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Nearly Exact Analytical Formulation of the DNL Yield of the Digital-to-Analog Converter

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2 Author(s)
Park, H. ; Univ. of California, Los Angeles, CA, USA ; Ken Yang, C.-K.K.

Simple analytical differential nonlinearity (DNL) yield models of an arbitrarily segmented digital-to-analog converter (DAC) are presented. The yield estimation requires the analysis of the correlated DNL variation at each transition of the input code. Instead of using high-order integration of multivariate Gaussian probability density functions, this brief explores a new perspective on the formulation of the DNL yield by selecting essential test codes and by analyzing correlation coefficients between the test codes. Generally, for most DAC designs >; 6 bits, DNL caused by the binary and thermometer groups are equivalently uncorrelated. This statistical independence simplifies the DNL yield model as a multiplication of each section's yield, which involves only separate 1-D integration. We provide behavioral and HSPICE Monte Carlo simulation results that precisely match the yield estimation predicted by our models.

Published in:

Circuits and Systems II: Express Briefs, IEEE Transactions on  (Volume:59 ,  Issue: 9 )

Date of Publication:

Sept. 2012

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