Expedited Design of Microstrip Antenna Subarrays Using Surrogate-Based Optimization

Koziel, Slawomir; Ogurtsov, Stanislav; Zieniutycz, Włodzimierz; Sorokosz, Lukasz

doi:10.1109/lawp.2014.2313694

Cited by 26 publications

(12 citation statements)

References 11 publications

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“…The successful operation of, for example, the microstrip resonators seems to suggest that basically they are poor radiators [5]. Despite this weakness microstrip antennas have received much attention in the open literatures because of their many unique and attractive properties [6]: low in profile, light in weight, compact and conformable to both planar and non-planar surfaces [2,[7][8][9][10], and easy to fabricate and to be integrated with solidstate devices. This structure has been analyzed extensively in the last two decades, employing a wide variety of techniques, ranging from simple intuitive models to highly sophisticated techniques using the rigorous spectral domain approach with the Galerkin method [1].…”

Section: Introductionmentioning

confidence: 99%

Spectral Domain Analysis of Resonant Characteristics of High Tc Superconducting Rectangular Microstrip Patch Printed on Isotropic or Uniaxial Anisotropic Substrates

Bedra

Fortaki

Messai

et al. 2015

Wireless Pers Commun

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In this paper, radiation characteristics of the perfectly superconducting, or an imperfectly conducting rectangular microstrip, which is printed on isotropic or uniaxial anisotropic substrate are investigated using a Fourier transforms domain in conjunction with the stationary phase method. The effects of uniaxial anisotropy on the resonant frequency, half-power bandwidth, and radiation patterns are investigated as the function of anisotropy ratio values of substrate materials. It is found that the resonant frequency and the half-power bandwidth are affected significantly by the superconductivity property of the patch. Further results show that a thin superconductor patch has a significant effect on the radiation pattern. Results are compared with previously published data and are found to be in good agreement.

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Section: Introductionmentioning

confidence: 99%

Spectral Domain Analysis of Resonant Characteristics of High Tc Superconducting Rectangular Microstrip Patch Printed on Isotropic or Uniaxial Anisotropic Substrates

Bedra

Fortaki

Messai

et al. 2015

Wireless Pers Commun

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“…Accuracy: Several methods are used in the domain of functional surrogate modeling techniques: [262][263][264] support vector machine, 265 kriging, 266 polynomial-based surrogate modeling, 267 and shape-preserving response. 268 Among these methods, AI methods including ANN and DNN 269 have become the most successful optimization techniques in communications and signal processing, according to the studied literature.…”

Section: Trading Off Between Accuracy and Speedmentioning

confidence: 99%

Overview of evolutionary algorithms and neural networks for modern mobile communication

Kouhalvandi

Shayea

Özoğuz

et al. 2022

Trans Emerging Tel Tech

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The sixth generation (6G) of mobile networks must support the huge growth of mobile connections and provides various intelligent services in future mobile networks. For that, designing high-performance network architecture and communication systems (CSs) as well as finding coherent solutions for the determined problems is critical demand that needs to be achieved in 6G networks.Optimal solutions are mainly sought by using modifiable, smart, and perceptive algorithms aimed at optimizing more specific tasks. Therefore, advanced optimization methods are highly required to accommodate the requirements of CSs efficiently. That will be in various parts of the future networks such as advanced mobility management, multi communication links, efficient power consumption, ultra-lower latency, ultra-security, high speed, and reliable connectivity.Accordingly, highly accurate and smart functions must be modeled to optimize the required communication parameters in the network. This study provides a comprehensive overview of optimization methods that may need further investigations and developments to be applied in 6G networks at various parts of networks. A detailed theoretical description for each method is presented and discussed to elucidate future research directions for optimizing specific characteristics with multi-objective optimizations. Moreover, this article illustrates the conceptual and structural viewpoints of reported optimization methods. Also, the capability of various optimization methods that can offer industrial solutions in 6G is discussed. The potential applications of each method are also analyzed. Finally, this article presented the research issues and future directions of optimization technology and research gaps that need to be addressed before the standardization of 6G networks. INTRODUCTIONRecently, innovative solutions of communication systems (CSs) have been developed impressively, as data traffic is increasing exponentially by more than 50% per year. 1 Several factors will contribute for increasing data demand massively, for example, as predicted by CISCO, the video will make up 82% of the all IP traffic by 2022. 2,3 This massive increase in data traffic will cause several new issues that will facing the implementation of future mobile networks. That will include a dramatic increase for wider spectrum need, 4 the necessity for big system capacity, 5 further mobility issues, 6,7 and higher energy consumption, 8 in which cannot be handled efficiently by the current cellular networks.

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“…Simultaneous handling of both radiation and reflection responses results in two‐objective problem, which is scalarized here by optimizing the SLL directly and ensuring a safe level of reflection using suitable penalty functions . The objective function takes the form (similar to the one used in ):

H ({boldR}_{f} (x)) = U_{SLL} + β \cdot \max_{n = 1, ..., N} {| S_{n} |_{f_{0}} + 10, 0}^{2}

…”

Section: Design Using Optimization Of Simulation‐based Surrogate Modelsmentioning

confidence: 99%

Phase-spacing optimization of linear microstrip antenna arrays using simulation-based surrogate superposition models

Koziel

Ogurtsov

2015

Int J RF and Microwave Comp Aid Eng

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A technique for simulation-driven optimization of the phase excitation tapers and spacings for linear arrays of microstrip patch antennas is presented. Our technique exploits two models of the array under optimization: an analytical model which is based on the array factor, as well as an electromagnetic (EM) simulation-based surrogate model of the entire array. The former is used to provide initial designs which meet the design requirements imposed on the radiation response. The latter is used for tuning of the array radiation response while controlling the array reflection response as well as for validation of the final design. Furthermore, the simulation-based surrogate model allows for subsequent evaluation of the array responses in the beam scanning operation at negligible computational costs. The simulation-based surrogate model is constructed with a superposition of simulated radiation and reflection responses of the array under design with only one radiator active at a time. Low computational cost of the surrogate model is ensured by the EM-simulation data computed with coarse meshes. Reliability of the model is achieved by means of suitable correction carried out with respect to the high-fidelity array model. The correction is performed iteratively in the optimization process. Performance, numerical efficiency, and accuracy of the technique is demonstrated with radiation pattern synthesis of linear arrays comprising 32 microstrip patch antennas by phase-spacing optimization. Properties of the optimal designs in the beam scanning operation are then studied using the superposition models and compared to suitably selected reference designs. The proposed technique is versatile as it also can be applied for simulation-based optimization of antenna arrays comprising other types of individually fed elements. V C 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:536-547, 2015.

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Expedited Design of Microstrip Antenna Subarrays Using Surrogate-Based Optimization

Cited by 26 publications

References 11 publications

Spectral Domain Analysis of Resonant Characteristics of High Tc Superconducting Rectangular Microstrip Patch Printed on Isotropic or Uniaxial Anisotropic Substrates

Spectral Domain Analysis of Resonant Characteristics of High Tc Superconducting Rectangular Microstrip Patch Printed on Isotropic or Uniaxial Anisotropic Substrates

Overview of evolutionary algorithms and neural networks for modern mobile communication

Phase-spacing optimization of linear microstrip antenna arrays using simulation-based surrogate superposition models

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