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

• Main Authors: Tsimbinos, J., Lever, K.V.
• Format: Conference Proceeding
• Language: English
• Subjects: Analog-digital conversion; Australia; Digital communication; Digital filters; Digital signal processing; Filtering; Higher order statistics; Nonlinear distortion; Signal processing; Timing jitter
• DOI: 10.1109/HOST.1993.264531

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.< >