A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning
- DOI
- 10.3390/aerospace13030285
- Published
- 2026-03-18
- Container
- Aerospace
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/aerospace13030285,
title = {A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning},
author = {He Yu and Shengli Li and Junchao Wu and Yanhong Sun and Limin Wang},
year = {2026},
journal = {Aerospace},
doi = {10.3390/aerospace13030285},
url = {https://doi.org/10.3390/aerospace13030285}
}RIS
TY - JOUR TI - A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning AU - He Yu AU - Shengli Li AU - Junchao Wu AU - Yanhong Sun AU - Limin Wang PY - 2026 JO - Aerospace DO - 10.3390/aerospace13030285 UR - https://doi.org/10.3390/aerospace13030285 ER -
APA
Yu, H., Li, S., Wu, J., Sun, Y., & Wang, L. (2026). A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning. Aerospace. https://doi.org/10.3390/aerospace13030285
Source records
- crossref · retrieved 2026-11-09T20:29:33.930Z