A Universal Evaluation Method of Element Matching Strategies for Data Converters Based on Optimal Combination Algorithms

Element matching approaches based on Optimal Combination Algorithms (OCAs) are methods that try to calibrate element mismatches in data converters by rearranging the mapping relations between circuit elements and control logics. This work for the first time proposes a universal method and its corresponding Figure-of-Merit to evaluate the performance of various OCA approaches. It adopts the quantile of integral nonlinearity as the criterion and is consequently compatible with most of matching OCAs. Dynamic performance and the corresponding effective-number-of-bits (ENOB) limited by mismatches are also investigated. A critical feature of the proposed method is its robustness to the disturbance of element standard deviation as long as the standard deviation is in a reasonable region. Merits of our method have been explained and proved mathematically, and also been verified numerically by data extracted from previously reported works and their reproduction by authors, which together make this proposal more convincing and rigorous. Due to those merits, our proposed method could also help designers to specify a feasible standard deviation for circuit elements when they are designing data converters with OCAs.