Improved-Efficacy EM-Based Antenna Miniaturization by Multi-Fidelity Simulations and Objective Function Adaptation

The growing demand for the integration of surface mount design (SMD) antennas into miniaturized electronic devices has imposed increasing limitations on the structure dimensions. Examples include embedded antennas in applications such as on-board devices, picosatellites, 5G communications, or implantable and wearable devices. The demands for size reduction while ensuring a satisfactory level of electrical and field performance can be managed through constrained numerical optimization. The reliability of optimization-based size reduction requires utilization of full-wave electromagnetic (EM) analysis, which entails significant computational costs. This can be alleviated by incorporating surrogate modeling techniques, adjoint sensitivities, or the employment of sparse sensitivity updates. An alternative is the incorporation of multi-fidelity simulation models, normally limited to two levels, low and high resolution. This paper proposes a novel algorithm for accelerated antenna miniaturization, featuring a continuous adjustment of the simulation model fidelity in the course of the optimization process. The model resolution is determined by factors related to violation of the design constraints as well as the convergence status of the algorithm. The algorithm utilizes the lowest-fidelity model for the early stages of the optimization process; it is gradually refined towards the highest-fidelity model upon approaching convergence, and the constraint violations improve towards the preset tolerance threshold. At the same time, a penalty function approach with adaptively adjusted coefficients is applied to enable the precise control of constraints, and to increase the achievable miniaturization rates. The presented procedure has been validated using five microstrip antennas, including three broadband, and two circularly polarized structures. The obtained results corroborate the relevance of the implemented mechanisms from the point of view of improving the average computational efficiency of the optimization process by 43% as compared to the single-fidelity adaptive penalty function approach. Furthermore, the presented methodology demonstrates a performance that is equivalent or even superior to its single-fidelity counterpart in terms of an average constraint violation of 0.01 dB (compared to 0.03 dB for the reference), and an average size reduction of 25% as compared to 25.6%.

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Cost-Efficient EM-Driven Size Reduction of Antenna Structures by Multi-Fidelity Simulation Models

Electronics ◽

10.3390/electronics10131536 ◽

2021 ◽

Vol 10 (13) ◽

pp. 1536

Author(s):

Anna Pietrenko-Dabrowska ◽

Slawomir Koziel

Keyword(s):

Impedance Matching ◽

Trust Region ◽

Simulation Models ◽

Axial Ratio ◽

Microstrip Antennas ◽

Size Reduction ◽

Model Management ◽

Feasible Region ◽

High Fidelity ◽

Fidelity Model

Design of antenna systems for emerging application areas such as the Internet of Things (IoT), fifth generation wireless communications (5G), or remote sensing, is a challenging endeavor. In addition to meeting stringent performance specifications concerning electrical and field properties, the structure has to maintain small physical dimensions. The latter normally requires searching for trade-off solutions because miniaturization has detrimental effects on antenna characteristics, including the impedance matching, gain, efficiency, or axial ratio bandwidth. Furthermore, explicit size reduction is more demanding than optimization with respect to other figures of merit. On the one hand, it is a constrained task with acceptance thresholds set on the bandwidth, gain, etc. On the other hand, optimum solutions are normally located at the boundary of the feasible region, traversing of which is a difficult problem by itself. The necessity of using full-wave electromagnetic (EM) analysis for antenna evaluation only aggravates the problem due to high computational costs associated with numerical optimization algorithms. This paper proposes a procedure for expedited optimization-based miniaturization of antenna structures involving trust-region gradient search and multi-fidelity EM simulations, as well as implicit handling of design constraints using a penalty function approach. The assumed model management scheme is associated with the convergence status of the optimization process with the lowest fidelity model employed at the early stages of the algorithm run and the discretization density of the structure gradually increased to reach the high-fidelity level towards the end of the run. This allows us to achieve a considerable computational speedup without compromising the reliability. Our methodology is demonstrated using two broadband microstrip antennas. The obtained CPU savings exceed seventy percent as compared to the reference procedure involving high-fidelity model only.

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