Model-Based Reinforcement Learning for Wireless Channel Access

Jong In Park, Kae Won Choi · 2022 13th International Conference on Information and Communication Technology Convergence (ICTC) · 2022

In this paper, we study a wireless channel access method using model-based reinforcement learning in limited spectral resources. The proposed method maximizes sampling efficiency by learning an environment and using it for actor learning. The environment is a model that considers a dynamic packet queue in a situation where a wireless channel is shared. We show the performance results of the proposed learning algorithm in the considered environment.

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