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20172026
most citedExperimental Comparison of Probabilistic Shaping Methods for Unrepeated Fiber Transmission

70 citations · 305 across the 27 of their papers we have counts for

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Showing 2023Show all

5 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…

physics.app-ph2023★ 1 cited

A comparison between black-, grey- and white-box modeling for the bidirectional Raman amplifier optimization

Metodi P. Yankov, Mehran Soltani, Andrea Carena +2

Designing and optimizing optical amplifiers to maximize system performance is becoming increasingly important as optical communication systems strive to increase throughput. Offlin…

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

Adaptive Turbo Equalization of Probabilistically Shaped Constellations

Edson Porto da Silva, Metodi Plamenov Yankov

Fiber nonlinearity compensation of probabilistically shaped constellations with adaptive turbo equalization is investigated for the first time. Potential for more than 100% transmi…

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…