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Learning effective nonlinear operator for high speed optical compensation system.

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    Optical communication systems face impairments from linear and nonlinear Kerr effects. A new method, SNSE-DBP, unifies compensation techniques for improved efficiency and reduced computational cost in signal transmission.

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    Area of Science:

    • Optical Communications
    • Digital Signal Processing

    Background:

    • Optical systems suffer signal impairments from linear and nonlinear Kerr effects.
    • Existing compensation methods like post-processing compensation (PPC) and digital back-propagation (DBP) have limitations in accuracy and computational complexity.
    • There is a need for a unified approach to nonlinear compensation that balances performance and cost.

    Purpose of the Study:

    • To introduce a unified framework for nonlinear compensation operators in optical systems.
    • To develop an efficient compensation method that overcomes limitations of current techniques.
    • To present SNSE-DBP as a novel solution for nonlinear compensation.

    Main Methods:

    • The study introduces the Simplified Nonlinear Symbol Equation (SNSE) as a theoretical framework.
    • SNSE is used to develop the SNSE-DBP compensation framework, employing a cross-shaped truncation for nonlinear effects.
    • The SNSE-DBP framework is implemented as a deep neural network for data-driven optimization.

    Main Results:

    • Numerical simulations show SNSE-DBP outperforms PPC and DBP in efficiency.
    • The proposed method offers a unified approach to handling linear and nonlinear impairments.
    • SNSE-DBP demonstrates improved performance compared to existing compensation schemes.

    Conclusions:

    • SNSE-DBP provides an effective and computationally feasible solution for nonlinear compensation in optical communication systems.
    • This work paves the way for more efficient optical communication networks.
    • The unified framework offers a significant advancement in digital signal processing for optical systems.