …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT) has gained rapid development, but due to the limited battery
capacity and access capacity, there are many complex problems in the application. In this …
被引用次数：2 相关文章

QoE-driven adaptive deployment strategy of multi-UAV networks based on hybrid deep reinforcement learning

Y Zhou, X Ma, S Hu, D Zhou… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) serve as aerial base stations to provide controlled
wireless connections for ground users. Due to their constraints on both mobility and energy …
被引用次数：24 相关文章
[PDF] arxiv.org

Radio resource management for cellular-connected UAV: a learning approach

Y Li, AH Aghvami - IEEE Transactions on Communications, 2023 - ieeexplore.ieee.org
Integrating unmanned aerial vehicles (UAVs) into existing cellular networks encounters lots
of challenges, among which one of the most striking concerns is how to achieve harmonious …
被引用次数：13 相关文章 所有 7 个版本

Joint Optimization of Trajectory Control, Resource Allocation and User Association Based on DRL for Multi-Fixed-Wing UAV Networks

B Yin, X Fang, X Wang - IEEE Transactions on Wireless …, 2024 - ieeexplore.ieee.org
Owing to the abundance of onboard energy and wide coverage, fixed-wing unmanned
aerial vehicles (FW-UAVs) have better capabilities to serve as aerial base stations, thereby …
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[PDF] ieee.org

Multi-agent reinforcement learning for cooperative trajectory design of UAV-BS fleets in terrestrial/non-terrestrial integrated networks

LT Hoang, CT Nguyen, HD Le… - IEICE Communications …, 2024 - ieeexplore.ieee.org
Aerial base stations (ABSs) have been envisioned as a promising technology toward
ubiquitous coverage and seamless high-rate connectivity in sixth-generation (6G) wireless …
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