The next generation heterogeneous satellite communication networks: Integration of resource management and deep reinforcement learning

B Deng, C Jiang, H Yao, S Guo… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
This article proposes an innovative resource management framework for the next generation
heterogeneous satellite networks (HSNs), which can achieve cooperation between …

Multi-agent deep reinforcement learning-based flexible satellite payload for mobile terminals

X Hu, X Liao, Z Liu, S Liu, X Ding… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Information dissemination in mobile networks turns out to be a problem when the network is
sparse. Mobile networks begin to establish a separate cluster attributable to the limited …

Multi-agent drl for resource allocation and cache design in terrestrial-satellite networks

X Li, H Zhang, H Zhou, N Wang, K Long… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
In the past few years, satellite communications have greatly affected our daily lives, and the
integrated terrestrial-satellite network can combine the advantages of satellite and base …

Distributed intelligence: A verification for multi-agent DRL-based multibeam satellite resource allocation

X Liao, X Hu, Z Liu, S Ma, L Xu, X Li… - IEEE …, 2020 - ieeexplore.ieee.org
Centralized radio resource management method puts all of the computational burdens in an
agent, which is unbearable with the increasing of data dimensionality. This letter focuses on …

Cooperative multi-agent deep reinforcement learning for resource management in full flexible VHTS systems

FG Ortiz-Gomez, D Tarchi, R Martínez… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Very high throughput satellite (VHTS) systems are expected to have a huge increase in
traffic demand in the near future. Nevertheless, this increase will not be uniform over the …

Reinforcement learning based capacity management in multi-layer satellite networks

C Jiang, X Zhu - IEEE Transactions on Wireless …, 2020 - ieeexplore.ieee.org
The development of satellite networks is drawing much more attention in recent years due to
the wide coverage ability. Composed of geosynchronous orbit (GEO), medium earth orbit …

Deep Q-learning aided networking, caching, and computing resources allocation in software-defined satellite-terrestrial networks

C Qiu, H Yao, FR Yu, F Xu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
With the development of satellite networks, there is an emerging trend to integrate satellite
networks with terrestrial networks, called satellite-terrestrial networks (STNs). 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 …

Dynamically adaptive cooperation transmission among satellite-ground integrated networks

F Tang - IEEE INFOCOM 2020-IEEE Conference on Computer …, 2020 - ieeexplore.ieee.org
It is a desirable goal to fuse satellite and ground integrated networks (SGINs) to improve the
resource utilization efficiency. However, existing work did not consider how to integrate them …

Load-aware satellite handover strategy based on multi-agent reinforcement learning

S He, T Wang, S Wang - GLOBECOM 2020-2020 IEEE Global …, 2020 - ieeexplore.ieee.org
Low Earth orbit (LEO) satellites play an important role to realize personal global
communication in future mobile communication networks, where terrestrial users can be …