Deep Neural Network Assisted Second-Order Perturbation-Based Nonlinearity Compensation
O. S. Sunish Kumar, Lutz Lampe, Shenghang Luo, Mrinmoy Jana, Jeebak, Mitra, and Chuandong Li
TL;DR
This paper introduces a novel nonlinearity compensation method for fiber-optic communication using deep neural networks combined with second-order perturbation theory, significantly improving signal quality over long distances.
Contribution
It presents a new fiber nonlinearity post-compensation technique that integrates DNNs with second-order perturbation theory, achieving notable performance gains.
Findings
1 dB Q-factor improvement at 1200 km for 32 Gbaud PDM-64-QAM
Effective nonlinear compensation surpassing linear dispersion methods
Potential for enhanced long-distance optical communication
Abstract
We propose a fiber nonlinearity post-compensation technique using the DNN and the second-order perturbation theory. We achieve 1 dB Q-factor improvement for a 32 Gbaud PDM-64-QAM at 1200 km compared to the linear dispersion compensation.
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Taxonomy
TopicsOptical Network Technologies · Advanced Fiber Laser Technologies · Advanced Photonic Communication Systems