Survey on Deep Reinforcement Learning Applied for LEO Satellites 


Vol. 48,  No. 2, pp. 196-205, Feb.  2023
10.7840/kics.2023.48.2.196


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  Abstract

With the rapid development of communication technology, research using LEO satellites in next-generation mobile communication is being actively conducted. In LEO satellite communication, complex problems such as resource management or handover occur, so deep reinforcement learning method can fix the problems that were difficult to solve with conventional methods. In this paper, we investigated the cases that applied deep reinforcement learning method in satellite communication. It is largely classified into scheduling problem, resource allocation, user access control, and the other problems.

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[IEEE Style]

H. Lee and J. Kim, "Survey on Deep Reinforcement Learning Applied for LEO Satellites," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 2, pp. 196-205, 2023. DOI: 10.7840/kics.2023.48.2.196.

[ACM Style]

Hyunsoo Lee and Joongheon Kim. 2023. Survey on Deep Reinforcement Learning Applied for LEO Satellites. The Journal of Korean Institute of Communications and Information Sciences, 48, 2, (2023), 196-205. DOI: 10.7840/kics.2023.48.2.196.

[KICS Style]

Hyunsoo Lee and Joongheon Kim, "Survey on Deep Reinforcement Learning Applied for LEO Satellites," The Journal of Korean Institute of Communications and Information Sciences, vol. 48, no. 2, pp. 196-205, 2. 2023. (https://doi.org/10.7840/kics.2023.48.2.196)
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