IEEE Photonics Journal (Jan 2024)

Joint Fiber Nonlinearity Mitigation and Compensation for Digital Sub-Carrier Multiplexing System

  • Selvakumar Tharranetharan,
  • Sunish Kumar Orappanpara Soman,
  • Lutz Lampe

DOI
https://doi.org/10.1109/JPHOT.2024.3429381
Journal volume & issue
Vol. 16, no. 4
pp. 1 – 17

Abstract

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Fiber nonlinearity is the bottleneck of optical communication systems and is commonly addressed by applying various nonlinearity mitigation and compensation techniques. In general, nonlinearity mitigation techniques offer modest improvements with minimal computational complexity, while nonlinearity compensation techniques provide significant performance gains at the expense of higher computational complexity. This motivates us to propose a joint nonlinearity mitigation and compensation approach in which the nonlinear effects during signal propagation are reduced to compensate for the residual nonlinearity at a lower complexity. Specifically, in this paper, we study the combination of symbol rate optimization (SRO) and perturbation-based nonlinearity compensation (PB-NLC) for a pre-chromatic dispersion compensated (pre-CDC) transmission of polarization multiplexing, digital sub-carrier multiplexing, and wavelength division multiplexing (PM-DSCM-WDM) optical communication system. We highlight the interplay between SRO and PB-NLC and demonstrate that joint SRO and PB-NLC provides considerable performance gain, significant complexity reduction, and an additional degree of freedom to balance performance-complexity trade-offs when compared to applying only PB-NLC in a conventional PM-WDM system. We observe that the pre-CDC transmission manifests a unique property that enables the distribution of PB-NLC computational complexity between transmitter and receiver. Leveraging the distinctive property, we propose a split PB-NLC technique for the PM-DSCM-WDM system. This technique combines the benefits of both pre-PB-NLC and post-PB-NLC, resulting in a modest performance improvement while maintaining the same computational complexity as post-PB-NLC.

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