On Computationally-Efficient Reference Design Acquisition for Reduced-Cost Constrained Modeling and Re-Design of Compact Microwave Passives

2023

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Re-design of microwave passive components for the assumed operating frequencies or substrate parameters is an important yet a tedious process. It requires simultaneous tuning of relevant circuit variables, often over broad ranges thereof, to ensure satisfactory performance of the system. If the operating conditions at the available design are distant from the intended ones, local optimization is typically insufficient, whereas global search entails excessive computational expenses. The problem is aggravated for miniaturized components, typically featuring large numbers of geometry parameters. Furthermore, owing to their tightly-arranged layouts, compact structures exhibit considerable cross-coupling effects. In order to reliably evaluate electrical characteristics under such conditions full-wave electromagnetic (EM) analysis is mandatory. Needless to say, EM-driven design over broad ranges of operating frequencies is an arduous and costly endeavor. In this paper, we introduce a novel procedure for rapid and reliable re-design of microwave passives. Our methodology involves concurrent scaling of geometry parameters interleaved with local (gradient-based) tuning. The scaling stage allows for low-cost relocation of the operating frequencies of the circuit, whereas the optimization stage ensures continuous (iteration-wise) alignment of the performance figures with their target values. The presented framework is validated using several miniaturized microstrip couplers, re-designed over extended ranges of the center frequencies. For all considered structures, satisfactory designs are successfully identified despite the initial designs being distant from the targets, whereas local tuning turns out to be demonstrably inferior. Apart from its efficacy, one of the most important advantages of the proposed framework is its simplicity, and the lack of problem-dependent control parameters.

Section: Circuit Re-design Using Concurrent Scaling and Intermittent ...mentioning

confidence: 99%

“… $ The coefficient β > 0 is a penalty factor that controls the contribution of the penalty terms to the merit function 82 . …”

Section: Circuit Re-design Using Concurrent Scaling and Intermittent ...mentioning

confidence: 99%

Rapid and reliable re-design of miniaturized microwave passives by means of concurrent parameter scaling and intermittent local tuning

2023

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“…Also, EM simulation results may contain a certain level of numerical noise, being a result of adaptive meshing techniques, or specific termination criteria used by the EM solvers. As mentioned before, a common mitigation method is a penalty function approach 47 , where the cost function is defined through aggregation of the main objective (size reduction) and contributions from constraint violations, appropriately scaled using weighting factors (penalty coefficients). Although conceptually attractive, optimum setup of the coefficient values is generally an intricate task, often associated with preparatory optimization runs.…”

Section: Miniaturization Of Microwave Passives With Direct Constraint...mentioning

confidence: 99%

“…Consequently, straightforward constraint handling is inconvenient. A widely used alternative is to incorporate penalty functions 47 , in which the main objective (size reduction) is supplemented with a linear combination of appropriately quantified constraint violations 48 . The advantage of this approach is problem reformulation, so that it becomes a formally unconstrained endeavor.…”

Section: Introductionmentioning

confidence: 99%

Direct constraint control for EM-based miniaturization of microwave passives

2022

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Handling constraints imposed on physical dimensions of microwave circuits has become an important design consideration over the recent years. It is primarily fostered by the needs of emerging application areas such as 5G mobile communications, internet of things, or wearable/implantable devices. The size of conventional passive components is determined by the guided wavelength, and its reduction requires topological modifications, e.g., transmission line folding, or utilization of compact cells capitalizing on the slow-wave phenomenon. The resulting miniaturized structures are geometrically complex and typically exhibit strong cross coupling effects, which cannot be adequately accounted for by analytical or equivalent network models. Consequently, electromagnetic (EM)-driven parameter tuning is necessary, which is computationally expensive. When the primary objective is size reduction, the optimization task becomes far more challenging due to the presence of constraints related to electrical performance figures (bandwidth, power split ratio, etc.), which are all costly to evaluate. A popular solution approach is to utilize penalty functions. Therein, possible violations of constraints degrade the primary objective, thereby enforcing their satisfaction. Yet, the appropriate setup of penalty coefficients is a non-trivial problem by itself, and is often associated to extra computational expenses. In this work, we propose an explicit approach to constraint handling, which is combined with the trust-region gradient-search procedure. In our technique, the decision about the adjustment of the search radius is determined based on the reliability of rendering the feasible region boundary by linear approximation models of the constraints. Comprehensive numerical experiments conducted using three miniaturized coupler structures demonstrate superiority of the presented method over the penalty function paradigm. Apart from the efficacy, its appealing features include algorithmic simplicity, and no need for tailoring the procedure for a particular circuit to be optimized.

“…As mentioned earlier, the number of trial points can be reduced by exploiting the sensitivity information 72 , whereas their identification costs may be diminished by warm-start optimization algorithms (e.g. 76 ).…”

Section: Introductionmentioning

confidence: 99%

Two-stage variable-fidelity modeling of antennas with domain confinement

Golunski

2022

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Surrogate modeling has become the method of choice in solving an increasing number of antenna design tasks, especially those involving expensive full-wave electromagnetic (EM) simulations. Notwithstanding, the curse of dimensionality considerably affects conventional metamodeling methods, and their capability to efficiently handle nonlinear antenna characteristics over broad ranges of the system parameters is limited. Performance-driven (or constrained) modeling frameworks may be employed to mitigate these issues by considering a construction of surrogates from the standpoint of the antenna performance figures rather than directly geometry parameters. This permits a significant reduction of the model setup cost without restricting its design utility. This paper proposes a novel modeling framework, which capitalizes on the domain confinement concepts and also incorporates variable-fidelity EM simulations, both at the surrogate domain definition stage, and when rendering the final surrogate. The latter employs co-kriging as a method of blending simulation data of different fidelities. The presented approach has been validated using three microstrip antennas, and demonstrated to yield reliable models at remarkably low CPU costs, as compared to both conventional and performance-driven modeling procedures.