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Cooperative Downloading for LEO Satellite Networks: A DRL-Based Approach
Hongrok Choi,
Sangheon Pack
School of Electrical Engineering
Research output
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Contribution to journal
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Article
›
peer-review
4
Citations (Scopus)
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Dive into the research topics of 'Cooperative Downloading for LEO Satellite Networks: A DRL-Based Approach'. Together they form a unique fingerprint.
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Keyphrases
Learning-based
100%
Deep Reinforcement Learning (deep RL)
100%
Cooperative Downloading
100%
Low Earth Orbit Satellite Networks
100%
Low Earth Orbit Satellites
66%
Neural Network
33%
Contact Time
33%
Network Layer
33%
High Mobility
33%
Discretized
33%
Ground Station
33%
Evaluation Results
33%
Satellite-based
33%
Remote Sensing
33%
Satellite Network
33%
Offloading Scheme
33%
Fully Connected Layer
33%
Latent Feature
33%
Action Space
33%
Remote Surveillance
33%
Graph Attention Network
33%
Deep Reinforcement Learning Algorithm
33%
Satellite Communication Link
33%
Average Utilization
33%
Soft Actor-critic
33%
Markov Decision Problem
33%
Inter-satellite Communication
33%
Computer Science
Deep Reinforcement Learning
100%
Satellite Network
100%
Network Layer
25%
Neural Network
25%
Evaluation Result
25%
Satellite Communication Network
25%
Collected Data
25%
Reinforcement Learning
25%
Attention (Machine Learning)
25%
Communication Link
25%
Decision Problem
25%
Average Utilization
25%
Fully Connected Layer
25%
Biochemistry, Genetics and Molecular Biology
Contact Time
100%
Remote Sensing
100%