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Deep Reinforcement Learning-Based Routing for Space-Terrestrial Networks
Kai Chu Tsai
*
, Ting Jui Yao
, Pin Hao Huang
, Cheng Sen Huang
, Zhu Han
,
Li Chun Wang
*
此作品的通信作者
電機工程學系
開源智能聯網研究中心
研究成果
:
Conference contribution
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同行評審
5
引文 斯高帕斯(Scopus)
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Keyphrases
Base Station
100%
Deep Reinforcement Learning (deep RL)
100%
Reinforcement Learning-based Routing
100%
Space-terrestrial Networks
100%
Satellite Constellation
100%
Well-defined
50%
World Wide Web
50%
Mathematical Analysis
50%
Mobile Devices
50%
Satellite Communication
50%
Transmission Delay
50%
Routing Algorithm
50%
Coverage Area
50%
Time Algorithm
50%
Downlink Transmission
50%
Uplink Transmission
50%
Wireless Systems
50%
Minimal Delay
50%
Dynamic Topology
50%
Functional Spaces
50%
Actual Situation
50%
Satellite Network
50%
Starlink
50%
Satellite Target
50%
Terrestrial Transmission
50%
Computer Science
Deep Reinforcement Learning
100%
Terrestrial Network
100%
Transmission Delay
50%
Routing Algorithm
50%
Coverage Area
50%
Downlink Transmission
50%
Uplink Transmission
50%
Wireless System
50%
Satellite Communication Network
50%
Dynamic Topology
50%
Academic Institution
50%
Actual Situation
50%
Target Satellite
50%
Functional Space
50%
Amino Acid Sequence
50%
Satellite Network
50%
Mobile Device
50%
Physics
Satellite Communication
100%
Satellite Network
100%