Satellite Staring Beam Scheduling Strategy Based on Multi-agent Reinforcement Learning-Reference-Cited by-同舟云学术

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Satellite Staring Beam Scheduling Strategy Based on Multi-agent Reinforcement Learning

Published:2022 Issue: Volume: Page:23-34
ISSN:1867-8211
Container-title:Wireless and Satellite Systems
language:
Short-container-title:

Author:

Zhu Hongtao,Wang Zhenyong,Li Dezhi,Guo Qing

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-93398-2_3

Reference9 articles.

1. Chen, S., Sun, S., Kang, S.: System integration of terrestrial mobile communication and satellite communication - the trends, challenges and key technologies in B5G and 6G. China Commun. 17(12), 156–171 (2020). https://doi.org/10.23919/JCC.2020.12.011

2. Rinaldi, F., et al.: Non-terrestrial networks in 5G beyond: a survey. IEEE Access 8, 165178–165200 (2020). https://doi.org/10.1109/ACCESS.2020.3022981

3. Giordani, M., Zorzi, M.: Non-terrestrial networks in the 6G era: challenges and opportunities. IEEE Netw. 35(2), 244–251 (2021). https://doi.org/10.1109/MNET.011.2000493

4. Restrepo, J., Maral, G.: Cellular geometry for world-wide coverage by non-geo satellites using “earth-fixed cell” technique. In: Proceedings of GLOBECOM 1996. 1996 IEEE Global Telecommunications Conference, vol. 3, pp. 2133–2137 (1996). https://doi.org/10.1109/GLOCOM.1996.592010

5. Wu, Y., Hu, G., Jin, F., Zu, J.: A satellite handover strategy based on the potential game in LEO satellite networks. IEEE Access 7, 133641–133652 (2019). https://doi.org/10.1109/ACCESS.2019.2941217

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