TSMC publishes an open source paper "CMOS Image Sensor Random Telegraph Noise Time Constant Extraction From Correlated To Uncorrelated Double Sampling" by Calvin Yi-Ping Chao, Honyih Tu, Thomas Wu, Kuo-Yu Chou, Shang-Fu Yeh, and Fu-Lung Hsueh in IEEE Journal of the Electron Devices Society, Jan. 2017 issue.
Abstract:
A new method for on-chip random telegraph noise (RTN) characteristic time constant extraction using the double sampling circuit in an 8.3 Mpixel CMOS image sensor is described. The dependence of the measured RTN on the time difference between the double sampling and the key equation used for time constant extraction are derived from the continuous time RTN model and the discrete event RTN model. Both approaches lead to the same result and describe the data reasonably well. From the detailed study of the noisiest 1000 pixels, we find that about 75% to 85% of them show the signature of a single-trap RTN behavior with three distinct signal levels, and about 96% of the characteristic time constants fall between 1 μs and 500 μs with the median around 10 μs at room temperature.
Abstract:
A new method for on-chip random telegraph noise (RTN) characteristic time constant extraction using the double sampling circuit in an 8.3 Mpixel CMOS image sensor is described. The dependence of the measured RTN on the time difference between the double sampling and the key equation used for time constant extraction are derived from the continuous time RTN model and the discrete event RTN model. Both approaches lead to the same result and describe the data reasonably well. From the detailed study of the noisiest 1000 pixels, we find that about 75% to 85% of them show the signature of a single-trap RTN behavior with three distinct signal levels, and about 96% of the characteristic time constants fall between 1 μs and 500 μs with the median around 10 μs at room temperature.
TSMC RTS Noise Research
Reviewed by MCH
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January 18, 2017
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Reviewed by MCH
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January 18, 2017
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