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Power allocation in a spatial multiplexing free-space optical system with reinforcement learning
Y. Li; T. Geng; R. Tian and S. Gao
2021
发表期刊Optics Communications
ISSN304018
卷号488
摘要The multiple-input multiple-output (MIMO) technique for free-space optical (FSO) system was initially designed for combating fading events in the diversity mode. However, as people demand for higher throughput, extra freedom can be obtained from the multiple apertures in the spatial multiplexing mode, where the system transmits independent parallel data streams over multiple apertures to increase data rate. In this paper, we study a MIMO FSO system in the multiplexing mode. By maximizing long-term benefits on the average capacity within limited time slots, we propose a power allocation algorithm based on the reinforcement learning (RL) method. Our RL algorithm utilizes an actorcritic structure, where both action space and state space are continuous. We also add the constraints on the peak power and total power. A novel reward function is designed with a punishment item for remaining power. The proposed RL algorithm can achieve a better performance than the existing benchmarks. 2021 Elsevier B.V.
DOI10.1016/j.optcom.2021.126856
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收录类别SCI ; EI
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/65545
专题中国科学院长春光学精密机械与物理研究所
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Y. Li,T. Geng,R. Tian and S. Gao. Power allocation in a spatial multiplexing free-space optical system with reinforcement learning[J]. Optics Communications,2021,488.
APA Y. Li,T. Geng,&R. Tian and S. Gao.(2021).Power allocation in a spatial multiplexing free-space optical system with reinforcement learning.Optics Communications,488.
MLA Y. Li,et al."Power allocation in a spatial multiplexing free-space optical system with reinforcement learning".Optics Communications 488(2021).
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