An adaptation method to improve secret key rates of time-frequency QKD in atmospheric turbulence channels

2016 ◽  
Author(s):  
Xiaole Sun ◽  
Ivan B. Djordjevic ◽  
Mark A. Neifeld
Keyword(s):  
Atmospheric Turbulence ◽  
Secret Key ◽  
Time Frequency ◽  
Adaptation Method

scholarly journals Adaptive low density parity check encoder for a complete free space optics/continuous variable-quantum key distribution system using commercially available off-the-shelf devices for variable throughput network considering dynamical atmospheric turbulence levels

2018 ◽  
Vol 64 (5) ◽  
pp. 478
Author(s):  
Josue Lopez
Keyword(s):  
Atmospheric Turbulence ◽  
Distribution System ◽  
Quantum Key Distribution ◽  
Continuous Variable ◽  
Free Space Optics ◽  
Parity Check ◽  
Secret Key ◽  
Space Optics ◽  
Low Density Parity Check ◽  
Commercial Network

 In this paper, an adaptive LDPC encoder for complete FSO/CV-QKD system using a COTS device for emulated dynamical atmospheric turbulence levels is presented. The experimental and emulation results show the maximum and minimal final secret key rates of  105 Kbps and 10 Kbps, respectively, for minimal and maximal throughput in a commercial network, 30 Mbps and 90 Mbps, respectively. Our proposal presents an adequate performance for weak and moderate atmospheric turbulence levels and a suitable option for improve the using of QKD systems.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Time-Frequency Analysis of Partial Discharge Phenomena in SF6 gas using Wavelet Transform

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Partial Discharge ◽  
Time Frequency Analysis ◽  
Time Frequency
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