A deep reinforcement learning-based dynamic traffic offloading in space-air-ground integrated networks (SAGIN)
Space-Air-Ground Integrated Networks (SAGIN) is considered as the key structure of the
next generation network. The space satellites and air nodes are the potential candidates to …
next generation network. The space satellites and air nodes are the potential candidates to …
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 …
Federated learning for intelligent transmission with space-air-ground integrated network toward 6G
The future intelligent devices requires ultra-low communication delay and high QoS
requirement for the following beyond-5G network. Space-air-ground Integrated Network …
requirement for the following beyond-5G network. Space-air-ground Integrated Network …
Optimizing space-air-ground integrated networks by artificial intelligence
It is widely acknowledged that the development of traditional terrestrial communication
technologies cannot provide all users with fair and high quality services due to scarce …
technologies cannot provide all users with fair and high quality services due to scarce …
Incorporating distributed DRL into storage resource optimization of space-air-ground integrated wireless communication network
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The
effective management of SAGIN resources is a prerequisite for high-reliability …
effective management of SAGIN resources is a prerequisite for high-reliability …
Space-air-ground integrated multi-domain network resource orchestration based on virtual network architecture: A DRL method
P Zhang, C Wang, N Kumar… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traditional ground wireless communication networks cannot provide high-quality services
for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due …
for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due …
Latency-aware offloading in integrated satellite terrestrial networks
Next-generation communication networks are expected to integrate newly-used
technologies in a smart way to ensure continuous connectivity in rural areas and to alleviate …
technologies in a smart way to ensure continuous connectivity in rural areas and to alleviate …
Deep reinforcement learning-based task offloading in satellite-terrestrial edge computing networks
D Zhu, H Liu, T Li, J Sun, J Liang… - 2021 IEEE Wireless …, 2021 - ieeexplore.ieee.org
In remote regions (eg, mountain and desert), cellular networks are usually sparsely
deployed or unavailable. With the appearance of new applications (eg, industrial automation …
deployed or unavailable. With the appearance of new applications (eg, industrial automation …
A deep reinforcement learning based approach for cost-and energy-aware multi-flow mobile data offloading
With the rapid increase in demand for mobile data, mobile network operators are trying to
expand wireless network capacity by deploying wireless local area network (LAN) hotspots …
expand wireless network capacity by deploying wireless local area network (LAN) hotspots …
Two-timescale learning-based task offloading for remote IoT in integrated satellite–terrestrial networks
In this article, we propose an integrated satellite–terrestrial network (ISTN) architecture to
support delay-sensitive task offloading for remote Internet of Things (IoT), in which satellite …
support delay-sensitive task offloading for remote Internet of Things (IoT), in which satellite …
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