Research on optical interconnection system employing deep learning assisted LDPC coding

Jiafei Fan; Wenhao Lei; Ran An; Jichen He; Lin Zhou

doi:10.1117/12.3008180

24 November 2023 Research on optical interconnection system employing deep learning assisted LDPC coding

Jiafei Fan, Wenhao Lei, Ran An, Jichen He, Lin Zhou

Proceedings Volume 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023); 1293552 (2023) https://doi.org/10.1117/12.3008180
Event: Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 2023, Xi’an, China

Abstract

In this paper, an intensity modulation direct detection interconnection system employing modeling-driven neural network (MDNN) assisted low-density parity-check code (LDPC) is proposed and experimentally demonstrated. The weights and biases are utilized to optimize the decoder parameters through model-driven deep learning LDPC decoding processing. Compared with traditional schemes that employ LDPC decoding with high computational complexity and redundancy, the proposed scheme has the advantages of a relatively lower complexity decoder and higher decoding gains. The results show that the MDNN signals can provide a 0.28-dB improvement in receiver power sensitivity and a 46% reduction in complexity in a 10-km IMDD optical four-pulse amplitude modulation interconnection system.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiafei Fan, Wenhao Lei, Ran An, Jichen He, and Lin Zhou "Research on optical interconnection system employing deep learning assisted LDPC coding", Proc. SPIE 12935, Fourteenth International Conference on Information Optics and Photonics (CIOP 2023), 1293552 (24 November 2023); https://doi.org/10.1117/12.3008180

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