Simple noise shaping DACs: some examples

A few days ago, @Brouhaha and I had a conversation on Twitter on simple noise shaping digital-to-analogue converters, a.k.a sigma-delta or delta-sigma DACs (depending on who you talk to).

These converters can generate high-quality analogue signals, such as CD-quality audio, by very quickly switching between a limited number of output voltages. One-bit DACs take this to the extreme: they can only output two voltages, e.g. 1V and -1V.

The advantage of such DACs is simplicity. A 1-bit DAC can be built using a single microcontroller or FPGA pin! It almost seems too good to be true — and it is!

Two big disadvantages are: 1) the fast switching causes a huge amount of noise to be generated, which we must take care of, and 2) the microcontroller or FPGA must be able to calculate and generate a new pin state at the switching frequency.

Noise shaping

Naively generating a 1-bit output signal is very simple: we just take our desired signal and see if it’s value is larger or smaller than zero and output, for instance, 1V when it’s larger and -1V when it’s smaller. While the output signal will very coarsely resemble the desired signal, a lot of error (noise!) is present.

Luckily, and perhaps surprisingly, this noise can be moved, or shaped, to be vastly more pronounced at high frequencies than at low frequencies. A lowpass filter at the output of the DAC will then be able to remove much of the noise, resulting in a much cleaner signal. In fact, the audio DAC in your PC, tablet or phone you’re reading this on work on exactly these principles!

The noise shaping is achieved in three steps: 1) the 1-bit (digital) output signal is fed back and subtracted from the input signal, thereby generating a signal representing the error at the output. 2) the error is fed into an integrator, which forms an error accumulator: the output represent the total output error over time. 3) the accumulated error is quantised by the 1-bit quantiser and turned into an analogue signal.

The method outlined above ensures that, on average / observed over time, the 1-bit output signal tracks the desired input signal. In other words: if we apply some kind of moving averaging on the 1V/-1V output, we obtain the low-frequency desired signal. In practice, this averaging is done using an analogue filter, often in the form of one or two RC sections.

The more integrators are used, the higher the order of the noise shaping and the more noise is suppressed at low frequencies. Of course, the higher the order the more hardware and/or calculations are required. At a certain point, increasing the order has diminishing returns. It is rare to see noise shapers use more than seven integrators.

To keep things simple, we will limit our experiments to first- and second-order architectures.

A 1-bit first-order DAC

firstorder

Fig 1: A two-level (1-bit quantizer) first-order noise shaping DAC with dithering.

A first order DAC is shown in Fig 1. For testing purposes, we use a 1 kHz sine wave with a 75% amplitude (relative to full scale, i.e. -1 .. 1). The sample rate (fs) of the desired signal is chosen to be 50ksps and the desired output band is assumed to be from 0 to 10kHz.

Our performance metric is Signal-to-Noise-And-Distortion ratio (SINAD), which is expressed in dB. For reference: an ideal 16-bit converter should have a SINAD of around 96 dB when generating a single full-scale wave. An ideal 8-bit converter should have a SINAD of around 48 dB when generating a single full-scale sine wave.

The noise shaper operates at a clock rate of fclk = OSR*fs, where fs is the sample rate of the input signal and OSR is the oversampling factor. Common oversampling factors are 32, 64, 128 and 256.

The following plots were generated by calculating the output spectrum of the noise shaping DAC at different oversampling factors. All relevant system parameters are shown in the title of the plot:

firstorder_32

firstorder_64

firstorder_128

firstorder_256

The plots clearly show the desired signal (the peak at 1 kHz) and the noise, which is increasing with frequency. Note that the slope of the increase is independent of the oversampling ratio. But, the higher the oversampling ratio, the lower the noise at the 1kHz desired frequency. This is because, at higher oversampling ratios, there is more spectral room to put the noise, due to the Nyquist sampling theorem.

The effective number of bits (ENOB) for OSR = 32, 64, 128 and 256 are 7 bits, 9 bits, 10.5 bits and 12 bits, respectively.

A 3-level (1.58-bit) first-order DAC

Instead of the usual 2-level quantizer, we can use a 3-level quantizer that outputs -1V, 0V and 1V. This will require at least two digital output pins but has the added benefit that a large-value DC decoupling capacitor can be avoided.

The architecture is exactly the same as the 2-level version, but is included here for completeness:

firstorder3

The following plots were generated by calculating the output spectrum of the noise shaping DAC at different oversampling factors. All relevant system parameters are shown in the title of the plot:

firstorder3_32

firstorder3_64

firstorder3_128

firstorder3_256

The noise level is around 1dB lower than in the 2-level case. It does not seem worth increasing the number of quantizer levels from 2 to 3 for noise reasons. In fact, I expect this performance gain is quickly lost because we now have to match the voltage levels of the two output pins. Any mismatch will result in additional in-band noise.

Given there is no noise advantage, the effective number of bits (ENOB) for this converter is approximately equal to the 2-level variant.

A 1-bit second-order DAC

To get better noise shaping, moving to a second-order noise shaper architecture makes sense. The following block diagram show such a second-order device:

secondorder2

Note that I have added additional power-of-two gain factors. These are needed to limit the working range of the registers between -1.0 and 1.0. Any serious implementation will include saturation logic for each integrator.

Again, the system is evaluated by generating spectrum plots:

secondorder_32

secondorder_64

secondorder_128

secondorder_256

All the plots show an increase is noise shaping: the slope is steeper compared to the first-order architectures. As expected, the increased noise shaping also has a large positive effect on the SINAD figures. A second-order DAC with OSR=32 attains the same SINAD as a first-order converter with an OSR of 128!

A second-order OSR=128 DAC has a simulated/theoretical performance of a traditional 16-bit converter, after brick wall lowpass filtering at 10kHz.

The OSR=256 DAC theoretically has more than 18 effective bits!

The following plot shows part of the OSR=32 converter output and a filtered version (8th order butterworth filter):

secondorder_timedomain_32

There be dragons here!

Wouldn’t it be nice if the actual performance was equal to the theoretical/simulated performance? Yes, yes it would — unfortunately, this will not be the case. Perhaps even more unfortunately, it won’t even be close!

There are a lot of limitations of the hardware that must be overcome in order to make good DACs. Some of these limitations are: high clock jitter sensitivity, non-zero ON resistance of the transistors in the output stage, slewing artifacts, out-of-band noise intermodulation and power supply noise injection, to name a few. Having to solve all these problems makes designing good DACs a highly skilled task indeed!

I write this not to keep the reader from experimenting, far from it. These are very nice architectures to explore, learn and have fun with! But be prepared and accept to get performance lower than your simulations show.