A Novel Surrogate-Based Approach to Yield Estimation and Optimization of Microwave Structures Using Combined Quadratic Mappings and Matrix Transfer Functions

Abstract

Yield estimation and yield-driven design optimization play important roles in microwave design. Existing surrogate-based yield estimation/optimization methods need to develop separate surrogate models or a large surrogate model with high complexity to deal with multiport problems, which is computationally inefficient. This article proposes a novel surrogate-based method to expedite yield estimation/optimization of multiport microwave structures using combined quadratic mappings and matrix-valued transfer functions. For multiport structures, the responses of different transfer functions corresponding to different pairs of input–output ports are computed with separate residues, while the responses of transfer functions for all pairs of input–output ports are computed with a common set of poles. Taking advantage of this, we propose to formulate a set of quadratic functions to map the relationship between the separate residues and statistical/geometrical parameters while employing merely one quadratic function to map the relationship between the common poles and statistical/geometrical parameters. The resultant mappings together with the matrix-format transfer function form an efficient surrogate to expedite the yield estimation and optimization processes for microwave structures. Compared with existing surrogate-based methods, the proposed method can achieve similar yield estimation accuracy in a shorter time due to fewer electromagnetic (EM) simulations. Three microwave structures are used to demonstrate the advantages of the proposed method. Based on accurate yield estimations, we further perform yield-driven design optimization incorporating the proposed surrogate for all the three examples.