Towards autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches

Y Bai, H Zhao, X Zhang, Z Chang… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV)-based wireless networks have received increasing
research interest in recent years and are gradually being utilized in various aspects of our …

Machine learning-aided operations and communications of unmanned aerial vehicles: A contemporary survey

H Kurunathan, H Huang, K Li, W Ni… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …

Deep reinforcement learning based latency minimization for mobile edge computing with virtualization in maritime UAV communication network

Y Liu, J Yan, X Zhao - IEEE Transactions on Vehicular …, 2022 - ieeexplore.ieee.org
The rapid development of maritime activities has led to the emergence of more and more
computation-intensive applications. In order to meet the huge demand for wireless …

Multi-agent reinforcement learning aided intelligent UAV swarm for target tracking

Z **a, J Du, J Wang, C Jiang, Y Ren… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Past few years have witnessed the widespread adoption of unmanned aerial vehicles
(UAVs) in target tracking for regional monitor and strike. Most existing target tracking …

UAV trajectory planning in wireless sensor networks for energy consumption minimization by deep reinforcement learning

B Zhu, E Bedeer, HH Nguyen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) have emerged as a promising candidate solution for data
collection of large-scale wireless sensor networks (WSNs). In this paper, we investigate a …

Deep reinforcement learning based dynamic trajectory control for UAV-assisted mobile edge computing

L Wang, K Wang, C Pan, W Xu, N Aslam… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In this paper, we consider a platform of flying mobile edge computing (F-MEC), where
unmanned aerial vehicles (UAVs) serve as equipment providing computation resource, and …

Resource scheduling based on deep reinforcement learning in UAV assisted emergency communication networks

C Wang, D Deng, L Xu, W Wang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) assisted emergency communication is an important
technique for future B5G/6G scenario. The UAV is usually considered as a mobile relay to …

Artificial intelligence for UAV-enabled wireless networks: A survey

MA Lahmeri, MA Kishk… - IEEE Open Journal of the …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for
the next-generation wireless communication networks. Their mobility and their ability to …

Trajectory design for UAV-based Internet of Things data collection: A deep reinforcement learning approach

Y Wang, Z Gao, J Zhang, X Cao… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
In this article, we investigate an unmanned aerial vehicle (UAV)-assisted Internet of Things
(IoT) system in a sophisticated 3-D environment, where the UAV's trajectory is optimized to …

Aerial intelligent reflecting surface-enabled terahertz covert communications in beyond-5G Internet of Things

MT Mamaghani, Y Hong - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting
wireless communications in the Internet of Things (IoT). On the other hand, terahertz (THz) …