Applications of higher-order statistics to modelling, identification and cancellation of nonlinear distortion in high-speed samplers and analogue-to-digital converters using the Volterra and Wiener models

Abstract

The authors demonstrate the use of the Volterra and Wiener models for the identification and removal of low order (soft) nonlinear distortion in high speed analogue-to-digital converters. In particular, they show that the Volterra and Wiener models may be used to identify and remove low order distortion in a typical high speed flash or two-stage subranging type analogue-to-digital converter, in which the input signal dependent timing jitter in its sample-and-hold circuit is the dominant source of distortion. A fifth order Volterra model is used to represent the sampler's timing jitter distortion. They obtain the Volterra model kernels using either the Lee-Schetzen (1976, 1989) method and the relationship between the Wiener and Volterra kernels, or by using an adaptive method to obtain the Volterra kernels directly. They then use a fifth order Volterra inverse to apply post-distortion to compensate for the sampler distortion.<>