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A Dynamic Allocation Algorithm of Satellite Channels Based on Deep Reinforcement Learning
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    Abstract:

    In satellite communication systems, frequencies and channels are very rare resources. How to use reliable and efficient methods to develop resources has become a severe problem that needs to be solved urgently. This paper proposes a dynamic satellite channels allocation algorithm DRLDCA. This algorithm is to model satellite and environment interaction on a Markov decision making process, improving satellite decision making ability through environmental feedback, realizing efficient response to user business requests, improving the service quality of satellite communication, and reducing the probability of communication blocking. The simulation analysis shows that the proposed algorithm can effectively improve the communication throughput and reduce the communication blocking rate.

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  • Received:
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  • Online: May 20,2022
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