Performance-driven modeling of compact couplers in restricted domains

Koziel, Slawomir; Sigurðsson, Ari T.

doi:10.1002/mmce.21296

Cited by 16 publications

(12 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consider two miniaturized microstrip couplers shown in Fig. 5, a rat-race coupler (RRC) [61], and a branch-line coupler (BLC) [62]. The details concerning the substrates, design variables, parameter and objective spaces, as well as reference designs can be found in Table 1.…”

Section: A Verification Case Studiesmentioning

confidence: 99%

Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate

et al. 2021

Self Cite

View full text Add to dashboard Cite

Fast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable-and often prohibitive-CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven models, which are fast to evaluate, versatile, and easy to handle. Notwithstanding, the curse of dimensionality as well as the utility demands (e.g., so that the model covers sufficiently broad ranges of the system operating conditions), limit the applicability of conventional methods. A performance-driven modeling paradigm allows for mitigating these issue by focusing the surrogate setup process in a constrained domain encapsulating designs being of high quality w.r.t. the assumed figures of interest. The nested kriging framework capitalizing on this idea, renders the constrained surrogate using kriging interpolation, and has been shown to surpass traditional approaches. In pursuit of further accuracy improvements, this work incorporates the performance-driven concept into the fully-connected regression model (FRCM). The latter has been recently introduced in the context of frequency selective surfaces, and combined deep neural networks with Bayesian optimization, the latter employed to determine the network architecture and hyper-parameters. Using two examples of miniaturized microstrip couplers, our methodology is demonstrated to outperform both conventional modeling techniques and nested kriging, with reliable models constructed over multi-dimensional parameters spaces using just a few hundreds of samples.INDEX TERMS Dara-driven modeling; surrogate modeling; performance-driven surrogates; nested kriging; deep regression model; Bayesian optimization.

show abstract

Section: A Verification Case Studiesmentioning

confidence: 99%

Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…The second verification case is a miniaturized microstrip rat-race coupler (RRC) [59], also implemented on RF-35 substrate (εr = 3.5, h = 0.762 mm, tan δ = 0.0018). The circuit geometry, shown in Fig.…”

Section: B Case 2: Miniaturized Rat-race Couplermentioning

confidence: 99%

Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits With Dimensionality Reduction

2020

Self Cite

View full text Add to dashboard Cite

Contemporary microwave design heavily relies on full-wave electromagnetic (EM) simulation tools. This is especially the case for miniaturized devices where EM cross-coupling effects cannot be adequately accounted for using equivalent network models. Unfortunately, EM analysis incurs considerable computational expenses, which becomes a bottleneck whenever multiple evaluations are required. Common simulation-based design tasks include parametric optimization and uncertainty quantification. These can be accelerated using fast replacement models, among which the data-driven surrogates are the most popular. Notwithstanding, a construction of approximation models for microwave components is hindered by the dimensionality issues as well as high nonlinearity of system characteristics. A partial alleviation of the mentioned difficulties can be achieved with the recently reported performance-driven modeling methods, including the nested kriging framework. Therein, the computational benefits are obtained by appropriate confinement of the surrogate model domain, spanned by a set of pre-optimized reference designs, and by focusing on the parameter space region that contains high quality designs with respect to the considered performance figures. This paper presents a methodology that incorporates the concept of nested kriging and enhances it by explicit dimensionality reduction based on spectral decomposition of the reference design set. Extensive verification studies conducted for a compact rat-race coupler and a three-section impedance matching transformer demonstrate superiority of the presented approach over both the conventional techniques and the nested kriging in terms of modeling accuracy. Design utility of our surrogates is corroborated through application cases studies. INDEX TERMS Microwave design; compact circuits; surrogate modeling; domain confinement; principal component analysis; dimensionality reduction.

show abstract

“…On the other hand, simulation models are frequently used in the design process itself, e.g., for tuning geometry parameters [8] or uncertainty quantification [9], [10]. EM-based design tasks are solved using numerical optimization [11] and modelling methods [12], which is mainly due to inadequacy of traditional EM-based techniques (e.g., supervised parameter sweeping) that are unable to handle multiple parameters, performance requirements, and constraints. Miniaturized microwave passives are representative examples of structures where EM-driven design closure is mandatory due to a typically large-compared to conventional transmission line (TL)based circuits-number of geometry parameters, and strong cross-coupling effects being a result of the employment of TL folding [13] or compact building blocks involving slowwave phenomenon [14] (e.g., compact microwave resonant cells, CMRCs [15]).…”

Section: Introductionmentioning

confidence: 99%

Improved-Efficacy Optimization of Compact Microwave Passives by Means of Frequency-Related Regularization

2020

Self Cite

View full text Add to dashboard Cite

Electromagnetic (EM)-driven optimization is an important part of microwave design, especially for miniaturized components where the cross-coupling effects in tightly arranged layouts make traditional (e.g., equivalent network) representations grossly inaccurate. Efficient parameter tuning requires reasonably good initial designs, which are difficult to be rendered for newly developed structures or when redesign for different operating conditions or material parameters is required. If global search is needed, due to either the aforementioned issues or multi-modality of the objective function, the computational cost of the EM-driven design increases tremendously. This paper introduces a frequency-related regularization as a way of improving the efficacy of simulation-based design processes. Regularization is realized by enhancing the conventional (e.g., minimax) objective function using a dedicated penalty term that fosters the alignment of the circuit characteristics (e.g., the operating frequency or bandwidth) with the target values specified by the design requirement. This leads to smoothening of the objective function landscape, improves reliability of the optimization process, and reduces its computational cost as compared to the standard formulation. An added benefit is the increased immunity to poor initial designs and multi-modality issues. In particular, regularization can make local search routines sufficient in situations where global optimization would normally be necessary. The presented approach is validated using two miniaturized circuits, a rat-race and a branch line coupler. The numerical results demonstrate its superiority over conventional design problem formulations in terms of reliability of the optimization process. INDEX TERMS Microwave design; miniaturized passive components; design optimization; EM-driven design; gradient-based search; regularization.

show abstract

Performance-driven modeling of compact couplers in restricted domains

Cited by 16 publications

References 12 publications

Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate

Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate

Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits With Dimensionality Reduction

Improved-Efficacy Optimization of Compact Microwave Passives by Means of Frequency-Related Regularization

Contact Info

Product

Resources

About