Estimation of Probability Density Function of Digital Substrate Noise in Mixed Signal System

  • Manisha Sharma
  • Pawan Kumar Singh
  • Tejbir Singh
  • Sanjay Sharma
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 18)

Abstract

The substrate noise generated in the mixed signal-integrated circuits, which encapsulates the analog, the RF, and the memory parts, is assumed to possess the non-Gaussian cyclostationary nature. This noise creates interference among the various parts of mixed signal circuits and even within the memory circuits itself. To estimate the PDF parameters of non-Gaussian noise, which is modeled by Cauchy’s distribution function (kind of non-Gaussian), the non-Gaussian noise is modeled by the non-Gaussian mixture density. The PDF parameters are estimated using the maximum log likelihood function, and the priori and post priori updates are used for updating the PDF parameters. The substrate noise in a CMOS inverter and in a chain of five CMOS inverters is estimated first, and then this has been considered as an example of non-Gaussian cyclostationary noise for PDF estimation. The probability density function (PDF) of non-Gaussian cyclostationary noise is analytically estimated in this paper.

Keywords

Substrate noise Probability density function Gaussian distribution Non-Gaussian distribution Cyclostationary process Cauchy’s distribution 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Manisha Sharma
    • 1
  • Pawan Kumar Singh
    • 1
  • Tejbir Singh
    • 1
  • Sanjay Sharma
    • 2
  1. 1.ECED, SRM University Delhi-NCRSonepatIndia
  2. 2.ECED, Thapar UniversityPatialaIndia

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