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20202023
most citedGeometric Constellation Shaping for Fiber-Optic Channels via End-to-End Learning

47 citations · 129 across the 15 of their papers we have counts for

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Showing 2023Show all

9 papers · 1 filter

eess.SP2023

BICM-compatible Rate Adaptive Geometric Constellation Shaping Using Optimized Many-to-one Labeling

Metodi Plamenov Yankov, Smaranika Swain, Ognjen Jovanovic +2

In this paper, a rate adaptive geometric constellation shaping (GCS) scheme which is fully backward-compatible with existing state of the art bit-interleaved coded modulation (BICM…

eess.SP2023★ 8 cited

Differentiable Machine Learning-Based Modeling for Directly-Modulated Lasers

Sergio Hernandez, Ognjen Jovanovic, Christophe Peucheret +2

End-to-end learning has become a popular method for joint transmitter and receiver optimization in optical communication systems. Such approach may require a differentiable channel…

eess.SP2023

Low-complexity Samples versus Symbols-based Neural Network Receiver for Channel Equalization

Yevhenii Osadchuk, Ognjen Jovanovic, Stenio M. Ranzini +4

Low-complexity neural networks (NNs) have successfully been applied for digital signal processing (DSP) in short-reach intensity-modulated directly detected optical links, where ch…

cs.LG2023

Addressing Data Scarcity in Optical Matrix Multiplier Modeling Using Transfer Learning

Ali Cem, Ognjen Jovanovic, Siqi Yan +3

We present and experimentally evaluate using transfer learning to address experimental data scarcity when training neural network (NN) models for Mach-Zehnder interferometer mesh-b…

eess.SP2023

Rate Adaptive Geometric Constellation Shaping Using Autoencoders and Many-To-One Mapping

Metodi P. Yankov, Ognjen Jovanovic, Darko Zibar +1

A many-to-one mapping geometric constellation shaping scheme is proposed with a fixed modulation format, fixed FEC engine and rate adaptation with an arbitrarily small step. An aut…

eess.SP2023★ 1 cited

Data-Driven Modeling of Directly-Modulated Lasers

Sergio Hernandez Fernandez, Christophe Peucheret, Ognjen Jovanovic +2

The end-to-end optimization of links based on directly-modulated lasers may require an analytically differentiable channel. We overcome this problem by developing and comparing dif…

cs.NI2023★ 4 cited

Multi-Wavelength Transponders for High-capacity Optical Networks: A Physical-layer-aware Network Planning Study

Jasper Müller, Ognjen Jovanovic, Tobias Fehenberger +3

Continued cost- and power-efficient capacity scaling in optical networks is imperative to keep pace with ever-increasing traffic demands. In this paper, we investigate multi-wavele…

cs.NI2023★ 1 cited

Comparison of Single-Wavelength and Multi-Wavelength Transponders in a Physical-layer-aware Network Planning Study

Jasper Müller, Ognjen Jovanovic, Carmen Mas-Machuca +3

Based on suitable system architectures and realistic specifications, transmit OSNR penalties and spectral constraints of multi-wavelength transponders are identified and analyzed i…

eess.SP2023

Rate Adaptive Autoencoder-based Geometric Constellation Shaping

Ognjen Jovanovic, Metodi P. Yankov, Francesco Da Ros +1

An autoencoder is used to optimize bit-to-symbol mappings for geometric constellation shaping. The mappings allow for net rate adaptivity without additional hardware complexity, wh…