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 …
the wide coverage ability. Composed of geosynchronous orbit (GEO), medium earth orbit …
The next generation heterogeneous satellite communication networks: Integration of resource management and deep reinforcement learning
This article proposes an innovative resource management framework for the next generation
heterogeneous satellite networks (HSNs), which can achieve cooperation between …
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 …
sparse. Mobile networks begin to establish a separate cluster attributable to the limited …
Deep Q-learning aided networking, caching, and computing resources allocation in software-defined satellite-terrestrial networks
With the development of satellite networks, there is an emerging trend to integrate satellite
networks with terrestrial networks, called satellite-terrestrial networks (STNs). The …
networks with terrestrial networks, called satellite-terrestrial networks (STNs). The …
Mission planning for Earth observation satellite with competitive learning strategy
Y Liu, Q Chen, C Li, F Wang - Aerospace Science and Technology, 2021 - Elsevier
In this paper, we studied mission planning problem for Earth observation satellites using a
competitive learning strategy. In particular, a scheme based on Q-network is proposed to …
competitive learning strategy. In particular, a scheme based on Q-network is proposed to …
Time-expanded graph-based resource allocation over the satellite networks
In this letter, we propose a transceiver resource allocation scheme based on the time-
expanded graph (TEG) for the satellite networks. Due to the time-varying topology of the …
expanded graph (TEG) for the satellite networks. Due to the time-varying topology of the …
Machine learning-based resource allocation in satellite networks supporting internet of remote things
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 …
Internet of remote things (IoRT) due to their advantages of wide coverage and high …
Toward optimized traffic distribution for efficient network capacity utilization in two-layered satellite networks
H Nishiyama, Y Tada, N Kato… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
A multi-layered satellite network (MLSN) appears to be a promising network for providing
global ubiquitous broadband communication. To utilize the abundant network resources of …
global ubiquitous broadband communication. To utilize the abundant network resources of …
Joint user association, power optimization and trajectory control in an integrated satellite-aerial-terrestrial network
Internet-of-Things (IoT) is being widely embraced with the number of connected devices
growing rapidly. Moreover, IoT applications are emerging in diverse verticals such as …
growing rapidly. Moreover, IoT applications are emerging in diverse verticals such as …
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 …
communication in future mobile communication networks, where terrestrial users can be …