文章基本信息

标题：Neural Network Equalizer in Visible Light Communication: State of the Art and Future Trends
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作者：Jianyang Shi ; Jianyang Shi ; Ouhan Huang 等
期刊名称：Frontiers in Communications and Networks
电子版ISSN：2673-530X
出版年度：2022
卷号：3
DOI：10.3389/frcmn.2022.824593
语种：English
出版社：Frontiers Media S.A.
摘要：As 6G research progresses, both visible light communication (VLC) and artificial intelligence (AI) become important components, which makes them appear to converge. Neural networks (NN) as equalizers are gradually occupying an increasingly important position in the research of the physical layer of VLC, especially in nonlinear compensation. In this paper, we will propose three categories of neural network equalizers, including input data reconfiguration NN, network reconfiguration NN and loss function reconfiguration NN. We give the definitions of these three neural networks and their applications in VLC systems. This work allows the reader to have a clearer understanding and future trends of neural networks in visible light communication, especially in terms of equalizers.