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arXiv · 2205.11284

Few-bit Quantization of Neural Networks for Nonlinearity Mitigation in a Fiber Transmission Experiment

Jamal Darweesh·Nelson Costa·Antonio Napoli·Bernhard Spinnler·Yves Jaouen·Mansoor Yousefi·.
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Abstract

A neural network is quantized for the mitigation of nonlinear and components distortions in a 16-QAM 9x50km dual-polarization fiber transmission experiment. Post-training additive power-of-two quantization at 6 bits incurs a negligible Q-factor penalty. At 5 bits, the model size is reduced by 85%, with 0.8 dB penalty.

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Jamal Darweesh, Nelson Costa, Antonio Napoli, Bernhard Spinnler, Yves Jaouen, Mansoor Yousefi, .. 2022-05-23. Few-bit Quantization of Neural Networks for Nonlinearity Mitigation in a Fiber Transmission Experiment. https://arxiv.org/abs/2205.11284

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