Robust Analog/RF Circuit Design With Projection-Based Performance Modeling

In this paper, a robust analog design (ROAD) tool for post-tuning (i.e., locally optimizing) analog/RF circuits is proposed. Starting from an initial design derived from hand analysis or analog circuit optimization based on simplified models, ROAD extracts accurate performance models via transistor-level simulation and iteratively improves the circuit performance by a sequence of geometric programming steps. Importantly, ROAD sets up all design constraints to include large-scale process and environmental variations, thereby facilitating the tradeoff between yield and performance. A crucial component of ROAD is a novel projection-based scheme for quadratic (both polynomial and posynomial) performance modeling, which allows our approach to scale well to large problem sizes. A key feature of this projection-based scheme is a new implicit power iteration algorithm to find the optimal projection space and extract the unknown model coefficients with robust convergence. The efficacy of ROAD is demonstrated on several circuit examples