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Found 27 papers, 0 papers with code
Fault Monitoring in Passive Optical Networks using Machine Learning Techniques
Passive optical network (PON) systems are vulnerable to a variety of failures, including fiber cuts and optical network unit (ONU) transmitter/receiver failures.
Faulty Branch Identification in Passive Optical Networks using Machine Learning
In this paper, to overcome the aforementioned issues, we propose a generic ML approach trained independently of the network architecture for identifying the faulty branch in PON systems given OTDR signals for the cases of branches with close lengths.
Branch Identification in Passive Optical Networks using Machine Learning
A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated.
Degradation Prediction of Semiconductor Lasers using Conditional Variational Autoencoder
Semiconductor lasers have been rapidly evolving to meet the demands of next-generation optical networks.
A Machine Learning-based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication
First of all, an attention based gated recurrent unit (GRU) model is adopted for real-time prediction of performance degradation.
Convolutional Neural Networks for Reflective Event Detection and Characterization in Fiber Optical Links Given Noisy OTDR Signals
Fast and accurate fault detection and localization in fiber optic cables is extremely important to ensure the optical network survivability and reliability.
Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory
To reduce operation-and-maintenance expenses (OPEX) and to ensure optical network survivability, optical network operators need to detect and diagnose faults in a timely manner and with high accuracy.
Machine Learning-based Anomaly Detection in Optical Fiber Monitoring
The proposed method combines an autoencoder-based anomaly detection and an attention-based bidirectional gated recurrent unit algorithm, whereby the former is used for fault detection and the latter is adopted for fault diagnosis and localization once an anomaly is detected by the autoencoder.
Optical Fiber Fault Detection and Localization in a Noisy OTDR Trace Based on Denoising Convolutional Autoencoder and Bidirectional Long Short-Term Memory
Optical time-domain reflectometry (OTDR) has been widely used for characterizing fiber optical links and for detecting and locating fiber faults.
Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques
A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1. 55 um InGaAsP MQW-DFB laser diodes is presented.
Gated Recurrent Unit based Autoencoder for Optical Link Fault Diagnosis in Passive Optical Networks
We propose a deep learning approach based on an autoencoder for identifying and localizing fiber faults in passive optical networks.
Machine Learning based Data Driven Diagnostic and Prognostic Approach for Laser Reliability Enhancement
In this paper, a data-driven diagnostic and prognostic approach based on machine learning is proposed to detect laser failure modes and to predict the remaining useful life (RUL) of a laser during its operation.
A Hybrid CNN-LSTM Approach for Laser Remaining Useful Life Prediction
A hybrid prognostic model based on convolutional neural networks (CNN) and long short-term memory (LSTM) is proposed to predict the laser remaining useful life (RUL).
Federated Learning Approach for Lifetime Prediction of Semiconductor Lasers
A new privacy-preserving federated learning framework allowing laser manufacturers to collaboratively build a robust ML-based laser lifetime prediction model, is proposed.
A BiLSTM-CNN based Multitask Learning Approach for Fiber Fault Diagnosis
A novel multitask learning approach based on stacked bidirectional long short-term memory (BiLSTM) networks and convolutional neural networks (CNN) for detecting, locating, characterizing, and identifying fiber faults is proposed.
Channel Performance Estimations with Extended Channel Probing
We test the concept of extended channel probing in an Optical Spectrum as a Service scenario in coherent optimized flex-grid long-haul and 10Gbit/s OOK optimized 100-GHz fixed-grid dispersion-managed legacy DWDM networks.
Fiber Nonlinearity Mitigation by Short-Length Probabilistic Constellation Shaping for Pilot-Aided Signaling
The reason for this behavior is that short-length PCS implicitly induces some temporal properties in the shaped transmit sequence that are beneficial for the fiber-optic channel.
56 Gb/s DMT Transmission with VCSELs in 1.5 um Wavelength Range over up to 12 km for DWDM Intra-Data Center Connects
We demonstrate up to 12 km, 56 Gb/s DMT transmission using high-speed VCSELs in the 1. 5 um wavelength range for future 400Gb/s intra-data center connects, enabled by vestigial sideband filtering of the transmit signal.
Solutions for 80 km DWDM Systems
We review currently discussed solutions for 80 km DWDM transmission targeting inter data-center connections at 100G and 400G line rates.
Practical Solutions for 400 Gbit/s Data Center Transmission
We review three solutions for low-cost data center interconnects with a target reach of up to 80 km.
Optimizing Discrete Multi-tone Transmission for 400G Data Center Interconnects
It can be seen that an FFT length of 128 is sufficient to reach the required performance in terms of bit error ratio, however, a higher length can significantly improve the performance.
Experimental Investigation of Discrete Multitone Transmission in the Presence of Optical Noise and Chromatic Dispersion
Enabled by channel adaptive bit and power loading, we experimentally demonstrate discrete multitone transmission at 56Gb/s with simple intensity modulation and direct detection and achieve 50 km reach in the 1. 55um window.
Analysis of Nonlinear Fiber Interactions for Finite-Length Constant-Composition Sequences
This temporal property results in weaker nonlinear interactions, and thus higher SNR, for short CC sequences.
Huffman-coded Sphere Shaping and Distribution Matching Algorithms via Lookup Tables
In this paper, we study amplitude shaping schemes for the probabilistic amplitude shaping (PAS) framework as well as algorithms for constant-composition distribution matching (CCDM).
Real-time 112 Gbit/s DMT for Data Center Interconnects
We report on 112 Gbit/s real-time DMT transmission over up to 60 km, targeted at DCI applications.
Real-time discrete multi-tone transmission for passive optical networks in C- and O-band
DMT at 25 Gbit/s, 50 Gbit/s and 100 Gbit/s in passive systems with electro-absorption modulators is investigated.
First Experimental Demonstration of a 3-Dimensional Simplex Modulation Format Showing Improved OSNR Performance Compared to DP-BPSK
We experimentally demonstrate a novel 3-dimensional modulation format with 1. 2-dB OSNR tolerance improvement potential compared to DP-BPSK, as verified for the linear case.
