Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis

Zheng Gao; Ting Jiang; Mingming Zhang; Hao Wu; Ming Tang

doi:10.1038/s41377-024-01726-5

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Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis

Original Articles

- Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis
- Light: Science & Applications Vol. 14, Issue 2, Pages: 531-540(2025)
- Affiliations：
  
  Wuhan National Laboratory for Optoelectronics, Next Generation Internet Access National Engineering Laboratory, and Hubei Optics Valley Laboratory, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
- Author bio：
  
  Hao Wu (wuhaoboom@hust.edu.cn)
  Ming Tang (tangming@mail.hust.edu.cn)
- Funds：
- DOI：10.1038/s41377-024-01726-5
  CLC：
- Received：26 August 2024，
  
  Revised：09 December 2024，
  
  Accepted：2024-12-17，
  
  Published Online：23 January 2025，
  
  Published：28 February 2025
- Accepted：
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Gao, Z. et al. Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis. Light: Science & Applications, 14, 531-540 (2025).
DOI：

Gao, Z. et al. Optical semantic communication through multimode fiber: from symbol transmission to sentiment analysis. Light: Science & Applications, 14, 531-540 (2025). DOI： 10.1038/s41377-024-01726-5.

摘要

Abstract

We propose and validate a novel optical semantic transmission scheme using multimode fiber (MMF). By leveraging the frequency sensitivity of intermodal dispersion in MMFs

we achieve high-dimensional semantic encoding and decoding in the frequency domain. Our system maps symbols to 128 distinct frequencies spaced at 600 kHz intervals

demonstrating a seven-fold increase in capacity compared to conventional communication encoding. We further enhance spectral efficiency by implementing 4-level pulse amplitude modulation (PAM-4)

achieving 9.12 bits/s/Hz without decoding errors. Additionally

we explore the application of this system for sentiment analysis using the IMDb movie review dataset. By encoding semantically similar symbols to adjacent frequencies

the system’s noise tolerance is effectively improved

facilitating accurate sentiment analysis. This work highlights the potential of MMF-based semantic communication to enhance both capacity and robustness in optical communication systems

offering promising applications in bandwidth-constrained and noisy environments.

关键词

Keywords

references

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