Adaptive Sampling Algorithm for Macromodeling of Parameterized $S$-Parameter Responses

Abstract

This paper presents a new adaptive sampling strategy for the parametric macromodeling of -parameter-based frequency responses. It can be linked directly with the simulator to determine up front a sparse set of data samples that characterize the design space. This approach limits the overall simulation and macromodeling time. The resulting sample distribution can be fed into any kind of macromodeling technique, provided that it can deal with scattered data. The effectiveness of the approach is illustrated by a parameterized H-shaped microwave example.