An Accurate and Realistic Channel Simulator of Optical Wireless Communication Systems Combining Deterministic and Random Noise

Recently, neural networks have gained prominence as potent tools in the realm of channel modeling in optical wireless communication (OWC) systems. However, existing channel networks tend to ignore random intensity noise and phase noise induced by optical sources under spontaneous and excited radiati...

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Veröffentlicht in:	Journal of lightwave technology 2024-04, Vol.42 (8), p.2666-2682
Hauptverfasser:	Wei, Yuan, Chen, Chaoxu, Li, Fujie, Yao, Li, Zhang, Haoyu, Liu, Yinjun, Li, Ziwei, Shen, Chao, Zhang, Junwen, Chi, Nan, Shi, Jianyang
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive optics Algorithms Channel estimation Channel modeling Computer simulation data driven Deep learning Generative adversarial networks Interference Machine learning Modelling neural network Neural networks Noise intensity Nonlinear optics Optical attenuators Optical filters Optical noise Optical variables measurement Optical wireless optical wireless communication Phase noise Random noise Shot noise Wireless communication systems Wireless communications
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