Cheol-Woong Lee

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2012-7

January 7, 2012

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-7.pdf

The strong market demand for mobile applications such as iPhone makes value on the form factor of the mobile devices. The form factor means how much we can integrate many functions in a given size of the mobile devices. The external component size is almost comparable to a chip size so that elimination of external component is crucial to the success of mobile devices in addition to the cost issues of the external components. External reference resistors are often used as the standard for calibrating voltage sources, current sources, and other component values within a circuit. Often these calibrations occur at a factory, but may also occur on an electronic device as it is used. However, external reference resistors consume area and cost and it is desirable to eliminate them. This work introduces a new way to calibrate on-chip resistance and capacitance without the external reference resistors. An integrated circuit includes a benchmarking circuitry and a tunable circuitry. The benchmarking circuit includes a target component and an internal reference component. The internal reference component exhibits a lower sensitivity to the changes in test conditions than the target component. Benchmarking Metric Measurement Module (BMMM) measures benchmarking metrics for the internal reference component and the target component. A benchmark value is calculated based on the benchmarking metrics. The novelty of this work is the powerful way to cancel the parasitic and systemic errors caused by operational amplifiers in RC tuner circuitry. This technique is broadly applicable to any RF and analog circuits that need the calibration of tunable circuit elements without external references.

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BibTeX citation:

@phdthesis{Lee:EECS-2012-7,
    Author= {Lee, Cheol-Woong},
    Title= {On-chip Benchmarking and Calibration without External References},
    School= {EECS Department, University of California, Berkeley},
    Year= {2012},
    Month= {Jan},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-7.html},
    Number= {UCB/EECS-2012-7},
    Abstract= {The strong market demand for mobile applications such as iPhone makes value on the form
factor of the mobile devices. The form factor means how much we can integrate many functions
in a given size of the mobile devices. The external component size is almost comparable to a
chip size so that elimination of external component is crucial to the success of mobile devices in
addition to the cost issues of the external components. External reference resistors are often used
as the standard for calibrating voltage sources, current sources, and other component values
within a circuit. Often these calibrations occur at a factory, but may also occur on an electronic
device as it is used. However, external reference resistors consume area and cost and it is
desirable to eliminate them.
This work introduces a new way to calibrate on-chip resistance and capacitance without the
external reference resistors. An integrated circuit includes a benchmarking circuitry and a
tunable circuitry. The benchmarking circuit includes a target component and an internal
reference component. The internal reference component exhibits a lower sensitivity to the
changes in test conditions than the target component. Benchmarking Metric Measurement
Module (BMMM) measures benchmarking metrics for the internal reference component and the
target component. A benchmark value is calculated based on the benchmarking metrics. The
novelty of this work is the powerful way to cancel the parasitic and systemic errors caused by
operational amplifiers in RC tuner circuitry. This technique is broadly applicable to any RF and
analog circuits that need the calibration of tunable circuit elements without external references.},
}

EndNote citation:

%0 Thesis
%A Lee, Cheol-Woong 
%T On-chip Benchmarking and Calibration without External References
%I EECS Department, University of California, Berkeley
%D 2012
%8 January 7
%@ UCB/EECS-2012-7
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-7.html
%F Lee:EECS-2012-7