Transfer learning assisted convolutional neural networks for modulation format recognition in few-mode fibers
Few-mode fiber (FMF), a mode multiplex technique, has been a candidate to provide high
transmission capability in next-generation elastic optical networks (EONs), where the …
transmission capability in next-generation elastic optical networks (EONs), where the …
Modulation format recognition with transfer learning assisted convolutional neural network using multiple Stokes sectional plane image in multi-core fibers
Z Guo, B Liu, J Ren, X Wu, Y Li, Y Mao, S Chen… - Optics …, 2022 - opg.optica.org
A modulation format recognition (MFR) scheme based on multi-core fiber (MCF) is proposed
for the next generation of elastic optical networks (EONs). In this scheme, multiple Stokes …
for the next generation of elastic optical networks (EONs). In this scheme, multiple Stokes …
Modulation format identification in mode division multiplexed optical networks
In this paper, we address the problem of modulation format identification (MFI) for few mode
fiber (FMF) transmission in elastic optical networks (EONs). The MFI accuracy is studied …
fiber (FMF) transmission in elastic optical networks (EONs). The MFI accuracy is studied …
Joint modulation format recognition and optical performance monitoring for efficient fiber-optic communication links using ensemble deep transfer learning
K Sindhumitha, RK Jeyachitra… - Optical …, 2022 - spiedigitallibrary.org
We propose an ensemble deep transfer learning (EDTL) method, which is a more refined
multilayer feature extraction achieved by aggregating the convolutional layers of pretrained …
multilayer feature extraction achieved by aggregating the convolutional layers of pretrained …
Optical performance monitoring via domain adversarial adaptation in few-mode fiber
We propose and demonstrate an optical performance monitoring (OPM) scheme in few-
mode fiber (FMF) based elastic optical networks (EONs). In this work, an adversarial transfer …
mode fiber (FMF) based elastic optical networks (EONs). In this work, an adversarial transfer …
Design of bend-limited large-mode area dispersion shifted few-mode fiber for fast communication
B Behera, MN Mohanty - 2019 international conference on …, 2019 - ieeexplore.ieee.org
We propose the novel design of ring core dispersion-shifted fiber (RC-DSF) for a few-mode
operation. The design claims to support four linearly-polarized (LP) modes such as LP 01 …
operation. The design claims to support four linearly-polarized (LP) modes such as LP 01 …
Low-complexity and nonlinearity-tolerant modulation format identification using random forest
Y Zhao, C Shi, D Wang, X Chen, L Wang… - IEEE Photonics …, 2019 - ieeexplore.ieee.org
A novel low-complexity and nonlinearity-tolerant modulation format identification (MFI) using
random forest (RF) is proposed for the flexible coherent receivers (FCRs). The RF-based …
random forest (RF) is proposed for the flexible coherent receivers (FCRs). The RF-based …
Performance investigation of modulation format identification in super-channel optical networks
The problem of automatic modulation format identification (MFI) is one of the main
challenges in adaptive optical systems. In this work, we investigate MFI in super-channel …
challenges in adaptive optical systems. In this work, we investigate MFI in super-channel …
Identifying modulation formats through 2D Stokes planes with deep neural networks
W Zhang, D Zhu, Z He, N Zhang, X Zhang, H Zhang… - Optics express, 2018 - opg.optica.org
A lightweight convolutional (deep) neural networks (CNNs) based modulation format
identification (MFI) scheme in 2D Stokes planes for polarization domain multiplexing (PDM) …
identification (MFI) scheme in 2D Stokes planes for polarization domain multiplexing (PDM) …
Modulation format identification in coherent receivers using deep machine learning
We propose a novel technique for modulation format identification (MFI) in digital coherent
receivers by applying deep neural network (DNN) based pattern recognition on signals' …
receivers by applying deep neural network (DNN) based pattern recognition on signals' …