## Getting Started With Delta-Sigma ADC Design

$\Delta \Sigma$ ADC is an irresistible topic for a Nyquist ADC designer. Several years ago I touched a bit of it when I studied noise-shaping SAR ADC. Recently I have the opportunity to revisit this topic.

The good thing is that there are plenty of resources you can find from the internet; while the bad part is that after reading so much stuff it seems what I know about it is still these two curves… Frustrating!

In this post, the focus is not on the technical details of $\Delta \Sigma$ ADC design, but on sharing my experience of getting started with it. Mainly I will point out the good references which speed up my learning curve and prevent drowning in the $\Delta \Sigma$ ADC sea of knowledge.

First, textbooks.

The popular yellow and green bibles are too difficult to digest for a newbie (BUT bibles are bibles! You will still need them time after time…). Until I found the data converter book written by Prof. Franco Maloberti, I just can’t stop reading its chapter 6 on oversampling and low order $\Sigma \Delta$ modulators. Besides a good explanatory flow, it also provides Matlab/Simulink models to vividly show the working algorithms and circuit defects of low order $\Delta \Sigma$ ADC.

Second, lecture notes.

Prof. Gabor C. Temes’s course on oversampled Delta-Sigma data converters from OSU (accessed 06/02/2022).

Prof. Richard Scherier’s course on Advanced Analog Circuits from University of Toronto (accessed 06/02/2022).

Prof. Vishal Saxena’s course on mixed-signal IC design (focused on Delta-Sigma ADCs) from Boise State University. I really like his hand-written lecture notes (accessed 06/02/2022).

Third, online resources.

cppsim.com by Michael H. Perrott. I benefit a lot from one of his tutorial (accessed 06/02/2022) on “Behavioral Simulation of A Second Order Discrete Time Delta‐Sigma ADC Using CppSim”. At the end of the document, there is an appendix on Matlab synthesis code based on Schreier’s Delta-Sigma Matlab Toolbox (very handy!).

Finally, I know … again … too much info here. Then stop reading, just start to create some behavioral model first!

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