A new approach for Variability Analysis of Analog ICs

The impact of process variability in nanoscale circuits has traditionally been handled with Monte Carlo analysis. In this paper, we propose a new method to estimate the variation bounds of circuit performance, that combines response surface modeling techniques with the Cornish-Fisher expansion: process parameter variations are first mapped to circuit performance metrics by a quadratic model, then an analytical approximation of the performance distribution's quantiles enables enclosure of the performance variations. The proposed method demonstrates an excellent accuracy/efficiency ratio compared to Monte Carlo-based methods.