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We introduce neural probabilistic amplitude shaping, a joint-distribution learning framework for coherent fiber systems. The proposed scheme provides a 0.5 dB signal-to-noise ratio gain over sequence selection for dual-polarized 64-QAM transmission across a single-span 205 km link.
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@article{askari2026neural,
title = {Neural Probabilistic Amplitude Shaping for Nonlinear Fiber Channels},
author = {Mohammad Taha Askari and Lutz Lampe and Amirhossein Ghazisaeidi},
year = {2026},
eprint = {2602.02716},
archivePrefix = {arXiv},
url = {http://arxiv.org/abs/2602.02716v1}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/2602.02716)