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Related Experiment Video

Updated: Jan 7, 2026

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

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Lightweight scale-enhanced neural network-based optimized detection for bandwidth-limited IM/DD systems.

Fei Xie, Hao Zhou, Yingjie Jiang

    Optics Letters
    |December 24, 2025
    PubMed
    Summary

    A new lightweight neural network detection scheme significantly enhances receiver sensitivity and slashes computational complexity in optical communication systems. This optimized detection improves performance in bandwidth-limited intensity modulation and direct detection systems.

    Related Experiment Videos

    Last Updated: Jan 7, 2026

    Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
    09:44

    Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

    Published on: March 8, 2024

    5.7K

    Area of Science:

    • Optical Communications
    • Digital Signal Processing
    • Machine Learning in Communications

    Background:

    • Bandwidth-limited Intensity Modulation and Direct Detection (IM/DD) systems face challenges in receiver digital signal processing (DSP).
    • Conventional optimized detection schemes often exhibit high computational complexity.
    • Efficient receiver design is crucial for next-generation high-speed optical networks.

    Purpose of the Study:

    • To propose and evaluate a lightweight and efficient optimized detection scheme for IM/DD systems.
    • To leverage a lightweight scale-enhanced neural network (LSE-NN) for improved receiver performance.
    • To reduce computational complexity in receiver DSP.

    Main Methods:

    • Developed a novel LSE-NN-based detection scheme.
    • Incorporated input preprocessing with 2-tap scale-enhanced low-pass filtering.
    • Utilized a neural network-based lookup table (NN-LUT) and a neural network-based log-maximum a posteriori (MAP) decoder (NN-MAP).
    • Implemented and tested the scheme in a 122-Gbps optical IM/DD system with 4-level pulse amplitude modulation (PAM-4) over 2 km.

    Main Results:

    • The LSE-NN-MAP scheme achieved a 2.4 dB improvement in receiver sensitivity.
    • Computational complexity was reduced by over 98.44% compared to conventional methods.
    • The system successfully met the 7% forward error correction (FEC) threshold.

    Conclusions:

    • The proposed LSE-NN-MAP scheme offers a lightweight and efficient solution for optimized detection in IM/DD systems.
    • This demonstrates the first application of a lightweight neural network architecture for optimized detection in IM/DD systems.
    • The results highlight the potential of neural network-based DSP for enhancing optical communication performance.