scholarly journals Simultaneous gain profile design and noise figure prediction for Raman amplifiers using machine learning

2021 ◽  
Vol 46 (5) ◽  
pp. 1157
Author(s):  
Uiara Celine de Moura ◽  
Ann Margareth Rosa Brusin ◽  
Andrea Carena ◽  
Darko Zibar ◽  
Francesco Da Ros
Keyword(s):  
Machine Learning ◽  
Noise Figure ◽  
Gain Profile ◽  
Raman Amplifiers ◽  
Profile Design

scholarly journals Influence of ASE Noise on Performance of DWDM Networks Using Low-power Pumped Raman Amplifiers

2015 ◽  
Vol 25 (2) ◽  
pp. 147
Author(s):  
Bui Trung Ninh ◽  
Nguyen Quoc Tuan ◽  
Ta Viet Hung ◽  
Nguyen The Anh ◽  
Pham Van Hoi
Keyword(s):  
Low Power ◽  
Wavelength Division Multiplexing ◽  
Bit Error Rate ◽  
Error Rate ◽  
Network Performance ◽  
Noise Figure ◽  
Chromatic Dispersion ◽  
Low Noise ◽  
Wavelength Division ◽  
Raman Amplifiers

We present the results of investigation  for  influence of amplified spontaneous emission (ASE) noise, noise figure (NF) and  chromatic dispersion on the performance of middle-distance Dense-wavelength-division-multiplexing (DWDM) networks using low-power pumped distributed Raman amplifiers (DRAs) in two different pump configurations, i.e., forward and backward pumping. We found that the pumping configurations, ASE noise, and dispersion play an important role for improving network performance by decrease of noise figure and bit error rate (BER) of the system. Simulation results show that the lowest bit error rate and low noise figure were obtained, when using forward pumping configuration. Moreover, we have also compared ASE noise powers of the simulation with these of the experiment. These results conclude that DRA with low pump power  ($<1$~W) is the promising key technology for short-- and/or middle-distance DWDM transmission networks.

Gain and noise figure spectrum control algorithm for fiber Raman amplifiers

2006 ◽  
Vol 18 (10) ◽  
pp. 1125-1127 ◽  
Author(s):  
J. Park ◽  
Jonghan Park ◽  
Pilhan Kim ◽  
Namkyoo Park
Keyword(s):  
Control Algorithm ◽  
Noise Figure ◽  
Raman Amplifiers ◽  
Spectrum Control

Machine Learning for Optimal Copper Doping Profile Design in CdTe Solar Cells

2021 ◽  
Author(s):  
Ghaith Salman ◽  
Stephen M. Goodnick ◽  
Abdul R. Shaik ◽  
Dragica Vasileska
Keyword(s):  
Machine Learning ◽  
Solar Cells ◽  
Doping Profile ◽  
Copper Doping ◽  
Cdte Solar Cells ◽  
Profile Design

scholarly journals Noise Gain Features of Fiber Raman Amplifier

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Georgii S. Felinskyi ◽  
Mykhailo Y. Dyriv
Keyword(s):  
Pump Power ◽  
Noise Figure ◽  
Single Mode ◽  
Gain Coefficient ◽  
Single Mode Fiber ◽  
Optical Noise ◽  
Raman Amplifier ◽  
Fiber Raman Amplifier ◽  
Gain Profile ◽  
Wide Wavelength Range

The formation dynamics of the optical noise in a silica single mode fiber (SMF) as function of the pump power variation in the counter pumped fiber Raman amplifier (FRA) is experimentally studied. The ratio between the power of amplified spontaneous emission and the power of incoherent optical noise is quantitatively determined by detailed analysis of experimental data in the pump powers range of 100–300 mW within the full band of Stokes frequencies, including FRA working wavelengths over the C + L transparency windows. It is found out the maximum of Raman gain coefficient for optical noise does not exceed ~60% of corresponding peak at the gain profile maximum of coherent signal. It is shown that the real FRA noise figure may be considerably less than 3 dB over a wide wavelength range (100 nm) at a pump power of several hundreds of mW.

scholarly journals Machine Learning Assisted Inverse Design for Ultrafine, Dynamic and Arbitrary Gain Spectrum Shaping of Raman Amplification

Photonics ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 260
Author(s):  
Yuting Huang ◽  
Jiangbing Du ◽  
Yufeng Chen ◽  
Ke Xu ◽  
Zuyuan He
Keyword(s):  
Machine Learning ◽  
Communication Systems ◽  
Noise Figure ◽  
Dynamic Change ◽  
Low Noise ◽  
Gain Spectrum ◽  
Inverse Design ◽  
Raman Amplification ◽  
Spectrum Shaping ◽  
Spectrum Optimization

Distributed Raman amplifier (DRA) has been widely studied in recent decades because of its low noise figure and flexible gain. In this paper, we present a novel scheme of DRA with broadband amplified spontaneous emission(ASE) source as pump instead of discrete pump lasers. The broadband pump is optimized by machine learning based inverse design and shaped by programmable waveshaper, so as to realize the ultrafine, dynamic and arbitrary gain spectrum shaping of Raman amplification. For the target of flat gain spectrum, the maximum gain flatness of 0.1086 dB is realized based on the simulation results. For the target of arbitrary gain spectrum, we demonstrate four gain profiles with maximum root mean square error (RMSE) of 0.074 dB. To further measure the performance of arbitrary gain spectrum optimization, the probability density functions (PDF) of RMSE and Errormax are presented. Meanwhile, the numeral relationship between the bands of broadband pump and signal is also explored. Furthermore, this work has great application potential to compensate the gain distortion or dynamic change caused by other devices in communication systems.

scholarly journals Optimizing gain profile and noise performance for distributed fiber Raman amplifiers

2004 ◽  
Vol 12 (24) ◽  
pp. 6053 ◽  
Author(s):  
Xueming Liu ◽  
Jian Chen ◽  
Chao Lu ◽  
Xiaoqun Zhou
Keyword(s):  
Noise Performance ◽  
Gain Profile ◽  
Raman Amplifiers
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