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All analog-to-digital converters (ADCs) have some amount of "input-referred noise," which can be modeled as a noise source in series with a noise-free ADC input. Input-referred noise is not the same as quantization noise, which only occurs when the ADC processes ac signals. In most cases, lower input noise is better, but in some cases, input noise can actually help achieve higher resolution. This may seem like a no-brainer, but keep reading this guide to understand why some noise is good noise.
overall architecture process
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Practical ADCs deviate from ideal ADCs in many ways. Input-referred noise is certainly not ideal, and its impact on the overall transfer function of the ADC is shown in the figure. As the analog input voltage increases, an "ideal" ADC (as shown) maintains a constant output code until the transition region is reached, at which point the output code immediately jumps to the next value and remains at that value until the next transition is reached district. Theoretically, an ideal ADC has zero "code transition" noise and zero transition region width. Real ADCs have a certain amount of code transition noise, so the transition region width depends on the amount of input-referred noise (as shown). The graph shows that the width of the code transition noise is approximately 1 LSB (least significant bit) peak-to-peak.
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technical details
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All ADC internal circuits generate some amount of root mean square (RMS) noise due to resistor noise and “kT/C” noise. This noise is present even with DC input signals, and it is the reason for the presence of code transition noise. Today it is common to refer to code transition noise as "input-referred noise" rather than directly using the term "code transition noise". Input-referred noise is usually characterized by a histogram of several output samples when the ADC input is a dc value. The output of most high-speed or high-resolution ADCs is a series of codes centered around the nominal value of the dc input (see Figure 2). To measure its value, the ADC's input is grounded or connected to a deeply decoupled voltage source, and a number of output samples are taken and represented as a histogram (sometimes called a "grounded input" histogram). Since the noise is roughly Gaussian distributed, the standard deviation σ of the histogram can be calculated, which corresponds to the effective input rms noise
While the inherent differential nonlinearity (DNL) of an ADC may cause its noise distribution to deviate slightly from the ideal Gaussian distribution (partial DNL is shown in the example figure), it is at least approximately Gaussian. If the DNL is relatively large, several σ values for different DC input voltages should be calculated and averaged. For example, if the code distribution has large and distinct peaks and valleys, it is an indication of a poor ADC design or, more likely, incorrect PCB layout routing, poor grounding, improper power supply decoupling ( ). If the distribution width changes drastically as the DC input is swept across the ADC input voltage range, this can also indicate a problem
The noise-free code resolution of an ADC is the number of bits beyond which individual codes cannot be unambiguously resolved due to the effective input noise (or input-referred noise) that all ADCs have, as above described in the text. This noise can be expressed as a root mean square quantity, usually in LSBrms. Multiplying by a factor of 6.6 converts rms noise to peak-to-peak noise (denoted by "LSB peak-to-peak"). The total range of the N-bit ADC is 2 NLSBs. Therefore, the total number of noise-free samples is equal to:
Note that the noise-free code resolution is 16.5 bits (80,000 noise-free samples) at an output data rate of 50Hz and an input range of ±10mV. The settling time under these conditions is 460ms, making this ADC ideal for precision weigh scale applications. Most data sheets provide similar data for high-resolution sigma-delta ADCs suitable for precision measurement applications. Resolution is sometimes calculated as the ratio of full-scale range to rms input noise (rather than peak-to-peak noise) and is called "effective resolution". Note: Under the same conditions, the effective resolution is log2(6.6) higher than the noise-free code resolution, about 2.7 bits.
summary
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Now consider a situation where the ADC has very low input-referred noise and the histogram always shows a clear code. What is the use of digital averaging for this ADC? The answer is simple - it doesn't work! No matter how many samples are averaged, the answer is always the same. But as long as enough noise is added to the input signal that there is more than one code in the histogram, then the mean method will work again. So a small amount of noise can be a good thing (at least for averaging methods), but the more noise present at the input, the more averaging samples are required to achieve the same resolution.