Three-dimension trajectory design for multi-UAV wireless network with deep reinforcement learning
The effective trajectory design of multiple unmanned aerial vehicles (UAVs) is investigated
for improving the capacity of the communication system. The aim is for maximizing real-time …
for improving the capacity of the communication system. The aim is for maximizing real-time …
Multi-UAV dynamic wireless networking with deep reinforcement learning
This letter investigates a novel unmanned aerial vehicle (UAV)-enabled wireless
communication system, where multiple UAVs transmit information to multiple ground …
communication system, where multiple UAVs transmit information to multiple ground …
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 …
Connectivity-aware 3D UAV path design with deep reinforcement learning
In this paper, we study the three-dimensional (3D) path planning problem for cellular-
connected unmanned aerial vehicle (UAV) taking into account the impact of 3D antenna …
connected unmanned aerial vehicle (UAV) taking into account the impact of 3D antenna …
Reinforcement learning in multiple-UAV networks: Deployment and movement design
A novel framework is proposed for quality of experience driven deployment and dynamic
movement of multiple unmanned aerial vehicles (UAVs). The problem of joint non-convex …
movement of multiple unmanned aerial vehicles (UAVs). The problem of joint non-convex …
Trajectory design and resource allocation for multi-UAV networks: Deep reinforcement learning approaches
The future mobile communication system is expected to provide ubiquitous connectivity and
unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which …
unprecedented services over billions of devices. The unmanned aerial vehicle (UAV), which …
UAV path planning based on multi-layer reinforcement learning technique
Z Cui, Y Wang - Ieee Access, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) have been widely used in many applications due to its
small size, swift mobility and low cost. Therefore, the study of guidance, navigation and …
small size, swift mobility and low cost. Therefore, the study of guidance, navigation and …
Joint 3D deployment and power allocation for UAV-BS: A deep reinforcement learning approach
Due to its high mobility and low cost, unmanned aerial vehicle mounted base station (UAV-
BS) can be deployed in a fast and cost-efficient manner for providing wireless services in …
BS) can be deployed in a fast and cost-efficient manner for providing wireless services in …
A two-step environment-learning-based method for optimal UAV deployment
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 …
the coverage requirements of wireless users in various scenarios. In practical applications …
Optimal Tethered-UAV Deployment in A2G Communication Networks: Multi-Agent Q-Learning Approach
An unmanned aerial vehicle-mounted base station (UAV-BS) is a promising technology for
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …
the forthcoming sixth-generation wireless networks, owing to its flexibility and cost …