English

Geometric Constellation Shaping for Phase-noise Channels Using a Differentiable Blind Phase Search

Signal Processing 2022-06-27 v1 Information Theory math.IT
Authors: Andrej Rode , Benedikt Geiger , Laurent Schmalen
View on arXiv ↗ PDF ↗ DOI ↗

Abstract

We perform geometric constellation shaping with optimized bit labeling using a binary autoencoder including a differential blind phase search (BPS). Our approach enables full end-to-end training of optical coherent transceivers taking into account the digital signal processing.

Keywords

image reconstruction

Cite

@article{arxiv.2112.03114,
  title  = {Geometric Constellation Shaping for Phase-noise Channels Using a Differentiable Blind Phase Search},
  author = {Andrej Rode and Benedikt Geiger and Laurent Schmalen},
  journal= {arXiv preprint arXiv:2112.03114},
  year   = {2022}
}

Comments

Submitted to the Optical Fiber Communication Conference (OFC) 2022

Related papers

View all related →
Signal Processing · Electrical Eng. & Systems
End-to-end Optimization of Constellation Shaping for Wiener Phase Noise Channels with a Differentiable Blind Phase Search
Andrej Rode, Benedikt Geiger, Shrinivas Chimmalgi, Laurent Schmalen
2023-04-25
Signal Processing · Electrical Eng. & Systems
Optimization of Geometric Constellation Shaping for Wiener Phase Noise Channels with Varying Channel Parameters
Andrej Rode, Laurent Schmalen
2022-06-30
Information Theory · Computer Science
Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning
Rasmus T. Jones, Tobias A. Eriksson, Metodi P. Yankov, Benjamin J. Puttnam +3
2018-10-02
Signal Processing · Electrical Eng. & Systems
Geometric Constellation Shaping with Low-complexity Demappers for Wiener Phase-noise Channels
Andrej Rode, Laurent Schmalen
2022-12-07
Information Theory · Computer Science
Joint Learning of Geometric and Probabilistic Constellation Shaping
Maximilian Stark, Fayçal Ait Aoudia, Jakob Hoydis
2019-08-30
Information Theory · Computer Science
End-to-End Learning of Joint Geometric and Probabilistic Constellation Shaping
Vahid Aref, Mathieu Chagnon
2021-12-10
Information Theory · Computer Science
Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities
Rasmus T. Jones, Tobias A. Eriksson, Metodi P. Yankov, Darko Zibar
2018-05-11
Information Theory · Computer Science
End-to-end Learning of Probabilistic and Geometric Constellation Shaping with Iterative Receivers
Harindu Jayarathne, Dileepa Marasinghe, Nandana Rajatheva, Matti Latva-aho
2025-10-28
Signal Processing · Electrical Eng. & Systems
Interplay of Probabilistic Shaping and the Blind Phase Search Algorithm
Darli A. A. Mello, Fabio A. Barbosa, Jacklyn D. Reis
2018-09-14
Information Theory · Computer Science
End-to-end Learning for GMI Optimized Geometric Constellation Shape
Rasmus T. Jones, Metodi P. Yankov, Darko Zibar
2019-07-22
Signal Processing · Electrical Eng. & Systems
Model-Based Deep Learning of Joint Probabilistic and Geometric Shaping for Optical Communication
Vladislav Neskorniuk, Andrea Carnio, Domenico Marsella, Sergei K. Turitsyn +2
2022-04-18
Information Theory · Computer Science
Constellation Design for Channels Affected by Phase Noise
Farbod Kayhan, Guido Montorsi
2012-10-08
Information Theory · Computer Science
Geometric Shaping of 2-Dimensional Constellations in the Presence of Laser Phase Noise
Hubert Dzieciol, Gabriele Liga, Eric Sillekens, Polina Bayvel +1
2021-02-03
Signal Processing · Electrical Eng. & Systems
End-to-end Learning of a Constellation Shape Robust to Channel Condition Uncertainties
Ognjen Jovanovic, Metodi P. Yankov, Francesco Da Ros, Darko Zibar
2022-06-08
Information Theory · Computer Science
Optimized Geometric Constellation Shaping for Wiener Phase Noise Channels with Viterbi-Viterbi Carrier Phase Estimation
Andrej Rode, Wintana Araya Gebrehiwot, Shrinivas Chimmalgi, Laurent Schmalen
2023-10-19
Information Theory · Computer Science
Geometric constellation shaping for wireless optical intensity channels: An information-theoretic approach
Suhua Zhou, Tianqi Li, Zhaoxi Fang, Jing Zhou +1
2024-12-03
Information Theory · Computer Science
Constellation Optimization in the Presence of Strong Phase Noise
Rajet Krishnan, Alexandre Graell i Amat, Thomas Eriksson, Giulio Colavolpe
2016-11-15
Information Theory · Computer Science
Joint Learning of Probabilistic and Geometric Shaping for Coded Modulation Systems
Fayçal Ait Aoudia, Jakob Hoydis
2020-04-15
Signal Processing · Electrical Eng. & Systems
Rate Adaptive Autoencoder-based Geometric Constellation Shaping
Ognjen Jovanovic, Metodi P. Yankov, Francesco Da Ros, Darko Zibar
2023-01-04
Signal Processing · Electrical Eng. & Systems
End-to-end Learning of a Constellation Shape Robust to Variations in SNR and Laser Linewidth
Ognjen Jovanovic, Metodi P. Yankov, Francesco Da Ros, Darko Zibar
2022-04-26
Information Theory · Computer Science
Full Diversity Blind Signal Designs for Unique Identification of Frequency Selective Channels
Jian-Kang Zhang, Chau Yuen
2008-05-21
Signal Processing · Electrical Eng. & Systems
Rate Adaptive Geometric Constellation Shaping Using Autoencoders and Many-To-One Mapping
Metodi P. Yankov, Ognjen Jovanovic, Darko Zibar, Francesco Da Ros
2023-07-20
Signal Processing · Electrical Eng. & Systems
High-Cardinality Hybrid Shaping for 4D Modulation Formats in Optical Communications Optimized via End-to-End Learning
Vinícius Oliari, Boris Karanov, Sebastiaan Goossens, Gabriele Liga +5
2021-12-21
Signal Processing · Electrical Eng. & Systems
Model-aided Geometrical Shaping of Dual-polarization 4D Formats in the Nonlinear Fiber Channel
Gabriele Liga, Bin Chen, Alex Alvarado
2021-10-25
Information Theory · Computer Science
Constellation Shaping for Bit-Interleaved LDPC Coded APSK
Matthew C. Valenti, Xingyu Xiang
2013-04-22
R2 v1 2026-06-24T08:06:07.091Z