Optical Semantic Communication through Multimode Fiber: From Symbol Transmission to Sentiment Analysis

TL;DR

This paper introduces a novel optical semantic communication system using multimode fiber that significantly increases capacity and robustness, enabling high-dimensional encoding and sentiment analysis in noisy environments.

Contribution

The work presents a new optical semantic transmission scheme leveraging intermodal dispersion in multimode fibers for high-capacity, noise-tolerant communication and sentiment analysis.

Findings

Seven-fold increase in capacity over conventional methods.

Achieved 9.12 bits/s/Hz spectral efficiency with PAM-4.

Enhanced noise tolerance for sentiment analysis using semantic encoding.

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.