Reinforcement learning in multiple-UAV networks: Deployment and movement design
A novel framework is proposed for quality of experience driven deployment and dynamic
movement of multiple unmanned aerial vehicles (UAVs). The problem of joint non-convex …
movement of multiple unmanned aerial vehicles (UAVs). The problem of joint non-convex …
Reinforcement learning for decentralized trajectory design in cellular UAV networks with sense-and-send protocol
Recently, the unmanned aerial vehicles (UAVs) have been widely used in real-time sensing
applications over cellular networks. The performance of a UAV is determined by both its …
applications over cellular networks. The performance of a UAV is determined by both its …
Three-dimension trajectory design for multi-UAV wireless network with deep reinforcement learning
The effective trajectory design of multiple unmanned aerial vehicles (UAVs) is investigated
for improving the capacity of the communication system. The aim is for maximizing real-time …
for improving the capacity of the communication system. The aim is for maximizing real-time …
Resource allocation in UAV-assisted networks: A clustering-aided reinforcement learning approach
S Zhou, Y Cheng, X Lei, Q Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As an aerial base station, unmanned aerial vehicle (UAV) has been considered as a
promising technology to assist future wireless communications due to its flexible, swift and …
promising technology to assist future wireless communications due to its flexible, swift and …
Reinforcement learning-based collision avoidance and optimal trajectory planning in UAV communication networks
YH Hsu, RH Gau - IEEE Transactions on Mobile Computing, 2020 - ieeexplore.ieee.org
In this paper, we propose a reinforcement learning approach of collision avoidance and
investigate optimal trajectory planning for unmanned aerial vehicle (UAV) communication …
investigate optimal trajectory planning for unmanned aerial vehicle (UAV) communication …
Optimal Tethered-UAV Deployment in A2G Communication Networks: Multi-Agent Q-Learning Approach
An unmanned aerial vehicle-mounted base station (UAV-BS) is a promising technology for
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …
Intelligent trajectory design in UAV-aided communications with reinforcement learning
In this correspondence paper, we focus on a cellular network aided an unmanned aerial
vehicle (UAV) that serves as an aerial base station for multiple ground users. The UAV's …
vehicle (UAV) that serves as an aerial base station for multiple ground users. The UAV's …
Multi-UAV dynamic wireless networking with deep reinforcement learning
This letter investigates a novel unmanned aerial vehicle (UAV)-enabled wireless
communication system, where multiple UAVs transmit information to multiple ground …
communication system, where multiple UAVs transmit information to multiple ground …
Trajectory design and power control for multi-UAV assisted wireless networks: A machine learning approach
A novel framework is proposed for the trajectory design of multiple unmanned aerial
vehicles (UAVs) based on the prediction of users' mobility information. The problem ofjoint …
vehicles (UAVs) based on the prediction of users' mobility information. The problem ofjoint …
Joint optimization of multi-UAV target assignment and path planning based on multi-agent reinforcement learning
H Qie, D Shi, T Shen, X Xu, Y Li, L Wang - IEEE access, 2019 - ieeexplore.ieee.org
One of the major research topics in unmanned aerial vehicle (UAV) collaborative control
systems is the problem of multi-UAV target assignment and path planning (MUTAPP). It is a …
systems is the problem of multi-UAV target assignment and path planning (MUTAPP). It is a …