429 citations · 806 across the 12 of their papers we have counts for
12 papers
Implementing Neural Network-Based Equalizers in a Coherent Optical Transmission System Using Field-Programmable Gate Arrays
Pedro J. Freire, Sasipim Srivallapanondh, Michael Anderson +9
In this work, we demonstrate the offline FPGA realization of both recurrent and feedforward neural network (NN)-based equalizers for nonlinearity compensation in coherent optical t…
Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systems
Pedro J. Freire, Michael Anderson, Bernhard Spinnler +8
For the first time, recurrent and feedforward neural network-based equalizers for nonlinearity compensation are implemented in an FPGA, with a level of complexity comparable to tha…
Distributed Transmission and Spatially Coupled Forward Error Correction in Regenerative Multipoint-to-Point Networks
Laurent Schmalen, Tobias A. Eriksson, Fred Buchali +2
We investigate the performance of coded modulation for multi-hop regenerative optical networks. We analyze options for computing decoder input LLRs, show reach increases by optimiz…
Inter-Core Crosstalk Impact of Classical Channels on CV-QKD in Multicore Fiber Transmission
Tobias A. Eriksson, Benjamin J. Puttnam, Georg Rademacher +5
Crosstalk-induced excess noise is experimentally characterized for continuous-variable quantum key distribution, spatially multiplexed with WDM PM-16QAM channels in a 19-core fiber…
Geometric Constellation Shaping for Fiber Optic Communication Systems via End-to-end Learning
Rasmus T. Jones, Tobias A. Eriksson, Metodi P. Yankov +4
In this paper, an unsupervised machine learning method for geometric constellation shaping is investigated. By embedding a differentiable fiber channel model within two neural netw…
Coexistence of Continuous Variable Quantum Key Distribution and 7 12.5 Gbit/s Classical Channels
Tobias A. Eriksson, Takuya Hirano, Motoharu Ono +6
We study coexistence of CV-QKD and 7 classical 12.5 Gbit/s on-off keying channels in WDM transmission over the C-band. We demonstrate key generation with a distilled secret key rat…
Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities
Rasmus T. Jones, Tobias A. Eriksson, Metodi P. Yankov +1
A new geometric shaping method is proposed, leveraging unsupervised machine learning to optimize the constellation design. The learned constellation mitigates nonlinear effects wit…
End-to-end Deep Learning of Optical Fiber Communications
Boris Karanov, Mathieu Chagnon, Félix Thouin +5
In this paper, we implement an optical fiber communication system as an end-to-end deep neural network, including the complete chain of transmitter, channel model, and receiver. Th…
Exploring and Experimenting with Shaping Designs for Next-Generation Optical Communications
Fanny Jardel, Tobias A. Eriksson, Cyril Méasson +4
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 tran…
Applying Neural Networks in Optical Communication Systems: Possible Pitfalls
Tobias A. Eriksson, Henning Bülow, Andreas Leven
We investigate the risk of overestimating the performance gain when applying neural network based receivers in systems with pseudo random bit sequences or with limited memory depth…
Long-haul coherent communications using microresonator-based frequency combs
Attila Fülöp, Mikael Mazur, Abel Lorences-Riesgo +8
Microresonator-based frequency combs are strong contenders as light sources for wavelength-division multiplexing (WDM). Recent demonstrations have shown the potential of microreson…
Impact of 4D channel distribution on the achievable rates in coherent optical communication experiments
Tobias A. Eriksson, Tobias Fehenberger, Peter A. Andrekson +3
We experimentally investigate mutual information and generalized mutual information for coherent optical transmission systems. The impact of the assumed channel distribution on the…