Analog-to-Digital Converters (ADC) - Charge-Balancing and Delta-Sigma ADC 

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Thank you for your question, that is indeed a very important question to fully understand Sigma-Delta ADCs. We can recommend, that you have a look at this website: www.analog.com/en/design-center/interactive-design-tools/sigma-delta-adc-tutorial.html There you can find a nice tool to "reproduce" the behaviour of a sigma-delta ADC step-by-step. In the example on the bottom of the website, they use a bit-stream which is 8-bit long, Vin=1.0V and Vref=2.5V. They receive a bit-stream of 1 0 1 1 1 0 1 1. We can see, that 6 of 8 outputs are high and 2 of 8 outputs are low. This means, that 75% of all outputs are high. Translating this back to a voltage would mean, that we are at 75% of the input range (in this case between -2.5V and +2.5V). Calculation gives Vout=-2.5V+5V*0.75=1.25V. If we are looking for a digital value: As we have 8 bits in the (unary) stream, this corresponds to 3 bits (=log2(8)) in a binary representation. In our case it would mean, that we would get a digital output value of 110 or 6 in decimal. Some more examples to understand the concept: unary -> binary 00000000 -> 000 10000000 -> 001 00000001 -> 001 00010000 -> 001 01010101 -> 100 10101010 -> 100 We hope this help in understanding the concept :)

In this video we only focussed on the basic principle of Sigma-Delta ADCs. Your question however, whether we can build a True Random Number Generator (TRNG) with these ADCs, is quite straightforward. It seems like there is some research [1], [2] ongoing in this topic, but we do not have any research experience there. So we would recommend having a look at current literature. [1] doi.org/10.1109/LSSC.2020.3010901 [2] doi.org/10.1109/ISCAS.2016.7527159

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