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Article

Neural Network-Based Transceiver Design for VLC System over ISI Channel

National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450000, China
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Author to whom correspondence should be addressed.
Photonics 2022, 9(3), 190; https://doi.org/10.3390/photonics9030190
Submission received: 13 February 2022 / Revised: 11 March 2022 / Accepted: 14 March 2022 / Published: 16 March 2022
(This article belongs to the Special Issue Visible Light Communication (VLC))

Abstract

In this letter, we construct the neural network (NN)-based transceiver to compensate for the varying inter-symbol-interference (ISI) effect in visible light communication (VLC) systems. For processing variable-length sequences, the convolution neural network (CNN) is utilized, and then the residual network structure is further leveraged at the receiver part to enhance the performance. To cope with varying ISI, the pilot sequence, instead of channel side information (CSI) obtained by an additional module, is integrated into the framework to recover the data sequence directly. Simulation results show that the symbol error rate (SER) performance of the proposed NN-based transceiver can outperform separately designed transceiver schemes and approach the ideal perfect CSI (PCSI) case with a few pilot symbols or even no pilot.
Keywords: visible light communication (VLC); neural network (NN); deep learning; autoencoder (AE); transceiver design visible light communication (VLC); neural network (NN); deep learning; autoencoder (AE); transceiver design

Share and Cite

MDPI and ACS Style

Li, L.; Zhu, Z.; Zhang, J. Neural Network-Based Transceiver Design for VLC System over ISI Channel. Photonics 2022, 9, 190. https://doi.org/10.3390/photonics9030190

AMA Style

Li L, Zhu Z, Zhang J. Neural Network-Based Transceiver Design for VLC System over ISI Channel. Photonics. 2022; 9(3):190. https://doi.org/10.3390/photonics9030190

Chicago/Turabian Style

Li, Lin, Zhaorui Zhu, and Jian Zhang. 2022. "Neural Network-Based Transceiver Design for VLC System over ISI Channel" Photonics 9, no. 3: 190. https://doi.org/10.3390/photonics9030190

APA Style

Li, L., Zhu, Z., & Zhang, J. (2022). Neural Network-Based Transceiver Design for VLC System over ISI Channel. Photonics, 9(3), 190. https://doi.org/10.3390/photonics9030190

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