Performance Assessment of Ge-on-SOI-photodetector / Si-CMOS Receivers for High-Speed Optical Communications

2019 ◽  
Vol 3 (7) ◽  
pp. 99-109
Author(s):  
Steve Koester ◽  
Laurent Schares ◽  
Clint L. Schow ◽  
Jeremy D. Schaub ◽  
Gabriel Dehlinger ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Optical Communications ◽  
High Speed ◽  
Cmos Receivers

scholarly journals Inverted p-down Design for High-Speed Photodetectors

Photonics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 39
Author(s):  
Masahiro Nada ◽  
Fumito Nakajima ◽  
Toshihide Yoshimatsu ◽  
Yasuhiko Nakanishi ◽  
Atsushi Kanda ◽  
...  
Keyword(s):  
Amplitude Modulation ◽  
Optical Communications ◽  
High Speed ◽  
Pulse Amplitude ◽  
Avalanche Photodiode ◽  
Device Fabrication ◽  
Pulse Amplitude Modulation ◽  
Optical Coupling ◽  
Pin Photodiodes

We discuss the structural consideration of high-speed photodetectors used for optical communications, focusing on vertical illumination photodetectors suitable for device fabrication and optical coupling. We fabricate an avalanche photodiode that can handle 100-Gbit/s four-level pulse-amplitude modulation (50 Gbaud) signals, and pin photodiodes for 100-Gbaud operation; both are fabricated with our unique inverted p-side down (p-down) design.

Silicon-based nonlinear optical devices for high-speed optical communications

2008 ◽  
Author(s):  
Haisheng Rong ◽  
Simon Ayotte ◽  
Shengbo Xu ◽  
Oded Cohen ◽  
Mario Paniccia
Keyword(s):  
Optical Communications ◽  
High Speed ◽  
Nonlinear Optical ◽  
Optical Devices ◽  
Nonlinear Optical Devices ◽  
Silicon Based

scholarly journals Heterostructured silicon-germanium-silicon p-i-n avalanche photodetectors for chip-integrated optoelectronics -INVITED

2021 ◽  
Vol 255 ◽  
pp. 01002
Author(s):  
Daniel Benedikovic ◽  
Leopold Virot ◽  
Guy Aubin ◽  
Jean-Michel Hartmann ◽  
Farah Amar ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Optical Communications ◽  
Silicon Germanium ◽  
High Speed ◽  
Near Infrared ◽  
Building Blocks ◽  
Electrical Signal ◽  
Avalanche Photodetectors ◽  
Infrared Wavelengths ◽  
Germanium Silicon

Optical photodetectors are at the forefront of photonic research since the rise of integrated optics. Photodetectors are fundamental building blocks for chip-scale optoelectronics, enabling conversion of light into an electrical signal. Such devices play a key role in many surging applications from communication and computation to sensing, biomedicine and health monitoring, to name a few. However, chip integration of optical photodetectors with improved performances is an on-going challenge for mainstream optical communications at near-infrared wavelengths. Here, we present recent advances in heterostructured silicon-germanium-silicon p-i-n photodetectors, enabling high-speed detection on a foundry-compatible monolithic platform.

Machine Learning for the Performance Assessment of High-Speed Links

2018 ◽  
Vol 60 (6) ◽  
pp. 1627-1634 ◽  
Author(s):  
Riccardo Trinchero ◽  
Paolo Manfredi ◽  
Igor S. Stievano ◽  
Flavio G. Canavero
Keyword(s):  
Machine Learning ◽  
Performance Assessment ◽  
High Speed

ON-LINE PERFORMANCE ASSESSMENT AND FAULT DIAGNOSIS OF MECHANICAL SYSTEMS

2015 ◽  
Vol 39 (3) ◽  
pp. 705-715 ◽  
Author(s):  
Shang-Liang Chen ◽  
Yin-Ting Cheng ◽  
Hsien-Cheng Liu ◽  
Yun-Yao Chen
Keyword(s):  
Fault Diagnosis ◽  
Performance Assessment ◽  
Mechanical System ◽  
High Speed ◽  
Mechanical Performance ◽  
Wavelet Packet ◽  
Principal Component ◽  
Spindle Motor ◽  
Diagnostic Model ◽  
On Line

This study integrates sensors, signal capture equipment, industrial computers and machinery health check-up software to develop an On-line Performance Assessment and Fault Diagnosis of Mechanical System, helping engineers predict mechanical conditions. Physical quantities captured by the sensors is utilized to process physical signals, and the Wavelet Packet Energy method is used for the feature extraction of non-stationary signals in coordination with the Principal Component Analysis for feature selection. This study establishes On-line Performance Assessment and Fault Diagnosis of Mechanical System based on Discriminant Analysis which is able to immediately determine the mechanical performance. When abnormal mechanical conditions occur, Bayesian Network will be activated to construct error diagnostic model and determine possible causes of error or malfunction of the machinery. Finally, the system is applied to the fan motor, high-speed spindle motor and AC motor of the machine tool. Experimental results show that the theory can effectively diagnose mechanical performance remarkable with an accuracy rate of 92.50% or higher.

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