Joint network control and resource allocation for space-terrestrial integrated network through hierarchal deep actor-critic reinforcement learning

HA Shah, L Zhao, IM Kim - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
Conventional approaches to network control and resource allocation by allocating dedicated
spectrum resources and separate infrastructure for massive Internet of Things (IoT) network …

Deep dyna-reinforcement learning based on random access control in LEO satellite IoT networks

X Liu, H Zhang, K Long, A Nallanathan… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Random access schemes in satellite Internet-of-Things (IoT) networks are being considered
a key technology of new-type machine-to-machine (M2M) communications. However, the …

Machine learning-based resource allocation in satellite networks supporting internet of remote things

D Zhou, M Sheng, Y Wang, J Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Satellite networks have been regarded as a promising architecture for supporting the
Internet of remote things (IoRT) due to their advantages of wide coverage and high …

Distributed deep reinforcement learning assisted resource allocation algorithm for space-air-ground integrated networks

P Zhang, Y Li, N Kumar, N Chen… - … on Network and …, 2022 - ieeexplore.ieee.org
To realize the Interconnection of Everything (IoE) in the 6G vision, the space-based, air-
based, and ground-based networks have shown a trend of integration. Compared with the …

Hypergraph Based Resource-Efficient Collaborative Reinforcement Learning for B5G Massive IoT

F Yang, C Yang, J Huang, K Yu, S Garg… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Beyond 5G (B5G) networks rapidly growing to connect billions of Internet of Things (IoT)
devices and the dense deployment of IoT devices leads the large-scale network conflict and …

Multi-Agent Reinforcement Learning-Based Resource Allocation Scheme for UAV-Assisted Internet of Remote Things Systems

D Lee, YG Sun, SH Kim, JH Kim, Y Shin, DI Kim… - IEEE …, 2023 - ieeexplore.ieee.org
Multi-layered communication networks including satellites and unmanned aerial vehicles
(UAVs) with remote sensing capability are expected to be an essential part of next …

Artificial intelligence enabled Internet of Things: Network architecture and spectrum access

H Song, J Bai, Y Yi, J Wu, L Liu - IEEE Computational …, 2020 - ieeexplore.ieee.org
The explosive growth of wireless devices motivates the development of the internet-of-things
(IoT), which is capable of interconnecting massive and diverse" things" via wireless …

Resource allocation for multi-UAV assisted IoT networks: A deep reinforcement learning approach

YY Munaye, RT Juang, HP Lin… - … on Pervasive Artificial …, 2020 - ieeexplore.ieee.org
The wireless communication system for the massively heterogeneous Internet of Things
(IoT) network hinders the allocation of resources. For this study, an unmanned aerial vehicle …

[HTML][HTML] Multi-agent deep reinforcement learning for user association and resource allocation in integrated terrestrial and non-terrestrial networks

DJ Birabwa, D Ramotsoela, N Ventura - Computer Networks, 2023 - Elsevier
Integrating the terrestrial network with non-terrestrial networks to provide radio access as
anticipated in the beyond 5G networks calls for efficient user association and resource …

Aoi-aware joint spectrum and power allocation for internet of vehicles: A trust region policy optimization-based approach

N Peng, Y Lin, Y Zhang, J Li - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
In Internet of Vehicles (IoV), information freshness is a significant indicator to indemnify road
traffic safety, which is measured by Age of Information (AoI). In this article, we consider the …