Polarization-multiplexed nonlinear inverse synthesis with standard and reduced-complexity NFT processing


In this work, we study the performance of polarization division multiplexing nonlinear inverse synthesis transmission schemes for fiber-optic communications, expected to have reduced nonlinearity impact. Our technique exploits the integrability of the Manakov equation—the master model for dual-polarization signal propagation in a single mode fiber—and employs nonlinear Fourier transform (NFT) based signal processing. First, we generalize some algorithms for the NFT computation to the two- and multicomponent case. Then, we demonstrate that modulating information on both polarizations doubles the channel information rate with a negligible performance degradation. Moreover, we introduce a novel dual-polarization transmission scheme with reduced complexity which separately processes each polarization component and can also provide a performance improvement in some practical scenarios.

Publication DOI: https://doi.org/10.1364/OE.26.017360
Divisions: College of Engineering & Physical Sciences > Aston Institute of Photonics Technology (AIPT)
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funding: Erasmus + mobility programme; EPSRC Programme (TRANSNET); Leverhulme Project (RPG-2018-063); POR FESR (FIPILI3).
Publication ISSN: 1094-4087
Last Modified: 20 May 2024 07:24
Date Deposited: 26 Jun 2018 12:45
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Related URLs: https://www.osa ... =oe-26-13-17360 (Publisher URL)
PURE Output Type: Article
Published Date: 2018-06-25
Published Online Date: 2018-06-20
Accepted Date: 2018-06-07
Authors: Civelli, S.
Turitsyn, S. K. (ORCID Profile 0000-0003-0101-3834)
Secondini, M.
Prilepsky, J. E. (ORCID Profile 0000-0002-3035-4112)



Version: Published Version

License: Creative Commons Attribution

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