Research output per year
Research output per year
Morteza Kamalian, Jaroslaw E. Prilepsky, Son Thai Le, Sergei K. Turitsyn
Research output: Contribution to journal › Article › peer-review
In this work, we introduce the periodic nonlinear Fourier transform (PNFT) method as an alternative and efficacious tool for compensation of the nonlinear transmission effects in optical fiber links. In the Part I, we introduce the algorithmic platform of the technique, describing in details the direct and inverse PNFT operations, also known as the inverse scattering transform for periodic (in time variable) nonlinear Schrödinger equation (NLSE). We pay a special attention to explaining the potential advantages of the PNFT-based processing over the previously studied nonlinear Fourier transform (NFT) based methods. Further, we elucidate the issue of the numerical PNFT computation: we compare the performance of four known numerical methods applicable for the calculation of nonlinear spectral data (the direct PNFT), in particular, taking the main spectrum (utilized further in Part II for the modulation and transmission) associated with some simple example waveforms as the quality indicator for each method. We show that the Ablowitz-Ladik discretization approach for the direct PNFT provides the best performance in terms of the accuracy and computational time consumption.
Original language | English |
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Pages (from-to) | 18353-18369 |
Number of pages | 17 |
Journal | Optics Express |
Volume | 24 |
Issue number | 16 |
Early online date | 2 Aug 2016 |
DOIs | |
Publication status | Published - 8 Aug 2016 |
Research output: Contribution to journal › Article › peer-review
Kamalian Kopae, M. (Creator), Prilepsky, J. E. (Creator), Le, S. T. (Creator) & Turitsyn, S. (Creator), Aston Data Explorer, 22 Jul 2016
DOI: 10.17036/a4d473dc-7f7c-4869-bba5-f82bd3bb3dea, https://www.osapublishing.org/oe/abstract.cfm?uri=oe-24-16-18353
Dataset
Kamalian Kopae, M. (Creator), Prilepsky, J. E. (Creator), Le, S. T. (Creator) & Turitsyn, S. (Creator), Aston Data Explorer, 22 Jul 2016
DOI: 10.17036/d867da63-e85a-470f-862f-f0175a23cef9, https://www.osapublishing.org/oe/abstract.cfm?uri=oe-24-16-18370
Dataset