Trajectory optimization and power allocation scheme based on DRL in energy efficient UAV‐aided communication networks
C Wang, Y Cui, D Deng, W Wang… - Chinese Journal of …, 2022 - Wiley Online Library
With flexibility, convenience and mobility, unmanned aerial vehicles (UAVS) can provide
wireless communication networks with lower costs, easier deployment, higher network …
wireless communication networks with lower costs, easier deployment, higher network …
Joint trajectory and power optimization for energy efficient UAV communication using deep reinforcement learning
Y Cui, D Deng, C Wang, W Wang - IEEE INFOCOM 2021-IEEE …, 2021 - ieeexplore.ieee.org
In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless
communication, attracting intensive attentions. UAVs can not only serve as relays, but also …
communication, attracting intensive attentions. UAVs can not only serve as relays, but also …
Energy Efficient Multi-UAV Communication Using DDPG
Recently, unmanned aerial vehicles (UAVs) have been widely used in wireless
communication. They can serve as aerial base stations for ground users (GUs). However …
communication. They can serve as aerial base stations for ground users (GUs). However …
Deep reinforcement learning for trajectory design and power allocation in UAV networks
Unmanned aerial vehicle (UAV) is considered to be a key component in the next-generation
cellular networks. Considering the non-convex characteristic of the trajectory design and …
cellular networks. Considering the non-convex characteristic of the trajectory design and …
Multi-agent deep reinforcement learning for optimising energy efficiency of fixed-wing UAV cellular access points
Unmanned Aerial Vehicles (UAVs) promise to become an intrinsic part of next generation
communications, as they can be deployed to provide wireless connectivity to ground users …
communications, as they can be deployed to provide wireless connectivity to ground users …
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 …
Cellular-connected UAV trajectory design with connectivity constraint: A deep reinforcement learning approach
Cellular-connected unmanned aerial vehicle (UAV) communication has attracted
increasingly attention recently. We consider a cellular-connected UAV carried with limited on …
increasingly attention recently. We consider a cellular-connected UAV carried with limited on …
Multi-agent model-based reinforcement learning for trajectory design and power control in UAV-enabled networks
S Zhou, Y Cheng, X Lei - 2022 3rd Information Communication …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) serving as aerial base stations is a promising technology
for wireless communications. This paper formulates a joint optimization problem of UAV …
for wireless communications. This paper formulates a joint optimization problem of UAV …
Energy minimization for cellular-connected UAV: From optimization to deep reinforcement learning
Cellular-connected unmanned aerial vehicles (UAVs) are expected to become integral
components of future cellular networks. To this end, one of the important problems to …
components of future cellular networks. To this end, one of the important problems to …
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 …
相关搜索
- power allocation trajectory design
- power allocation uav networks
- power optimization uav communication
- trajectory optimization communication networks
- joint trajectory uav communication
- uav networks trajectory design
- joint trajectory power optimization
- uav networks deep reinforcement
- power allocation deep reinforcement
- reinforcement learning uav communication
- reinforcement learning power optimization
- energy efficiency power control