LMS Adaptive Digital Background Calibration of Pipelined A/D Converters

Yun Chiu, Cheongyuen (Bill) Tsang, and Abhishek Somani
(Professors Paul R. Gray and Borivoje Nikolic)

This project will investigate the possibilities of using digital signal processing techniques to enhance pipelined A/D converter performance. Specifically, we're currently applying the Wiener filtering concept to the correction of analog errors. With a slow-but-accurate helper A/D and a back end FIR digital filter, we have proven in simulation that capacitor mismatch, finite opamp gain, and various offset errors can be eliminated through the digital filtering. The analog signal paths involved are open-loop. Correction is performed solely in digital, without feedback to the pipeline A/D to tweak analog parameters. The system is further made adaptive to track slow environmental changes (power supply voltage drift, ambient temperature change, etc.) by means of an LMS algorithm. Adaptation rate can be adjusted depending on the speed of the slow helper. With this approach, we're potentially looking at a very high conversion speed (> 200 MS/s) and high accuracy (>= 10 bits) where the stringent requirement on analog circuit components can be relaxed with the aid of digital techniques. Down the road, we will also investigate applications of Voterra filtering to correct nonlinearities and bandwidth limitations in analog circuits where the complexity of digital filters will increase geometrically. The driving force behind this, however, is the inexorable power of scaling coming from digital CMOS technology. If strategically leveraged upon, it will revolutionize the performance and design of traditional analog circuits in the near future.

Send mail to the author : (chiuyun@eecs.berkeley.edu)

Edit this abstract