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20142026
most citedIntroducing Enumerative Sphere Shaping for Optical Communication Systems with Short Blocklengths

110 citations · 556 across the 65 of their papers we have counts for

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34 papers · 1 filter

eess.SP2026

Multi-Modal Fiber Sensing for OffshoreEnvironmental and Infrastructure Monitoring

Konstantinos Alexoudis, Florian Azendorf, Alvaro Doval +5

Monitoring a 118 km subsea cable using Distributed acoustic, state-of-polarization, and Brillouin sensing captured storm-induced strain up to (dynamic) and $\app…

eess.SP2025

Precise Localization of High-Voltage Breakdown Events using -Optical Time-Domain Reflectometry on an Optical Ground Wire

Konstantinos Alexoudis, Luke Silvestre, Tom Huiskamp +6

We present -OTDR for detecting and localising full spark-gap breakdowns by analysing backscattered light phase and frequency-domain signatures during high-voltage discharges syn…

eess.SP2025★ 1 cited

Real-Time Diverse Fiber Sensing Multi-Event Detection using Phase OTDR Measurements

Konstantinos Alexoudis, Jasper Müller, Sai Kireet Patri +6

We demonstrate an experimental phase optical time-domain reflectometry (OTDR) system capable of simultaneous detection and classification of various environmental events, such as w…

eess.SP2025

On Irradiance Distributions for Weakly Turbulent FSO Links: Log-Normal vs. Gamma-Gamma

Carmen Álvarez Roa, Yunus Can Gültekin, Vincent van Vliet +3

Weak turbulence is commonly modeled using the log-normal distribution. Our experimental results show that this distribution fails to capture irradiance fluctuations in this regime.…

eess.SP2024

Mitigation of Polarization-Induced Fading in Optical Vector Network Analyzer for the Characterization of km-scale Space-Division Multiplexing Fibers

Besma Kalla, Martina Cappelletti, Menno van den Hout +5

We propose an optimized optical vector network analyzer with automatic polarization control to stabilize the reference arm polarization throughout the sweep range. We demonstrate t…

eess.SP2022

4D Geometric Shell Shaping with Applications to 400ZR

Sebastiaan Goossens, Yunus Can Gültekin, Olga Vassilieva +4

Geometric shell shaping is introduced and evaluated for reach increase and nonlinearity tolerance in terms of MI against PM-16QAM and PS-PM-16QAM in a 400ZR compatible transmission…

eess.SP2022★ 15 cited

Introducing 4D Geometric Shell Shaping for Mitigating Nonlinear Interference Noise

Sebastiaan Goossens, Yunus Can Gültekin, Olga Vassilieva +4

Four dimensional geometric shell shaping (4D-GSS) is introduced as an approach for closing the nonlinearity-caused shaping gap. This format is designed at the spectral efficiency o…

eess.SP2022

Experimental Validation of Sequence-Wise Predistorter for Evaluation of Geometrically Shaped 128-QAM

Menno van den Hout, Sjoerd van der Heide, Sebastiaan Goossens +1

A predistorter for transmitter nonlinearities is applied to the evaluation of a geometrically shaped constellation, such that constellation points are transmitted correctly during…

eess.SP2022★ 5 cited

Mitigating Nonlinear Interference by Limiting Energy Variations in Sphere Shaping

Yunus Can Gültekin, Alex Alvarado, Olga Vassilieva +4

Band-trellis enumerative sphere shaping is proposed to decrease the energy variations in channel input sequences. Against sphere shaping, 0.74 dB SNR gain and up to 9% increase in…

eess.SP2021★ 11 cited

High-Cardinality Hybrid Shaping for 4D Modulation Formats in Optical Communications Optimized via End-to-End Learning

Vinícius Oliari, Boris Karanov, Sebastiaan Goossens +6

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 divis…

eess.SP2021

MDG and SNR Estimation in SDM Transmission Based on Artificial Neural Networks

Ruby S. B. Ospina, Menno van den Hout, Sjoerd van der Heide +7

The increase in capacity provided by coupled SDM systems is fundamentally limited by MDG and ASE noise. Therefore, monitoring MDG and optical SNR is essential for accurate performa…

eess.SP2021★ 4 cited

Low-Complexity Geometrical Shaping for 4D Modulation Formats via Amplitude Coding

Bin Chen, Wei Ling, Yunus Can Gültekin +3

Signal shaping is vital to approach Shannon's capacity, yet it is challenging to implement at very high speeds. For example, probabilistic shaping often requires arithmetic coding…

eess.SP2021★ 4 cited

Real-time Transmission of Geometrically-shaped Signals using a Software-defined GPU-based Optical Receiver

