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 …
[HTML][HTML] Communication-enabled deep reinforcement learning to optimise energy-efficiency in UAV-assisted networks
Unmanned aerial vehicles (UAVs) are increasingly deployed to provide wireless
connectivity to static and mobile ground users in situations of increased network demand or …
connectivity to static and mobile ground users in situations of increased network demand or …
5G Network on Wings: A Deep Reinforcement Learning Approach to the UAV-based Integrated Access and Backhaul
Fast and reliable wireless communication has become a critical demand in human life. In the
case of mission-critical (MC) scenarios, for instance, when natural disasters strike, providing …
case of mission-critical (MC) scenarios, for instance, when natural disasters strike, providing …
Empowering Non-Terrestrial Networks with Artificial Intelligence: A Survey
6G networks can support global, ubiquitous and seamless connectivity through the
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …
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 …
Towards autonomous multi-UAV wireless network: A survey of reinforcement learning-based approaches
Unmanned aerial vehicle (UAV)-based wireless networks have received increasing
research interest in recent years and are gradually being utilized in various aspects of our …
research interest in recent years and are gradually being utilized in various aspects of our …
Integrating LEO satellites and multi-UAV reinforcement learning for hybrid FSO/RF non-terrestrial networks
Integrating low-altitude earth orbit (LEO) satellites (SATs) and unmanned aerial vehicles
(UAVs) within a non-terrestrial network (NTN), we investigate the problem of forwarding …
(UAVs) within a non-terrestrial network (NTN), we investigate the problem of forwarding …
Reinforcement learning for satellite communications: From LEO to deep space operations
PVR Ferreira, R Paffenroth… - IEEE …, 2019 - ieeexplore.ieee.org
The National Aeronautics and Space Administration (NASA) is in the midst of defining and
developing the future space and ground architecture for the coming decades to return …
developing the future space and ground architecture for the coming decades to return …
Deep reinforcement learning for multi-user access control in non-terrestrial networks
Non-Terrestrial Networks (NTNs) composed of space-borne (eg, satellites) and airborne
vehicles (eg, drones and blimps) have recently been proposed by 3GPP as a new paradigm …
vehicles (eg, drones and blimps) have recently been proposed by 3GPP as a new paradigm …
DeepWiERL: Bringing deep reinforcement learning to the internet of self-adaptive things
F Restuccia, T Melodia - IEEE INFOCOM 2020-IEEE …, 2020 - ieeexplore.ieee.org
Recent work has demonstrated that cutting-edge advances in deep reinforcement learning
(DRL) may be leveraged to empower wireless devices with the much-needed ability to" …
(DRL) may be leveraged to empower wireless devices with the much-needed ability to" …