A Behavioral Dynamic Nonlinear Model for Time-Interleaved ADC Based on Volterra Series

Wentao Wei, Peng Ye*, Jinpeng Song, Hao Zeng, Jian Gao, Yu Zhao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

The non-ideal circuit implementations cause a significant degradation in the performance of the time-interleaved analog-to-digital converter (TIADC) system. In this paper, a behavioral model for the TIADC based on Volterra series is proposed to model the dynamic nonlinearities in TIADC. The time-domain and frequency-domain expressions of the behavioral model based on hybrid Volterra series are derived first. Then, the discrete-time equivalent model is proposed by transforming the hybrid TIADC system to a discrete time one based on discrete-time Volterra series only. The derivations give a theoretical foundation to use discrete-time Volterra series to model the mixed-domain TIADC system, which makes it possible to make full use of the related existing derivations, conclusions, and methodologies on discrete-time Volterra series. We also summarize some common special cases of Volterra series to provide practical guidelines for ADC and TIADC practitioners. We present the main features of these models and their relationship with the Volterra series. The simulation and experimental results show the effectiveness of the proposed model.

Original languageEnglish
Article number6287639
Pages (from-to)41860-41873
Number of pages14
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019
Externally publishedYes

Keywords

  • Analog-to-digital converter
  • Volterra series
  • discrete-time equivalent model
  • dynamic nonlinearities
  • time-interleaved

Fingerprint

Dive into the research topics of 'A Behavioral Dynamic Nonlinear Model for Time-Interleaved ADC Based on Volterra Series'. Together they form a unique fingerprint.

Cite this