Energy-efficient multi-uav network using multi-agent deep reinforcement learning
With the explosive growth in mobile data traffic, unmanned aerial vehicles (UAVs) has
received much attention in recent years. While UAV offers a number of benefits, the …
received much attention in recent years. While UAV offers a number of benefits, the …
Toward energy-efficient UAV-assisted wireless networks using an artificial intelligence approach
This article studies the application of artificial intelligence (AI) approach in UAV-assisted
wireless networks to cope with a large number of parameters impacting energy-efficiency in …
wireless networks to cope with a large number of parameters impacting energy-efficiency in …
Multiagent Q-Learning-Based Multi-UAV Wireless Networks for Maximizing Energy Efficiency: Deployment and Power Control Strategy Design
In air-to-ground communications, the network lifetime depends on the operation time of
unmanned aerial vehicle-base stations (UAV-BSs) owing to the restricted battery capacity …
unmanned aerial vehicle-base stations (UAV-BSs) owing to the restricted battery capacity …
Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks
Unmanned aerial vehicles (UAVs) serving as aerial base stations can be deployed to
provide wireless connectivity to mobile users, such as vehicles. However, the density of …
provide wireless connectivity to mobile users, such as vehicles. However, the density of …
Optimal frequency reuse and power control in multi-UAV wireless networks: Hierarchical multi-agent reinforcement learning perspective
To overcome the problems caused by the limited battery lifetime in multiple-unmanned
aerial vehicle (UAV) wireless networks, we propose a hierarchical multi-agent reinforcement …
aerial vehicle (UAV) wireless networks, we propose a hierarchical multi-agent reinforcement …
Optimizing energy efficiency in UAV-assisted networks using deep reinforcement learning
In this letter, we study the energy efficiency (EE) optimization of unmanned aerial vehicles
(UAVs) providing wireless coverage to static and mobile ground users. Recent multi-agent …
(UAVs) providing wireless coverage to static and mobile ground users. Recent multi-agent …
Decentralized trajectory and power control based on multi-agent deep reinforcement learning in UAV networks
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 …
cellular networks by acting as aerial base stations (ABSs). Due to the limited on-board …
Multi-agent deep reinforcement learning for trajectory design and power allocation in multi-UAV networks
N Zhao, Z Liu, Y Cheng - IEEE Access, 2020 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) is regarded as an effective technology in future wireless
networks. However, due to the non-convexity feature of joint trajectory design and power …
networks. However, due to the non-convexity feature of joint trajectory design and power …
Energy Consumption Modeling and Optimization of UAV-Assisted MEC Networks Using Deep Reinforcement Learning
Unmanned aerial vehicle (UAV)-assisted multiaccess edge computing (MEC) technology
has garnered significant attention and has been successfully implemented in specific …
has garnered significant attention and has been successfully implemented in specific …
Deep reinforcement learning based resource allocation and trajectory planning in integrated sensing and communications UAV network
Y Qin, Z Zhang, X Li, W Huangfu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this paper, multi-UAVs serve as mobile aerial ISAC platforms to sense and communicate
with on-ground target users. To optimize the communication and sensing performance, we …
with on-ground target users. To optimize the communication and sensing performance, we …