Abstract
Space-Air-Ground Integrated network(SAGIN) is a heterogeneous network which combines ground network, air network and space network. In SAGIN, a sub-network access algorithm based on reinforcement learning is proposed to make full use of multi-dimensional network resources, improve network delay and reduce packet loss rate. The algorithm learns from the environment iteratively and revises the model constantly, so as to make the optimal access choice. In the simulation experiment, the ASA-RL algorithm has obvious improvement over the comparison algorithm in terms of communication delay and packet loss rate.
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