Sjoerd van der Heide, Ruben S. Luis, Sebastiaan Goossens +8

A software-defined optical receiver is implemented on an off-the-shelf commercial graphics processing unit (GPU). The receiver provides real-time signal processing functionality to…

eess.SP2021

Real-time 10,000 km Straight-line Transmission using a Software-defined GPU-Based Receiver

Sjoerd van der Heide, Ruben S. Luis, Benjamin J. Puttnam +6

Real-time 10,000 km transmission over a straight-line link is achieved using a software-defined multi-modulation format receiver implemented on a commercial off-the-shelf general-p…

eess.SP2021★ 1 cited

Kramers-Kronig Receiver Combined With Digital Resolution Enhancer

Menno van den Hout, Sjoerd van der Heide, Chigo Okonkwo

A Kramers-Kronig receiver with a continuous wave tone added digitally at the transmitter is combined with a digital resolution enhancer to limit the increase in transmitter quantiz…

eess.SP2021★ 2 cited

Kurtosis-limited Sphere Shaping for Nonlinear Interference Noise Reduction in Optical Channels

Yunus Can Gültekin, Alex Alvarado, Olga Vassilieva +4

Nonlinear interference (NLI) generated during the propagation of an optical waveform through the fiber depends on the fourth order standardized moment of the channel input distribu…

eess.SP2021★ 3 cited

Neural-network-based MDG and Optical SNR Estimation in SDM Transmission

Ruby S B Ospina, Menno van den Hout, Sjoerd van der Heide +2

We propose a neural network model for MDG and optical SNR estimation in SDM transmission. We show that the proposed neural-network-based solution estimates MDG and SNR with high ac…

eess.SP2021★ 7 cited

10,000 km Straight-line Transmission using a Real-time Software-defined GPU-Based Receiver

Sjoerd van der Heide, Ruben S. Luis, Benjamin J. Puttnam +6

Real-time operation of a software-defined, GPU-based optical receiver is demonstrated over a 100-span straight-line optical link. Performance of minimum-phase Kramers-Kronig 4-, 8-…

eess.SP2020★ 17 cited

Field Trial of a Flexible Real-time Software-defined GPU-based Optical Receiver

Sjoerd van der Heide, Ruben S. Luis, Benjamin J. Puttnam +6

We introduce a flexible, software-defined real-time multi-modulation format receiver implemented on an off-the-shelf general-purpose graphics processing unit (GPU). The flexible re…

eess.SP2020★ 2 cited

1 Tbit/s/ Transmission Over a 130 km Link Consisting of Graded-Index 50 m Core Multi-Mode Fiber and 6LP Few-Mode Fiber

Menno van den Hout, Sjoerd van der Heide, John van Weerdenburg +7

We demonstrate 1 Tbit/s/ single-span transmission over a heterogeneous link consisting of graded-index 50 m core multi-mode fiber and 6LP few-mode fiber using a Kramers-Kroni…

eess.SP2020★ 4 cited

Experimental validation of MDL emulation and estimation techniques for SDM transmission systems

Menno van den Hout, Ruby S. B. Ospina, Sjoerd van der Heide +8

We experimentally validate a mode-dependent loss (MDL) estimation technique employing acorrection factor to remove the MDL estimation dependence on the SNR when using a minimum mea…

eess.SP2020★ 5 cited

Real-time, Software-Defined, GPU-Based Receiver Field Trial

Sjoerd van der Heide, Ruben S. Luis, Benjamin J. Puttnam +6

We demonstrate stable real-time operation of a software-defined, GPU-based receiver over a metropolitan network. Massive parallelization is exploited for implementing direct-detect…

eess.SP2020★ 34 cited

Mode-dependent Loss and Gain Estimation in SDM Transmission Based on MMSE Equalizers

Ruby S. B. Ospina, Menno van den Hout, Juan Carlos Alvarado-Zacarias +7

The capacity in space division multiplexing (SDM) systems with coupled channels is fundamentally limited by mode-dependent loss (MDL) and mode-dependent gain (MDG) generated in com…

eess.SP2020★ 48 cited

Revisiting Efficient Multi-Step Nonlinearity Compensation with Machine Learning: An Experimental Demonstration

Vinícius Oliari, Sebastiaan Goossens, Christian Häger +7

Efficient nonlinearity compensation in fiber-optic communication systems is considered a key element to go beyond the "capacity crunch''. One guiding principle for previous work on…