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Subtractive-Dither-Assisted Background Calibration for Linearity Enhancement in Pipelined ADCs for IIoT Applications
Shang Xu1, Shuwen Liang1, Jinbin Li1
1School of Integrated Circuits, Huazhong University of Science and Technology, Wuhan 430074, China.
Abstract:
This paper presents a subtractive-dither-assisted background calibration technique for a 2 GS/s 12 bit pipelined analog-to-digital converter (ADC). A large 7 bit pseudo-random dither is injected in both the flash and the multiplying digital-to-analog converter (MDAC) to decorrelate the differential nonlinearity (DNL) errors caused by the inherent quantization error nonlinearity, capacitor mismatching, and inter-stage amplifier nonlinearity from the input signal. Designed in a 28 nm CMOS process with a 1 V supply, post-layout simulations demonstrate a 10.2 dB improvement in spurious-free dynamic range (SFDR), from 73.8 dB to 84.4 dB, with dithering enabled under a close-to-Nyquist input frequency of 985 MHz. Although the injected dither cannot be completely removed in the digital domain, the proposed ADC exhibits only a 0.5 dB degradation in signal-to-noise-and-distortion ratio (SNDR) for full-scale input, achieving an SNDR of 62.3 dB and an effective number of bits (ENOB) of 10.1 bits. Dithering also improves static performance, with DNL and INL optimized to +0.54/-0.53 LSBs and +0.85/-0.88 LSBs, respectively. Moreover, the proposed dither-based calibration technique introduces an additional power consumption of less than 2 mW.
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