Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse

In this paper, data-transmission using the nonlinear Fourier transform for jointly modulated discrete and continuous spectra is investigated. A recent method for purely discrete eigenvalue removal at the detector is extended to signals with additional continuous spectral support. At first, the eigen...

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Main Authors: Benedikt Leible, Daniel Plabst, Norbert Hanik
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/22/10/1131
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spelling doaj-3fc25299cd0240af963692e270d0d1042020-11-25T03:55:49ZengMDPI AGEntropy1099-43002020-10-01221131113110.3390/e22101131Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its InverseBenedikt Leible0Daniel Plabst1Norbert Hanik2Institute for Communications Engineering, Technical University of Munich, Theresienstr. 90, 80333 Munich, GermanyInstitute for Communications Engineering, Technical University of Munich, Theresienstr. 90, 80333 Munich, GermanyInstitute for Communications Engineering, Technical University of Munich, Theresienstr. 90, 80333 Munich, GermanyIn this paper, data-transmission using the nonlinear Fourier transform for jointly modulated discrete and continuous spectra is investigated. A recent method for purely discrete eigenvalue removal at the detector is extended to signals with additional continuous spectral support. At first, the eigenvalues are sequentially detected and removed from the jointly modulated received signal. After each successful removal, the time-support of the resulting signal for the next iteration can be narrowed, until all eigenvalues are removed. The resulting truncated signal, ideally containing only continuous spectral components, is then recovered by a standard NFT algorithm. Numerical simulations without a fiber channel show that, for jointly modulated discrete and continuous spectra, the mean-squared error between transmitted and received eigenvalues can be reduced using the eigenvalue removal approach, when compared to state-of-the-art detection methods. Additionally, the computational complexity for detection of both spectral components can be decreased when, by the choice of the modulated eigenvalues, the time-support after each removal step can be reduced. Numerical simulations are also carried out for transmission over a Raman-amplified, lossy SSMF channel. The mutual information is approximated and the eigenvalue removal method is shown to result in achievable rate improvements.https://www.mdpi.com/1099-4300/22/10/1131fiber-optic communicationsnonlinear fourier transforminverse scatteringalgorithms
collection DOAJ
language English
format Article
sources DOAJ
author Benedikt Leible
Daniel Plabst
Norbert Hanik
spellingShingle Benedikt Leible
Daniel Plabst
Norbert Hanik
Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse
Entropy
fiber-optic communications
nonlinear fourier transform
inverse scattering
algorithms
author_facet Benedikt Leible
Daniel Plabst
Norbert Hanik
author_sort Benedikt Leible
title Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse
title_short Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse
title_full Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse
title_fullStr Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse
title_full_unstemmed Back-to-Back Performance of the Full Spectrum Nonlinear Fourier Transform and Its Inverse
title_sort back-to-back performance of the full spectrum nonlinear fourier transform and its inverse
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2020-10-01
description In this paper, data-transmission using the nonlinear Fourier transform for jointly modulated discrete and continuous spectra is investigated. A recent method for purely discrete eigenvalue removal at the detector is extended to signals with additional continuous spectral support. At first, the eigenvalues are sequentially detected and removed from the jointly modulated received signal. After each successful removal, the time-support of the resulting signal for the next iteration can be narrowed, until all eigenvalues are removed. The resulting truncated signal, ideally containing only continuous spectral components, is then recovered by a standard NFT algorithm. Numerical simulations without a fiber channel show that, for jointly modulated discrete and continuous spectra, the mean-squared error between transmitted and received eigenvalues can be reduced using the eigenvalue removal approach, when compared to state-of-the-art detection methods. Additionally, the computational complexity for detection of both spectral components can be decreased when, by the choice of the modulated eigenvalues, the time-support after each removal step can be reduced. Numerical simulations are also carried out for transmission over a Raman-amplified, lossy SSMF channel. The mutual information is approximated and the eigenvalue removal method is shown to result in achievable rate improvements.
topic fiber-optic communications
nonlinear fourier transform
inverse scattering
algorithms
url https://www.mdpi.com/1099-4300/22/10/1131
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