Noise Loading Analysis using Volterra Kernels to Characterize Fiber Nonlinearities
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초록
We derive analytical expressions for the output spectral density and the noise power Pβ in noise loading analysis using Volterra kernels to characterize fiber nonlinearities. The bandwidth of the input noise source has little effect on Pβ, but the power of the input noise source and the dispersion parameter value of the fiber have a significant effect on Pβ. The Volterra method predicts = 30 dB/decade, which agrees very accurately over a wide range of fiber parameters compared with the numerical results by the split-step Fourier method. Therefore the Volterra method could be useful to predict the performance of a dense WDM system when we plan to upgrade fiber or increase signal power.
Abstract
We derive analytical expressions for the output spectral density and the noise power Pβ in noise loading analysis using Volterra kernels to characterize fiber nonlinearities. The bandwidth of the input noise source has little effect on Pβ, but the power of the input noise source and the dispersion parameter value of the fiber have a significant effect on Pβ. The Volterra method predicts = 30 dB/decade, which agrees very accurately over a wide range of fiber parameters compared with the numerical results by the split-step Fourier method. Therefore the Volterra method could be useful to predict the performance of a dense WDM system when we plan to upgrade fiber or increase signal power.
참고문헌 (11)
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