Fast Design Space Exploration and Multi-Objective Optimization of Wide-Band Noise-Canceling LNAs

Abstract

Design optimization of RF low-noise amplifiers (LNAs) remains a time-consuming and complex process. Iterations are needed to adjust impedance matching, gain, and noise figure (NF) simultaneously. The process can involve more iterations to adjust the non-linear behavior of the circuit which can be represented by the input-referred third-order intercept (IIP3). In this work, we present a variation-aware automated design and optimization flow for a wide-band noise-canceling LNA. We include the circuit non-linearity in the optimization flow without using a simulator in the loop. By describing the transistors using precomputed lookup tables (LUTs), a design database that contains 200,000 design points is generated in 3 s only without non-linearity computation and 10 s when non-linearity is taken into account. Using a gm/ID-based correct-by-construction design procedure, the generated design points automatically satisfy proper biasing, input matching, and gain matching requirements. The generated database enables the designer to visualize the design space and explore the design trade-offs. Moreover, multi-objective optimization across corners for a given set of specifications is applied to find the Pareto-optimal fronts of the design figures-of-merit. We demonstrate the presented flow using two design examples in a 65 nm process and the results are verified using Cadence Spectre.