Evolution of non-terrestrial networks from 5G to 6G: A survey

MM Azari, S Solanki, S Chatzinotas… - … surveys & tutorials, 2022 - ieeexplore.ieee.org
Non-terrestrial networks (NTNs) traditionally have certain limited applications. However, the
recent technological advancements and manufacturing cost reduction opened up myriad …

A comprehensive overview on 5G-and-beyond networks with UAVs: From communications to sensing and intelligence

Q Wu, J Xu, Y Zeng, DWK Ng… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Due to the advancements in cellular technologies and the dense deployment of cellular
infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and …

Applications of artificial intelligence and machine learning in smart cities

Z Ullah, F Al-Turjman, L Mostarda… - Computer Communications, 2020 - Elsevier
Smart cities are aimed to efficiently manage growing urbanization, energy consumption,
maintain a green environment, improve the economic and living standards of their citizens …

Deep reinforcement learning for Internet of Things: A comprehensive survey

W Chen, X Qiu, T Cai, HN Dai… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

Energy efficiency maximization in RIS-assisted SWIPT networks with RSMA: A PPO-based approach

R Zhang, K **ong, Y Lu, P Fan… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
This paper investigates reconfigurable intelligent surface (RIS)-assisted simultaneous
wireless information and power transfer (SWIPT) networks with rate splitting multiple access …

Machine learning empowered trajectory and passive beamforming design in UAV-RIS wireless networks

X Liu, Y Liu, Y Chen - IEEE Journal on Selected Areas in …, 2020 - ieeexplore.ieee.org
A novel framework is proposed for integrating reconfigurable intelligent surfaces (RIS) in
unmanned aerial vehicle (UAV) enabled wireless networks, where an RIS is deployed for …

Multi-agent deep reinforcement learning for multi-robot applications: A survey

J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …

A survey on machine-learning techniques for UAV-based communications

PS Bithas, ET Michailidis, N Nomikos, D Vouyioukas… - Sensors, 2019 - mdpi.com
Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless
communication networks. Their adoption in various communication-based applications is …

Machine learning-aided operations and communications of unmanned aerial vehicles: A contemporary survey

H Kurunathan, H Huang, K Li, W Ni… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …

Multi-objective optimization for UAV-assisted wireless powered IoT networks based on extended DDPG algorithm

Y Yu, J Tang, J Huang, X Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper studies an unmanned aerial vehicle (UAV)-assisted wireless powered IoT
network, where a rotary-wing UAV adopts fly-hover-communicate protocol to successively …