Accurate design‐oriented simulation‐driven modeling of miniaturized microwave structures

Abstract

SUMMARYOne of the important prerequisites for efficient design optimization of microwave structures is availability of fast yet reliable replacement models (surrogates) so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations for handling optimizationrelated tasks is often prohibitive. A popular approach to construction of fast surrogates is data-driven modeling. Unfortunately, it normally requires a large number of training samples, and it is virtually infeasible for structures that exhibit highly nonlinear responses (e.g. filters or couplers). In this work, a design-oriented modeling technique is proposed where good accuracy is achieved by careful non-uniform design space sampling that accounts for nonlinear relationship between the operating frequency of the structure and its geometry parameters, as well as carrying out the modeling process only for selected characteristic points of the structure responses (those that determine satisfaction/violation of given design specifications). Our approach is demonstrated using a miniaturized microstrip rat-race coupler modeled in a wide range of geometry parameters and compared to conventional data-driven modeling using kriging interpolation. Design optimization examples are also provided.

Fast optimization of quasi‐periodic slow‐wave structures with applications to broadband microwave coupler miniaturization

“…Majority of them utilize transmission line (TL) theory to provide closed‐form design formulas applicable for the target devices, but also require some sort of EM‐based fine‐tuning procedure to account for inaccuracies of the utilized models . Design closure is typically realized using repetitive parameter sweeps or direct optimization, both being computationally expensive . This difficulty can be alleviated through surrogate‐based optimization (SBO), which relies on iteratively corrected fast low‐fidelity models (surrogates) replacing high‐fidelity EM models.…”

“…One should note that SBO techniques such as space mapping (SM) indispensably require low‐fidelity models to be well‐aligned with their high‐fidelity counterparts. Development of such models for quasi‐periodic slow‐wave structures is an extremely challenging task due to limitations of TL theory in modeling of complex cross‐coupling effects between adjacent slow‐wave cells …”

“…1,2,4 Design closure is typically realized using repetitive parameter sweeps or direct optimization, both being computationally expensive. 22 This difficulty can be alleviated through surrogatebased optimization (SBO), 8 which relies on iteratively corrected fast low-fidelity models (surrogates) replacing high-fidelity EM models. One should note that SBO techniques such as space mapping (SM) 9 indispensably require low-fidelity models to be well-aligned with their high-fidelity counterparts.…”

“…Development of such models for quasi-periodic slow-wave structures is an extremely challenging task due to limitations of TL theory in modeling of complex crosscoupling effects between adjacent slow-wave cells. 6,10,22 This work presents a customized procedure for the construction of a reliable surrogate model pertaining to a quasi-periodic slow-wave structure. The proposed approach involves low-cost EM simulations, local approximation modeling, space mapping and surrogate-based optimization to provide accurate results.…”