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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…

Machine Learning · Computer Science 2026-02-04 Mohammad Taha Askari , Lutz Lampe , Amirhossein Ghazisaeidi

A new probabilistic shaping distribution that outperforms Maxwell-Boltzmann is studied for the nonlinear fiber channel. Additional gains of 0.1 bit/symbol MI or 0.2 dB SNR for both DP-256QAM and DP-1024QAM are reported after 200 km…

Optimizing the input probability distribution of a discrete-time channel is a standard step in the information-theoretic analysis of digital communication systems. Nevertheless, many practical communication systems transmit uniformly and…

Signal Processing · Electrical Eng. & Systems 2024-12-13 Mohammad Taha Askari , Lutz Lampe

Autoencoder-based deep learning is applied to jointly optimize geometric and probabilistic constellation shaping for optical coherent communication. The optimized constellation shaping outperforms the 256 QAM Maxwell-Boltzmann probabilistic…

Signal Processing · Electrical Eng. & Systems 2022-04-18 Vladislav Neskorniuk , Andrea Carnio , Domenico Marsella , Sergei K. Turitsyn , Jaroslaw E. Prilepsky , Vahid Aref

This paper studies the impact of probabilistic shaping on effective signal-to-noise ratios (SNRs) and achievable information rates (AIRs) in a back-to-back configuration and in unrepeated nonlinear fiber transmissions. For back-to-back,…

In this paper, probabilistic shaping is numerically and experimentally investigated for increasing the transmission reach of wavelength division multiplexed (WDM) optical communication system employing quadrature amplitude modulation (QAM).…

In this paper we carry out a joint optimization of probabilistic (PS) and geometric shaping (GS) for four-dimensional (4D) modulation formats in long-haul coherent wavelength division multiplexed (WDM) optical fiber communications using an…

We transmit probabilistic enumerative sphere shaped dual-polarization 64-QAM at 350Gbit/s/channel over 1610km SSMF using a short blocklength of 200. A reach increase of 15% over constant composition distribution matching with identical…

We introduce a trainable coded modulation scheme that enables joint optimization of the bit-wise mutual information (BMI) through probabilistic shaping, geometric shaping, bit labeling, and demapping for a specific channel model and for a…

Information Theory · Computer Science 2020-04-15 Fayçal Ait Aoudia , Jakob Hoydis

We show that short-length probabilistic shaping reduces nonlinear interference in optical fiber transmission. SNR improvements of up to 0.8 dB are obtained. The shaping gain vanishes when interleaving is employed and not undone before…

Signal Processing · Electrical Eng. & Systems 2020-03-27 Tobias Fehenberger , Helmut Griesser , Jörg-Peter Elbers

The rate flexibility and probabilistic shaping gain of $4$-dimensional signaling is experimentally tested for short-reach, unrepeated transmission. A rate granularity of 0.5 bits/QAM symbol is achieved with a distribution matcher based on a…

A class of circular 64-QAM that combines 'geometric' and 'probabilistic' shaping aspects is presented. It is compared to square 64-QAM in back-to-back, single-channel, and WDM transmission experiments. First, for the linear AWGN channel…

As communication systems are foreseen to enable new services such as joint communication and sensing and utilize parts of the sub-THz spectrum, the design of novel waveforms that can support these emerging applications becomes increasingly…

Information Theory · Computer Science 2021-07-15 Fayçal Ait Aoudia , Jakob Hoydis

Probabilistic shaping of quadrature amplitude modulation (QAM) is used to enhance the sensitivity of an optical communication system. Sensitivity gains of 0.43 dB and 0.8 dB are demonstrated in back-to-back experiments by shaping of 16QAM…

Information Theory · Computer Science 2016-01-19 Tobias Fehenberger , Domaniç Lavery , Robert Maher , Alex Alvarado , Polina Bayvel , Norbert Hanik

A scheme is proposed that combines probabilistic signal shaping with bit-metric decoding. The transmitter generates symbols according to a distribution on the channel input alphabet. The symbols are labeled by bit strings. At the receiver,…

Information Theory · Computer Science 2014-04-22 Georg Böcherer

An end-to-end learning method for constellation shaping with a shaping-encoder assisted transceiver architecture is presented. The shaping encoder, which produces shaping bits with a higher probability of zeros, is used to produce an…

Information Theory · Computer Science 2025-10-28 Harindu Jayarathne , Dileepa Marasinghe , Nandana Rajatheva , Matti Latva-aho

We present a novel end-to-end autoencoder-based learning for coherent optical communications using a "parallelizable" perturbative channel model. We jointly optimized constellation shaping and nonlinear pre-emphasis achieving mutual…

Signal Processing · Electrical Eng. & Systems 2021-07-27 Vladislav Neskorniuk , Andrea Carnio , Vinod Bajaj , Domenico Marsella , Sergei K. Turitsyn , Jaroslaw E. Prilepsky , Vahid Aref

Probabilistic amplitude shaping (PAS) is a practical means to achieve a shaping gain in optical fiber communication. However, PAS and shaping in general also affect the signal-dependent generation of nonlinear interference. This provides an…

Information Theory · Computer Science 2023-04-18 Mohammad Taha Askari , Lutz Lampe , Jeebak Mitra

Probabilistic shaping is a pragmatic approach to improve the performance of coherent optical fiber communication systems. In the nonlinear regime, the advantages offered by probabilistic shaping might increase thanks to the opportunity to…

Information Theory · Computer Science 2024-01-19 Stella Civelli , Enrico Forestieri , Marco Secondini

Different aspects of probabilistic shaping for a multi-span optical communication system are studied. First, a numerical analysis of the additive white Gaussian noise (AWGN) channel investigates the effect of using a small number of input…

Information Theory · Computer Science 2016-07-29 Tobias Fehenberger , Alex Alvarado , Georg Böcherer , Norbert Hanik
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