Perturbation-based Sequence Selection for Probabilistic Amplitude Shaping
Mohammad Taha Askari, Lutz Lampe
TL;DR
This paper presents a new sequence selection metric for probabilistic amplitude shaping that improves signal-to-noise ratio in fiber-optic communication systems, achieving significant gains in practical scenarios.
Contribution
The authors introduce a sign-dependent sequence selection metric and a predictive method for SNR gains, enhancing probabilistic amplitude shaping performance.
Findings
0.5 dB SNR gain in 256-QAM transmission
Effective sequence selection metric for fiber-optic links
Simple prediction method for SNR improvements
Abstract
We introduce a practical sign-dependent sequence selection metric for probabilistic amplitude shaping and propose a simple method to predict the gains in signal-to-noise ratio (SNR) for sequence selection. The proposed metric provides a dB SNR gain for single-polarized 256-QAM transmission over a long-haul fiber link.
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Taxonomy
TopicsImage Processing and 3D Reconstruction