Black-Box Calibration for ADCs With Hard Nonlinear Errors Using a Novel INL-Based Additive Code: A Pipeline ADC Case Study

This paper presents a digital nonlinearity calibration technique for ADCs with strong input-output discontinuities between adjacent codes, such as pipeline, algorithmic, and SAR ADCs with redundancy. In this kind of converter, the ADC transfer function often involves multivalued regions, where conventional integral-nonlinearity (INL)-based calibration methods tend to miscalibrate, negatively affecting the ADC's performance. As a solution to this problem, this paper proposes a novel INL-based calibration which incorporates information from the ADC's internal signals to provide a robust estimation of static nonlinear errors for multivalued ADCs. The method is fully generalizable and can be applied to any existing design as long as there is access to internal digital signals. In pipeline or subranging ADCs, this implies access to partial subcodes before digital correction; for algorithmic or SAR ADCs, conversion bit/bits per cycle are used. As a proof-of-concept demonstrator, the experimental results for a 1.2 V 23 mW 130 nm-CMOS pipeline ADC with a SINAD of 58.4 dBc (in nominal conditions without calibration) is considered. In a stressed situation with 0.95 V of supply, the ADC has SINAD values of 47.8 dBc and 56.1 dBc, respectively, before and after calibration (total power consumption, including the calibration logic, being 15.4 mW).