Reinforcement learning in the sky: A survey on enabling intelligence in ntn-based communications
Non terrestrial networks (NTN) involving 'in the sky'objects such as low-earth orbit satellites,
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
Simultaneous navigation and radio mapping for cellular-connected UAV with deep reinforcement learning
Cellular-connected unmanned aerial vehicle (UAV) is a promising technology to unlock the
full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their …
full potential of UAVs in the future by reusing the cellular base stations (BSs) to enable their …
Aerial base station placement: A tutorial introduction
PQ Viet, D Romero - IEEE Communications Magazine, 2022 - ieeexplore.ieee.org
The deployment of aerial base stations (ABSs) mounted onboard unmanned aerial vehicles
is emerging as a promising technology to provide connectivity in areas where terrestrial …
is emerging as a promising technology to provide connectivity in areas where terrestrial …
Chase or wait: Dynamic UAV deployment to learn and catch time-varying user activities
Unmanned aerial vehicle (UAV) technology is a promising solution for rapidly providing
wireless communication services to ground users, where a UAV has limited service …
wireless communication services to ground users, where a UAV has limited service …
A transfer learning approach for UAV path design with connectivity outage constraint
The connectivity-aware path design is crucial in the effective deployment of autonomous
unmanned aerial vehicles (UAVs). Recently, reinforcement learning (RL) algorithms have …
unmanned aerial vehicles (UAVs). Recently, reinforcement learning (RL) algorithms have …
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 …
Spatial Deep Learning for Site-Specific Movement Optimization of Aerial Base Stations
Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (ABSs) to provide
wireless connectivity for ground users (GUs) in various emergency scenarios. However, it is …
wireless connectivity for ground users (GUs) in various emergency scenarios. However, it is …
Machine learning methods for uav flocks management-a survey
The development of unmanned aerial vehicles (UAVs) has been gaining momentum in
recent years owing to technological advances and a significant reduction in their cost. UAV …
recent years owing to technological advances and a significant reduction in their cost. UAV …
Enhanced border surveillance through a hybrid swarm optimization algorithm
Protecting borders from the illicit transfer of people, goods, and drones is essential for a
country's security and economic strength. Conventionally, most borders deploy manual …
country's security and economic strength. Conventionally, most borders deploy manual …
Learning to Fly: A Distributed Deep Reinforcement Learning Framework for Software-Defined UAV Network Control
Control and performance optimization of wireless networks of Unmanned Aerial Vehicles
(UAVs) require scalable approaches that go beyond architectures based on centralized …
(UAVs) require scalable approaches that go beyond architectures based on centralized …