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    A new digital post-linearization algorithm improves mobile fronthaul systems using fiber optics and lasers. This blind adaptation method enhances signal quality by reducing interference and error, boosting performance without complex training.

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    Area of Science:

    • Optical Communications
    • Signal Processing
    • Wireless Networks

    Background:

    • Mobile fronthaul systems require efficient signal transmission over fiber optics.
    • Directly modulated lasers (DMLs) are cost-effective but prone to nonlinear distortions.
    • Bandwidth-efficient intermediate frequency-over-fiber (IFoF) technology is crucial for high-capacity mobile networks.

    Purpose of the Study:

    • To propose and demonstrate a novel digital post-linearization algorithm for mobile fronthaul systems.
    • To address nonlinear distortions in systems using DMLs and IFoF technology.
    • To achieve linearization without training signals or prior channel knowledge.

    Main Methods:

    • Development of a digital post-linearization algorithm with blind adaptation capabilities.
    • Utilizing a closed-form solution for estimating optimal linearizer coefficients, enabling non-iterative operation.
    • Experimental setup transmitting multiple 200 MHz 64-QAM OFDM IF signals over a 10 km single-mode fiber link with a DML.

    Main Results:

    • Significant reduction in adjacent channel leakage ratio (ACLR) by over 8 dB.
    • Substantial decrease in error vector magnitude (EVM) by over 10 dB.
    • Increased EVM-compliant input radio frequency (RF) power range by over 9 dB for both single and multiple IF channels.

    Conclusions:

    • The proposed blind digital post-linearization algorithm effectively mitigates nonlinear distortions in mobile fronthaul systems.
    • The algorithm offers a practical and efficient solution for enhancing signal integrity in IFoF systems employing DMLs.
    • Experimental validation confirms the algorithm's performance benefits, including improved ACLR, EVM, and RF power handling.