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    Area of Science:

    • Optical Communications
    • Nonlinear Fiber Optics
    • Signal Processing

    Background:

    • Fiber-optic communications face limitations due to signal nonlinearity.
    • Polarization division multiplexing (PDM) is a key technique for increasing data rates.
    • The Manakov equation models dual-polarization signal propagation in single-mode fibers.

    Purpose of the Study:

    • To evaluate PDM nonlinear inverse synthesis transmission schemes for reduced nonlinearity impact.
    • To generalize nonlinear Fourier transform (NFT) algorithms for multicomponent systems.
    • To introduce a novel, reduced-complexity dual-polarization transmission scheme.

    Main Methods:

    • Exploiting the integrability of the Manakov equation.
    • Employing nonlinear Fourier transform (NFT) based signal processing.
    • Generalizing NFT computation algorithms for two- and multicomponent cases.

    Main Results:

    • Demonstrated doubling of channel information rate by modulating information on both polarizations.
    • Achieved negligible performance degradation with dual-polarization modulation.
    • Introduced a novel scheme with separate polarization processing, showing performance improvements in practical scenarios.

    Conclusions:

    • PDM nonlinear inverse synthesis with NFT offers a promising approach for high-capacity fiber-optic communications.
    • The proposed scheme effectively mitigates nonlinearity and enhances spectral efficiency.
    • The developed techniques pave the way for more efficient and robust optical transmission systems.