A deep reinforcement learning based approach for energy-efficient channel allocation in satellite Internet of Things
B Zhao, J Liu, Z Wei, I You - IEEE Access, 2020 - ieeexplore.ieee.org
Recently, Satellite Internet of Things (SIoT), a space network that consists of numerous Low
Earth Orbit (LEO) satellites, is regarded as a promising technique since it is the only solution …
Earth Orbit (LEO) satellites, is regarded as a promising technique since it is the only solution …
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 …
resource allocation of Satellite Internet of Things (S-IoT). This paper presents a deep …
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 …
Intelligent channel prediction and power adaptation in leo constellation for 6g
Integrated satellite and terrestrial networks (ISTN) are rapidly evolving to meet the ever-
increasing demands of higher throughput, lower latency, and wider coverage for future …
increasing demands of higher throughput, lower latency, and wider coverage for future …
Deep reinforcement learning architecture for continuous power allocation in high throughput satellites
In the coming years, the satellite broadband market will experience significant increases in
the service demand, especially for the mobility sector, where demand is burstier. Many of the …
the service demand, especially for the mobility sector, where demand is burstier. Many of the …
Distributed deep reinforcement learning assisted resource allocation algorithm for space-air-ground integrated networks
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 …
based, and ground-based networks have shown a trend of integration. Compared with the …
Deep reinforcement learning for channel and power allocation in UAV-enabled IoT systems
Unmanned aerial vehicles (UAVs) have recently been proposed as moving base stations to
collect data from ground IoT nodes in remote areas. Since IoT nodes are normally battery …
collect data from ground IoT nodes in remote areas. Since IoT nodes are normally battery …
Latency optimization for hybrid GEO–LEO satellite-assisted IoT networks
Benefiting from the development of satellite on-board processing capability, the orbital
computing can be realized by deploying edge computing servers on satellites to reduce the …
computing can be realized by deploying edge computing servers on satellites to reduce the …
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 …
Deep reinforcement learning based dynamic channel allocation algorithm in multibeam satellite systems
S Liu, X Hu, W Wang - IEEE Access, 2018 - ieeexplore.ieee.org
Dynamic channel allocation (DCA) is the key technology to efficiently utilize the spectrum
resources and decrease the co-channel interference for multibeam satellite systems. Most …
resources and decrease the co-channel interference for multibeam satellite systems. Most …