It may be the first time you've heard of the term, with function implied by semantics. But what are digitally assisted analog circuits? How do they perform or give "assistance" to the analog part exactly? What are their advantages and disadvantages? Does this field have any potential in emerging technologies (in my opinion they do, which is why I've decided to write all about them in this article).

Before anything else, a proper background to digitally assisted analog circuits is in order (what a mouthful! I'll be writing this as DAAC or DAA for short throughout the article).  

It all started when scaled CMOS technology began progressing rapidly, challenges in analog design becoming more difficult to surmount. Remember that with decreasing area, precision decreases and devices become more nonlinear. In addition, estimates show advances in the digital sector equating to 3 times longer in analog for catching up. Obviously, there was a burgeoning demand for a solution to this lag. One such solution that was cooked up is DAAC design.

What are all these D.A.A.C.s, Anyhow?

DAACs supposedly bring the best of both analog and digital by integrating them. The digital fabric, which could be a digital signal processor, implements corrections to the unregulated output from the analog block. The most famous applications are in DACs and ADCs [2], with impressive power efficiency and performance improvements suggested by most recent studies. Digital calibration (to be discussed later) solved analog deficiencies in deep submicron (that's <0.1 um) CMOS technology with increased tolerance in mismatch at almost no cost in precision.

Other applications involve amplifiers, where digital assistance relaxes requirements on linearity and gain precision with the critical requirement at input referred noise. Aside from lower power consumption in conventional amplifiers, many alternative amplifier topologies can be used.  Another application is a 28nm Mobile SoC (based from a study conducted by Broadcom Corp. in Irvine, CA) [3]. You can observe the contrast in performance from the table (Fig. 10)

Note: "This Work" denotes testing on the 28nm Mobile SoC - a DSP and application switching regulator (ASR).

Some DAAC applications don't just stop with a combination of analog and digital. They also add a bit of machine learning. Now we have a machine-learning digitally assisted analog circuit. But why would we want such a feature for a DAAC? Well, for a delta-sigma DAAC - gradient descent purports improving online calibration of parameters (especially to effects of local minima).

How do these digitally-assisted-analog-circuits "assist"?

There are in general 2 types of assistance: digital compensation and digital calibration. Digital compensation refers to a digital mapping of raw output bits to a corrected, final set of output bits. On the other hand, digital calibration involves using digital calibration settings to adjust analog circuit parameters, directly correcting output values from the analog block.
Fig. 1 provides a simple illustration of how both types work.

Fig. 1 Shown are block diagrams comparing (a) Digital Compensation (b) Digital Calibration

There are many ways to apply digital assistance in circuit design. One direct approach is by adjustment of comparator thresholds (which are at the heart of most ADC architectures). Popular methods for calibration include varying the load capacitance, the body voltages of the transistors at the input of the comparator, and using a redundant input pair of those said transistors. 

Comparator adjustment shifts limitations in accuracy from offset to electrical noise, which significantly reduces the power consumed by the comparator, as well as its input capacitance. In addition, some alternative architectures that potentially further power efficiency become possible (as with amplifiers). In DACs, digital assistance reduces required area for matching, which is useful at high resolutions.

From theory, digital signals carry a lot more noise than analog signals and a structure that combines both analog and digital provides a path for the noise from the digital block to get coupled to analog. This is an important consideration because it will be difficult to provide separate isolated paths for the analog and digital ground if they are close to each other on the layout.

Given the arguments above, it is easy to presume that DAACs have the potential of offering a bright future to analog. Of course, the ultimate decision will lay upon how the industry and consumers will respond, as well as on whether any competing solutions can outshine this approach. 



[2] Fang-shi Lai, Yung-Fu Lin, Digitally-assisted analog designs for submicron CMOS technology. Proceedings of 2010 International Symposium on VLSI Design, Automation and Test, IEEE Conference Publications, pp. 49-52

[3] Xicheng Jiang; Narayan Prasad Ramachandran, (2014). Digitally-assisted analog and analog-assisted digital design techniques for a 28 nm mobile system-on-chip. ESSCIRC 2014 - 40th European Solid State Circuits Conference, pp. 475-478