Stochastic properties of quantization noise in memoryless converters affected by integral nonlinearity

This paper is focused on the stochastic properties of quantization noise introduced by nonideal memoryless converters. In particular, overloading effects and integral nonlinearity (INL) are considered. A theoretical model is given, which accurately describes the quantization noise probability density function in presence of overloading noise and both deterministic and stochastic INL. A Gaussian stimulus is adopted for validation purposes due to its relevance in modern telecommunication systems. The proposed model is then used to derive quantization noise power as a function of both input signal and INL stochastic properties, in order to evaluate the average performance of classes of analog-to-digital converters (ADC). Finally, the results are applied to a memoryless converter affected by Gaussian INL, analyzing the properties of quantization noise.