Инд. авторы:	Redyuk A., Averyanov E., Sidelnikov O., Fedoruk M., Turitsyn S.
Заглавие:	Compensation of Nonlinear Impairments Using Inverse Perturbation Theory With Reduced Complexity
Библ. ссылка:	Redyuk A., Averyanov E., Sidelnikov O., Fedoruk M., Turitsyn S. Compensation of Nonlinear Impairments Using Inverse Perturbation Theory With Reduced Complexity // Journal of Lightwave Technology. - 2020. - Vol.38. - Iss. 6. - P.1250-1257. - ISSN 0733-8724.
Внешние системы:	DOI: 10.1109/JLT.2020.2971768; РИНЦ: 43288167; SCOPUS: 2-s2.0-85082400294; WoS: 000522169400017;
Реферат:	eng: We propose a modification of the conventional perturbation-based approach of fiber nonlinearity compensation that enables straight-forward implementation at the receiver and meets feasible complexity requirements. We have developed a model based on perturbation analysis of an inverse Manakov problem, where we use the received signal as the initial condition and solve Manakov equations in the reversed direction, effectively implementing a perturbative digital backward propagation enhanced by machine learning techniques. To determine model coefficients we employ machine learning methods using a training set of transmitted symbols. The proposed approach allowed us to achieve 0.5 dB and 0.2 dB Q(2)-factor improvement for 2000 km transmission of 11 x 256 Gbit/s DP-16QAM signal compared to chromatic dispersion equalization and one step per span two samples per symbol digital back-propagation technique, respectively. We quantify the trade-off between performance and complexity.
Ключевые слова:	perturbation-based detection technique; optical communication system; nonlinear signal distortions; EQUALIZER; manakov equations; Fiber nonlinearity compensation; machine learning; SIGNAL;
Издано:	2020
Физ. характеристика:	с.1250-1257