activity
20202022
most citedMachine Learning based Laser Failure Mode Detection

15 citations · 35 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2022★ 10 cited

Lifetime Prediction of 1550 nm DFB Laser using Machine learning Techniques

Khouloud Abdelli, Danish Rafique, Helmut Griesser +1

A novel approach based on an artificial neural network (ANN) for lifetime prediction of 1.55 um InGaAsP MQW-DFB laser diodes is presented. It outperforms the conventional lifetime…

eess.SP2022★ 15 cited

Machine Learning based Laser Failure Mode Detection

Khouloud Abdelli, Danish Rafique, Stephan Pachnicke

Laser degradation analysis is a crucial process for the enhancement of laser reliability. Here, we propose a data-driven fault detection approach based on Long Short-Term Memory (L…

cs.NI2021

Exploring Channel Probing to Determine Coherent Optical Transponder Configurations in a Long-Haul Network

Kaida Kaeval, Danish Rafique, Kamil Blawat +6

We use channel probing to determine the best transponder configurations for spectral services in a long-haul production network. An estimation accuracy better than +/- 0,7dB in GSN…

eess.SP2020

64 GBd DP-Bipolar-8ASK Transmission over 120 km SSMF Employing a Monolithically Integrated Driver and MZM in 0.25-um SiGe BiCMOS Technology

Gilda Raoof Mehrpoor, Carsten Schmidt-Langhorst, Benjamin Wohlfeil +13

We demonstrate 64 GBd signal generation up to bipolar-8-ASK utilizing a single MZM, monolithically integrated with segmented drivers in SiGe. Using polarization multiplexing, 300-G…

cs.NI2020★ 10 cited

HeCSON: Heuristic for Configuration Selectionin Optical Network Planning

Sai Kireet Patri, Achim Autenrieth, Danish Rafique +2

We present a transceiver configuration selection heuristic combining Enhanced Gaussian Noise (EGN) models, which shows a 40\% increase in throughput and 87\% decrease in execution…