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Optical performance monitoring using artificial neural networks trained with empirical moments of asynchronously sampled signal amplitudes

机译:使用人工神经网络进行光学性能监控,该人工神经网络经过异步采样信号幅度的经验矩训练

摘要

We propose a low-cost technique for simultaneous and independent optical signal-to-noise ratio (OSNR), chromatic dispersion (CD), and polarization-mode dispersion (PMD) monitoring in 40/56-Gb/s return-to-zero differential quadrature phase-shift keying (RZ-DQPSK) and 40-Gb/s RZ-DPSK systems, using artificial neural networks (ANN) trained with empirical moments of asynchronously sampled signal amplitudes. The proposed technique employs an extremely simple hardware and digital signal processing to enable multi-impairment monitoring at different data rates and for various modulation formats without necessitating hardware changes. Simulation results demonstrate wide dynamic ranges and good monitoring accuracies.
机译:我们提出了一种低成本技术,用于在40 / 56-Gb / s归零时同时并独立地进行光信噪比(OSNR),色散(CD)和偏振模色散(PMD)监控差分正交相移键控(RZ-DQPSK)和40 Gb / s RZ-DPSK系统,使用经过人工神经网络(ANN)训练的异步采样信号幅度的经验矩进行训练。所提出的技术采用了极其简单的硬件和数字信号处理,从而能够在不同的数据速率和各种调制格式下进行多损害监测,而无需更改硬件。仿真结果证明了宽动态范围和良好的监视精度。

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