Dynamic resource management in integrated NOMA terrestrial–satellite networks using multi-agent reinforcement learning

A Nauman, HM Alshahrani, N Nemri… - Journal of Network and …, 2024 - Elsevier
The integration of terrestrial and satellite wireless communication networks offers a practical
solution to enhance network coverage, connectivity, and cost-effectiveness. Moreover, in …

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 …

Multi-agent DRL for user association and power control in terrestrial-satellite network

X Li, H Zhang, W Li, K Long - 2021 IEEE global …, 2021 - ieeexplore.ieee.org
In the past few years, satellite communications have greatly affected our daily lives. Because
the resources of terrestrial-satellite network are limited, how to allocate resources of …

[HTML][HTML] Deep reinforcement learning-based resource allocation for satellite internet of things with diverse QoS guarantee

S Tang, Z Pan, G Hu, Y Wu, Y Li - Sensors, 2022 - mdpi.com
Large-scale terminals' various QoS requirements are key challenges confronting the
resource allocation of Satellite Internet of Things (S-IoT). This paper presents a deep …

Multi-Agent DDPG based Resource Allocation in NOMA-enabled Satellite IoT

F Chai, Q Zhang, H Yao, X Xin, F Wang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Due to the scarcity of spectrum resources in Non-orthogonal Multiple Access (NOMA)
systems and insufficient satellite-ground integration in satellite Internet of Things (IoT), this …

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 …

Collaborative Deep Reinforcement Learning for Resource Optimization in Non-Terrestrial Networks

Y Cao, SY Lien, YC Liang, D Niyato… - 2023 IEEE 34th Annual …, 2023 - ieeexplore.ieee.org
Non-terrestrial networks (NTNs) with low-earth orbit (LEO) satellites have been regarded as
promising remedies to support global ubiquitous wireless services. Due to the rapid mobility …

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 …

A self-attention based dynamic resource management for satellite-terrestrial networks

L Tianhao, L Zhiyong - China Communications, 2024 - ieeexplore.ieee.org
The satellite-terrestrial networks possess the ability to transcend geographical constraints
inherent in traditional communication networks, enabling global coverage and offering users …

Deep Reinforcement Learning Based Resource Allocation for RSMA in LEO Satellite-Terrestrial Networks

J Huang, Y Yang, J Lee, D He… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper considers the joint optimization of resource allocation and power control for rate-
splitting multiple access (RSMA) based low earth orbits (LEO) satellite-terrestrial networks …