Cooperative trajectory design of multiple UAV base stations with heterogeneous graph neural networks

X Zhang, H Zhao, J Wei, C Yan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles as base stations (UAV-BSs) are recognized as effective means
for tackling eruptive communication service requirements especially when terrestrial …
被引用次数：33 相关文章 所有 2 个版本
[PDF] deepiiotlab.com

Joint optimization of access and backhaul links for UAVs based on reinforcement learning

A Fotouhi, M Ding, LG Giordano… - 2019 IEEE …, 2019 - ieeexplore.ieee.org
In this paper, we study the application of unmanned aerial vehicle (UAV) base stations (BSs)
in order to improve the cellular network capacity. We consider flying BSs where BS …
被引用次数：15 相关文章 所有 4 个版本

Resource allocation and trajectory design in UAV-aided cellular networks based on multiagent reinforcement learning

S Yin, FR Yu - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
In this article, we focus on a downlink cellular network, where multiple unmanned aerial
vehicles (UAVs) serve as aerial base stations for ground users through frequency-division …
被引用次数：70 相关文章

The application of multi-agent reinforcement learning in UAV networks

J Cui, Y Liu, A Nallanathan - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
This article investigates autonomous resource allocation of multiple UAVs enabled
communication networks with the goal of maximizing long-term rewards. To model the …
被引用次数：34 相关文章
[PDF] arxiv.org

Analysis of reinforcement learning schemes for trajectory optimization of an aerial radio unit

H Mohammadi, V Marojevic… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
This paper introduces the deployment of unmanned aerial vehicles (UAVs) as lightweight
wireless access points that leverage the fixed infrastructure in the context of the emerging …
被引用次数：4 相关文章 所有 4 个版本

Deep reinforcement learning for multi-user access control in UAV networks

Y Cao, L Zhang, YC Liang - ICC 2019-2019 IEEE International …, 2019 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) have recently been proposed as flying base stations,
called UAV-BSs, to provide reliable connections and extend the coverage of the existing …
被引用次数：24 相关文章

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

Federated deep reinforcement learning-based intelligent dynamic services in UAV-assisted MEC

P Hou, X Jiang, Z Wang, S Liu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs)-assisted multiaccess edge computing (MEC) has
emerged as a promising solution in B5G/6G networks. The high flexibility and seamless …
被引用次数：5 相关文章
[PDF] uwaterloo.ca

Packet routing in dynamic multi-hop UAV relay network: A multi-agent learning approach

R Ding, J Chen, W Wu, J Liu, F Gao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The multi-hop unmanned aerial vehicle (UAV) network can serve as data relays where
ground users (GUs) do not have reliable direct connections to the base station (BS). Existing …
被引用次数：33 相关文章 所有 3 个版本
[PDF] ieee.org

Multi-agent reinforcement learning-based resource allocation for UAV networks

J Cui, Y Liu, A Nallanathan - IEEE Transactions on Wireless …, 2019 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are capable of serving as aerial base stations (BSs) for
providing both cost-effective and on-demand wireless communications. This article …
被引用次数：468 相关文章 所有 5 个版本