Machine learning for radio resource management in multibeam GEO satellite systems
Satellite communications (SatComs) systems are facing a massive increase in traffic
demand. However, this increase is not uniform across the service area due to the uneven …
demand. However, this increase is not uniform across the service area due to the uneven …
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 …
agent, which is unbearable with the increasing of data dimensionality. This letter focuses on …
Edge intelligence assisted resource management for satellite communication
Satellite communication has been seen as a vital part of the sixth generation
communication, which greatly extends network coverage. In satellite communication …
communication, which greatly extends network coverage. In satellite communication …
Cooperative multi-agent deep reinforcement learning for resource management in full flexible VHTS systems
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 …
traffic demand in the near future. Nevertheless, this increase will not be uniform over the …
Convolutional neural networks for flexible payload management in VHTS systems
Very high throughput satellite (VHTS) systems are expected to have a large increase in
traffic demand in the near future. However, this increase will not be uniform throughout the …
traffic demand in the near future. However, this increase will not be uniform throughout the …
A novel deep reinforcement learning architecture for dynamic power and bandwidth allocation in multibeam satellites
J Xu, Z Zhao, L Wang, Y Zhang - Acta Astronautica, 2023 - Elsevier
Due to the explosive growth and dynamic change of user demand, an efficient power and
bandwidth allocation algorithm is quite essential for multibeam satellites with flexible digital …
bandwidth allocation algorithm is quite essential for multibeam satellites with flexible digital …
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 …
sparse. Mobile networks begin to establish a separate cluster attributable to the limited …
Sequential dynamic resource allocation in multi-beam satellite systems: A learning-based optimization method
Y Huang, WU Shufan, Z Zhankui, K Zeyu… - Chinese Journal of …, 2023 - Elsevier
Multi-beam antenna and beam hopping technologies are an effective solution for scarce
satellite frequency resources. One of the primary challenges accompanying with Multi-Beam …
satellite frequency resources. One of the primary challenges accompanying with Multi-Beam …
Artificial intelligence algorithms for power allocation in high throughput satellites: A comparison
Automating resource management strategies is a key priority in the satellite communications
industry. The future landscape of the market will be changed by a substantial increase of …
industry. The future landscape of the market will be changed by a substantial increase of …
A deep reinforcement learning-based framework for dynamic resource allocation in multibeam satellite systems
X Hu, S Liu, R Chen, W Wang… - IEEE Communications …, 2018 - ieeexplore.ieee.org
Dynamic resource allocation (DRA) is the key technology to improve the network
performance in resource-limited multibeam satellite (MBS) systems. The aim is to find a …
performance in resource-limited multibeam satellite (MBS) systems. The aim is to find a …