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Random access protocol learning in LEO satellite networks via reinforcement learning |
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| Author: | Lee, Ju-Hyung1,2; Seo, Hyowoon3; Park, Jihong4; |
| Organizations: |
1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, USA 2Department of Electrical and Computer Engineering, Korea University, Seoul, Korea 3Department of Electronics and Communications Engineering, Kwangwoon University, Seoul, Korea
4School of Information Technology, Deakin University, Geelong, VIC, Australia
5Centre for Wireless Communications, University of Oulu, Oulu, Finland |
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 0.5 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe2023021026808 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2022
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| Publish Date: | 2023-02-10 |
| Description: |
AbstractA mega-constellation of low-altitude earth orbit (LEO) satellites (SATs) are envisaged to provide a global coverage SAT network in beyond fifth-generation (5G) cellular systems. However, such wide coverage rather makes it difficult to apply existing multiple access protocols, such as random access channel (RACH). To overcome this issue, in this paper, we propose a novel random access solution for LEO SAT networks, called as S-RACH. In contrast to existing standardized protocols, S-RACH is a model-free approach using deep reinforcement learning (DRL). Compared to RACH, we show from various simulations that our proposed S-RACH yields around 2x lower average access delay. see all
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| Series: |
IEEE Vehicular Technology Conference |
| ISSN: | 1550-2252 |
| ISSN-E: | 2577-2465 |
| ISSN-L: | 1550-2252 |
| ISBN: | 978-1-6654-8243-1 |
| ISBN Print: | 978-1-6654-8244-8 |
| Article number: | 9860594 |
| DOI: | 10.1109/vtc2022-spring54318.2022.9860594 |
| OADOI: | https://oadoi.org/10.1109/vtc2022-spring54318.2022.9860594 |
| Host publication: |
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring) |
| Conference: |
IEEE Vehicular Technology Conference |
| Type of Publication: |
A4 Article in conference proceedings |
| Field of Science: |
213 Electronic, automation and communications engineering, electronics |
| Subjects: | |
| Funding: |
This research was funded by the National Research Foun-dation of Korea (2022R1A2C2004869). |
| Copyright information: |
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