Least mean square adaptive digital background calibration of pipelined analog-to-digital converters

被引:140
|
作者
Chiu, Y [1 ]
Tsang, CW [1 ]
Nikolic, B [1 ]
Gray, PR [1 ]
机构
[1] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
关键词
adaptive digital background calibration; capacitor mismatch; code domain; finite op-amp gain; finite-impulse response (FIR); linear equalizer (LE); least mean square (LMS); algorithm; noise enhancement; pipelined analog-to-digital converter (ADC);
D O I
10.1109/TCSI.2003.821306
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We present an adaptive digital technique to calibrate pipelined analog-to-digital converters (ADCs). Rather than achieving linearity by adjustment of analog component values, the new approach infers component errors from conversion results and applies digital postprocessing to correct those results. The scheme proposed here draws close analogy to the channel equalization problem commonly encountered in digital communications. We show that, with the help of a slow but accurate ADC, the proposed code-domain adaptive finite-impulse-response filter is sufficient to remove the effect of component errors including capacitor mismatch, finite op-amp gain, op-amp offset, and sampling-switch-induced offset, provided they are not signal-dependent. The algorithm is all digital, fully adaptive, data-driven, and operates in the background. Strong tradeoffs between accuracy and speed of pipelined ADCs are greatly relaxed in this approach with the aid of digital correction techniques. Analog precision problems are translated into the complexity of digital signal -processing circuits, allowing this approach to benefit from CMOS device scaling in contrast to most conventional correction techniques.
引用
收藏
页码:38 / 46
页数:9
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