activity
20182022
most citedEnd-to-end optimization of coherent optical communications over the split-step Fourier method guided by the nonlinear Fourier transform theory

54 citations · 66 across the 4 of their papers we have counts for

collaborators

5 papers

cs.NI2022★ 2 cited

Spectral Power Profile Optimization of Field-Deployed WDM Network by Remote Link Modeling

Rasmus T. Jones, Kyle R. H. Bottrill, Natsupa Taengnoi +2

A digital twin model of a multi-node WDM network is obtained from a single access point. The model is used to predict and optimize the transmit power profile for each link in the n…

eess.SP2020★ 54 cited

End-to-end optimization of coherent optical communications over the split-step Fourier method guided by the nonlinear Fourier transform theory

Simone Gaiarin, Francesco Da Ros, Rasmus T. Jones +1

Optimizing modulation and detection strategies for a given channel is critical to maximize the throughput of a communication system. Such an optimization can be easily carried out…

cs.IT2019

End-to-end Learning for GMI Optimized Geometric Constellation Shape

Rasmus T. Jones, Metodi P. Yankov, Darko Zibar

Autoencoder-based geometric shaping is proposed that includes optimizing bit mappings. Up to 0.2 bits/QAM symbol gain in GMI is achieved for a variety of data rates and in the pres…

cs.IT2018★ 10 cited

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…

cs.IT2018

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…