Reinforcement learning based resource allocation for coverage continuity in high dynamic UAV communication networks

J Li, C Zhou, J Liu, M Sheng, N Zhao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicles mounted aerial base stations (ABSs) are capable of providing on-
demand coverage in next-generation mobile communication system. However, resource …

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) …

A two-step environment-learning-based method for optimal UAV deployment

X Luo, Y Zhang, Z He, G Yang, Z Ji - IEEE Access, 2019 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) can be used as low-altitude flight base stations to satisfy
the coverage requirements of wireless users in various scenarios. In practical applications …

Multi-UAV dynamic wireless networking with deep reinforcement learning

Q Wang, W Zhang, Y Liu, Y Liu - IEEE Communications Letters, 2019 - ieeexplore.ieee.org
This letter investigates a novel unmanned aerial vehicle (UAV)-enabled wireless
communication system, where multiple UAVs transmit information to multiple ground …

A reinforcement learning approach for fair user coverage using UAV mounted base stations under energy constraints

HV Abeywickrama, Y He, E Dutkiewicz… - IEEE Open Journal …, 2020 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) are gaining popularity in many aspects of wireless
communication systems. UAV-mounted mobile base stations (UAV-BSs) are an effective and …

UAV trajectory design and bandwidth allocation for coverage maximization with energy and time constraints

X Jing, C Masouros - … on Personal, Indoor and Mobile Radio …, 2020 - ieeexplore.ieee.org
Unmanned Aerial Vehicle (UAV) networks have recently gained interest, owing to the
mobility of UAVs that can be exploited to improve channel conditions and user coverage. In …

Dense Multi-Agent Reinforcement Learning Aided Multi-UAV Information Coverage for Vehicular Networks

H Fu, J Wang, J Chen, P Ren, Z Zhang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
With the rapid development of wireless communication networks, UAVs serving as base
stations are increasingly being applied in various scenarios which not only include edge …

Trace Pheromone-Based Energy-Efficient UAV Dynamic Coverage Using Deep Reinforcement Learning

X Cheng, R Jiang, H Sang, G Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are widely used in disaster or remote areas to provide
ubiquitous service. Due to the limited energy and communication range of UAVs, and the …

Deep reinforcement learning for user access control in UAV networks

Y Cao, L Zhang, YC Liang - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAV) are recently proposed as the flying base stations (BS),
namely, UAV-BS, to boost the capacity as well as extend the coverage of the current …

Deployment algorithms for UAV airborne networks toward on-demand coverage

H Zhao, H Wang, W Wu, J Wei - IEEE Journal on Selected …, 2018 - ieeexplore.ieee.org
Due to the flying nature of unmanned aerial vehicles (UAVs), it is very attractive to deploy
UAVs as aerial base stations and construct airborne networks to provide service for on …