Abstract

Space division multiplexing (SDM) – such as based on multi-mode fibers – is under investigation to support the growing capacity demands. In optical networks, the estimation of quality of transmission (QoT) is a fundamental control task to identify the most suitable transmission parameters (e.g., modulation format) to meet proper spectral efficiency while satisfying the required optical reach. The Gaussian Noise (GN) model is widely adopted for QoT estimation. However, the basic version of the GN model does not account for the interplay between mode dispersion and the Kerr effect. In this paper, we investigate the impact of mode dispersion on SDM networks exploiting strongly coupled modes, through an extended GN model. Network performance analysis is evaluated. First, an analysis of the achievable information rate (AIR) with Gaussian data statistics is presented. Then, a network capacity analysis is shown constrained to a set of supported modulation formats and a fixed symbol rate. Finally, blocking probability is studied with the same set of supported modulation formats with variable symbol rates. The presented network analysis shows that accounting for mode dispersion increases the throughput considering: i) Gaussian data statistics, ii) different modulation formats. Moreover, the blocking probability analysis shows a blocking reduction when mode dispersion is considered in the physical layer modeling.

Dependence of nonlinear interference on mode dispersion and modulation format in strongly-coupled SDM transmissions

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Performance comparisons between machine learning and analytical models for quality of transmission estimation in wavelength-division-multiplexed systems [Invited]

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Machine learning regression for QoT estimation of unestablished lightpaths

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