Learning for Perturbation-Based Fiber Nonlinearity Compensation
2022 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC)(2022)
摘要
Several machine learning inspired methods for perturbation-based fiber nonlinearity (PBNLC) compensation have been presented in recent literature. We critically revisit acclaimed benefits of those over non-learned methods. Numerical results suggest that learned linear processing of perturbation triplets of PB-NLC is preferable over feedforward neural-network solutions.
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关键词
fiber nonlinearity compensation,perturbation-based
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