Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Demonstration of spectrum narrowing mitigation based on recurrent neural networks for ultra-dense WDM networks

Not Accessible

Your library or personal account may give you access

Abstract

Traversing each WSS in ultra-dense WDM networks narrows the signal spectra. Simulations and experiments demonstrate, for the first time to our knowledge, spectrum narrowing mitigation based on RNN. Numerical simulations show that the RNN-based demodulation with impairment-aware optical path control significantly enlarges the transmission distance. Transmission experiments in the extended C-band successfully confirm an extension of the transmissible distance of 16QAM signals by over 500 km.

© 2024 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Space–time domain equalization algorithm based on complex-valued neural network in a long-haul photonic-aided MIMO THz system

Sicong Xu, Wen Zhou, Weiping Li, Yumeng Gou, Bohan Sang, Rahim Uddin, and Lingchuan Zeng
Opt. Lett. 49(5) 1253-1256 (2024)

Generalized Rayleigh quotient optimization method for inter-channel nonlinearity compensation in coherent optical communication systems

Tianxiang Lan, Chuanchuan Yang, Xiansong Fang, Fan Zhang, Wenjing Yu, Weiqin Zhou, and Zhangyuan Chen
Opt. Lett. 49(3) 694-697 (2024)

Recurrent neural network (RNN) for delay-tolerant repetition-coded (RC) indoor optical wireless communication systems

Jiayuan He, Jeonghun Lee, Tingting Song, Hongtao Li, Sithamparanathan Kandeepan, and Ke Wang
Opt. Lett. 44(15) 3745-3748 (2019)

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (6)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.