Abstract:
Practical microwave design is most often carried out in the nominal sense. Yet, in some cases, performance degradation due to uncertainties may lead to the system failing...Show MoreMetadata
Abstract:
Practical microwave design is most often carried out in the nominal sense. Yet, in some cases, performance degradation due to uncertainties may lead to the system failing to meet the prescribed specifications. Reliable uncertainty quantification (UQ) is, therefore, important yet intricate from numerical standpoint, especially when the circuit at hand is to be evaluated using electromagnetic (EM) simulation tools. Tolerance-aware design (e.g., yield improvement) is even more challenging. This article introduces a methodology for low-cost surrogate-based yield optimization of passive microwave components. The novelty of the proposed approach, and, at the same time, its major acceleration factor is to span the metamodel domain with the selected principal vectors, characterized by significant response variability within operating frequency bands of the component under design. This results in a volumewise constriction of the domain (thereby lower cost of the surrogate model setup) without restricting its size along the relevant directions of the parameter space. Consequently, our technique is a one-shot approach for yield optimization that does not require neither domain relocation nor surrogate reconstruction. Our methodology is demonstrated using two microstrip components and favorably compared to benchmark metamodeling techniques in terms of the computational cost of the yield maximization procedure. The average cost is only 130 EM simulations of the respective circuit, versus the average of 800 and over 360 analyses for the benchmark procedures. At the same time, its reliability is verified by means of EM-based Monte Carlo simulation.
Published in: IEEE Transactions on Microwave Theory and Techniques ( Volume: 70, Issue: 9, September 2022)