Multiagent deep reinforcement learning for wireless-powered UAV networks
Unmanned aerial vehicles (UAVs) have attracted much attention lately and are being used
in a multitude of applications. But the duration of being in the sky remains to be an issue due …
in a multitude of applications. But the duration of being in the sky remains to be an issue due …
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 …
Multi-UAV-enabled AoI-aware WPCN: A multi-agent reinforcement learning strategy
Unmanned Aerial Vehicles (UAVs) have been deployed in virtually all tasks of enabling
wireless powered communication networks (WPCNs). To ensure sustainable energy support …
wireless powered communication networks (WPCNs). To ensure sustainable energy support …
Trajectory optimization of flying energy sources using q-learning to recharge hotspot uavs
Despite the increasing popularity of commercial usage of UAVs or drone-delivered services,
their dependence on the limited-capacity on-board batteries hinders their flight-time and …
their dependence on the limited-capacity on-board batteries hinders their flight-time and …
Joint power allocation and 3D deployment for UAV-BSs: A game theory based deep reinforcement learning approach
Ultra-dense unmanned aerial vehicle (UAV) plays an important role in the field of
communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial …
communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial …
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 …
UAV-enabled wireless power transfer: A tutorial overview
Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) has recently
emerged as a promising technique to provide sustainable energy supply for widely …
emerged as a promising technique to provide sustainable energy supply for widely …
Minimum throughput maximization for multi-UAV enabled WPCN: A deep reinforcement learning method
This paper investigates joint unmanned aerial vehicle (UAV) trajectory planning and time
resource allocation for minimum throughput maximization in a multiple UAV-enabled …
resource allocation for minimum throughput maximization in a multiple UAV-enabled …
Synchronizing UAV teams for timely data collection and energy transfer by deep reinforcement learning
Due to their promising applications and intriguing characteristics, Unmanned Aerial Vehicles
(UAVs) can be dispatched as flying base stations to serve multiple energy-constrained …
(UAVs) can be dispatched as flying base stations to serve multiple energy-constrained …
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 …