Crosstalk-aware routing, spectrum, and core assignment in space-division multiplexing networks with bidirectional multicore fibers

Chen, Yidong; Yin, Shuo; Guo, Shijia; Ma, Rong; Huang, Shanguo

doi:10.1117/1.oe.58.11.116110

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…Multicore fiber (MCF) has been emerged as a promising and sustaining space division multiplexing (SDM) technology to overcome the optical signal transmission capacity constraint of the existing single mode-single core fiber (SM-SCF) and to satisfy the ultra-high transmission capacity demand of the future optical technologies [Chen et al 2019;Saitoh and Matsuo 2016;Farooque at al. 2019].…”

Section: Introductionmentioning

confidence: 99%

“…In the recent past, investigations of the signal distortions, such as crosstalk and dispersion in MCFs have been the main concern among the researchers across the globe [Chen et al 2019;Saitoh and Matsuo 2016;Farooque at al. 2019;Lataoui et al 2022;Jiang et al 2019;Zhang et al 2021;García et al 2019].…”

Section: Introductionmentioning

confidence: 99%

“…2019;Lataoui et al 2022;Jiang et al 2019;Zhang et al 2021;García et al 2019]. Further, WC-MCF is a promising SDM approach which does not require any multiple input multiple output (MIMO) processing for the crosstalk indemnification [Chen et al 2019]. Moreover, the variations in intercore differential mode delay (DMD) due to variations in mode coupling, is negligibly small in weakly coupled homogeneous multicore fibers (WC-HMCF) .…”

Section: Introductionmentioning

confidence: 99%

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Differential group delay behavior in homogeneous weakly coupled multicore fiber under bending and twisting condition

Farooque

Kumar

Singh

et al. 2023

J Opt

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The impacts of core count/layout on the mode effective refractive index, bend and twist induced differential group delay (DGD) of different cores, worst-case DGD, and intercore DGD, in weakly coupled homogeneous multicore fibers (WC-HMCFs) have been analyzed to select the proper core layout with low DGD value for a particular core count. Further, in order to calculate the intercore DGD values, the generalized expressions of core pitch for the different core layouts have been derived. Moreover, the impacts of core radius, relative refractive index difference, and core pitch on the mode effective refractive index and DGD levels for the 3-core WC-HMCFs, with linear and triangular core layouts, have been analyzed numerically by using the finite element method based FemSIM simulation platform, and MATLAB. It is observed that for a certain core count value, the core layout and core pitch have significant impacts on the DGD levels; while, the variations in the values of core radius and relative refractive index difference have no significant impact on the DGD levels. Further, increase in core count normally increases the DGD levels in all core layouts. On the other hand, for the fixed values of core count, cladding diameter, and outer cladding thickness, the core layout which has the lowest core pitch leads to the lowest value of intercore DGD, as compared to the other core layouts. The investigations carried out in this work may provide the guidelines in different MCF applications, such as MCF based multi-parameter sensing, signal processing in microwave photonics, etc.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Differential group delay behavior in homogeneous weakly coupled multicore fiber under bending and twisting condition

Farooque

Kumar

Singh

et al. 2023

J Opt

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show abstract

“…To increase capacity for EON's, Space Division Multiplexing has been proposed recently including multi-core and few mode fiber, which introduces core assignment as another problem that needs to be solved when multi-core fiber is used. This necessitates knowledge of the physical impairments especially crosstalk introduced by multi core fiber (Tode and Hirota, 2014;Chen et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Aided Optical Performance Monitoring Techniques: A Review

2022

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Future communication systems are faced with increased demand for high capacity, dynamic bandwidth, reliability and heterogeneous traffic. To meet these requirements, networks have become more complex and thus require new design methods and monitoring techniques, as they evolve towards becoming autonomous. Machine learning has come to the forefront in recent years as a promising technology to aid in this evolution. Optical fiber communications can already provide the high capacity required for most applications, however, there is a need for increased scalability and adaptability to changing user demands and link conditions. Accurate performance monitoring is an integral part of this transformation. In this paper, we review optical performance monitoring techniques where machine learning algorithms have been applied. Moreover, since many performance monitoring approaches in the optical domain depend on knowledge of the signal type, we also review work for modulation format recognition and bitrate identification. We additionally briefly introduce a neuromorphic approach as an emerging technique that has only recently been applied to this domain.

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Phase error analysis and compensation considering ambient light for phase measuring profilometry

Zhou

Liu

et al. 2014

Optics and Lasers in Engineering

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Crosstalk-aware routing, spectrum, and core assignment in space-division multiplexing networks with bidirectional multicore fibers

Cited by 5 publications

References 13 publications

Differential group delay behavior in homogeneous weakly coupled multicore fiber under bending and twisting condition

Differential group delay behavior in homogeneous weakly coupled multicore fiber under bending and twisting condition

Machine Learning-Aided Optical Performance Monitoring Techniques: A Review

Phase error analysis and compensation considering ambient light for phase measuring profilometry

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