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Statistical quantification of nonlinear interference noise components in coherent systems.

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    We developed a new statistical method to separate nonlinear interference noise (NLIN) into residual Gaussian (ResN) and phase noise (NLPN) components. This accurately predicts post-digital signal processing (DSP) transmission performance, considering carrier phase recovery (CPR).

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    Area of Science:

    • Optical Communications
    • Signal Processing
    • Statistical Modeling

    Background:

    • Nonlinear interference noise (NLIN) significantly impacts optical transmission performance.
    • Accurate prediction of post-digital signal processing (DSP) performance is crucial for system design.
    • Carrier phase recovery (CPR) is a key DSP component affected by NLIN.

    Purpose of the Study:

    • To present and validate a statistical method for separating NLIN into residual Gaussian (ResN) and nonlinear phase noise (NLPN) components.
    • To account for the interaction between NLIN and receiver DSP, specifically CPR.
    • To enable accurate prediction of achievable post-DSP transmission performance.

    Main Methods:

    • A novel statistical method is introduced to decompose NLIN.
    • The method incorporates the correlation of the NLPN component to model its interaction with CPR.
    • Simulations are conducted using various quadrature amplitude modulation (QAM) and probabilistically shaped (PS) formats over standard single mode fiber (SSMF) and dispersion shifted fiber (DSF).

    Main Results:

    • The proposed method accurately predicts post-DSP transmission performance across different modulation formats and fiber types.
    • Validation is achieved by comparing results with ideal data-aided CPR and blind phase search (BPS) algorithms.
    • Discrepancies between the new method and existing theoretical models are identified and discussed.

    Conclusions:

    • The developed statistical method provides a straightforward and accurate way to predict transmission performance under NLIN.
    • The approach effectively models the impact of NLIN on CPR, leading to improved prediction accuracy.
    • This method offers a valuable tool for optimizing optical communication system design.