Reinforcement learning for dynamic aerial base station positioning
I Lee - 2020 - ideals.illinois.edu
Reliable communication infrastructure plays an extremely important role in peoples'
everyday lives and the lack of sufficient communication means could have severe negative …
everyday lives and the lack of sufficient communication means could have severe negative …
Deep reinforcement learning for UAV-assisted emergency response
In the aftermath of a disaster, the ability to reliably communicate and coordinate emergency
response could make a meaningful difference in the number of lives saved or lost. However …
response could make a meaningful difference in the number of lives saved or lost. However …
[PDF][PDF] Deep Reinforcement Learning for UAV-Assisted Emergency
In the aftermath of a disaster, the ability to reliably communicate and coordinate emergency
response could make a meaningful difference in the number of lives saved or lost. However …
response could make a meaningful difference in the number of lives saved or lost. However …
Autonomous UAV positioning using multi-agent reinforcement learning with decentralized swarms
Y Chen - 2023 - ideals.illinois.edu
The rapid development of unmanned aerial vehicles (UAVs) has aroused public attentions,
as the versatility of UAVs allows it to be easily adapted for various activities. In recent years …
as the versatility of UAVs allows it to be easily adapted for various activities. In recent years …
Intelligent positioning of UAVs for future cellular networks
One of the most promising paradigms for the fifth generation of cellular systems (5G) is the
concept of self-organizing networks (SON)[1]. SON consist of the network monitoring its own …
concept of self-organizing networks (SON)[1]. SON consist of the network monitoring its own …
Optimum aerial base station deployment for UAV networks: A reinforcement learning approach
MC Hou, DJ Deng, CL Wu - 2019 IEEE Globecom Workshops …, 2019 - ieeexplore.ieee.org
The boom of unmanned aerial vehicles (UAVs) is projected to fundamentally shift paradigms
of transportations, logistics, agricultures, and public safety as a dominating unmanned …
of transportations, logistics, agricultures, and public safety as a dominating unmanned …
Performance Enhancement of Aerial Base Stations via Reinforcement Learning-based 3D Placement Techniques
N Parvaresh - 2022 - ruor.uottawa.ca
Deploying unmanned aerial vehicles (UAVs) as aerial base stations (BSs) in order to assist
terrestrial connectivity, has drawn significant attention in recent years. UAV-BSs can take …
terrestrial connectivity, has drawn significant attention in recent years. UAV-BSs can take …
Machine learning for the dynamic positioning of UAVs for extended connectivity
F Oliveira, M Luís, S Sargento - Sensors, 2021 - mdpi.com
Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for
the military, but also for public and civil purposes. Their versatility provides advantages in …
the military, but also for public and civil purposes. Their versatility provides advantages in …
Autonomous UAV Base Stations for Next Generation Wireless Networks: A Deep Learning Approach
A Murat Demirtas, M Saygin Seyfioglu… - arXiv e …, 2021 - ui.adsabs.harvard.edu
To address the ever-growing connectivity demands of wireless communications, the
adoption of ingenious solutions, such as Unmanned Aerial Vehicles (UAVs) as mobile Base …
adoption of ingenious solutions, such as Unmanned Aerial Vehicles (UAVs) as mobile Base …
MPRdeep: multi-objective joint optimal node positioning and resource allocation for FANETs with deep reinforcement learning
This paper addresses the problem of UAV positioning and resource allocation under
dynamic network conditions and under instantaneous communication demands in FANETs …
dynamic network conditions and under instantaneous communication demands in FANETs …