Modelling of Tunable CPW Structure Dielectric Phase Shifters

He, Xin; Kong, Linghui; Zhang, Yunjing

doi:10.1109/iceict51264.2020.9334247

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…There are presented many new structures of antennas [4][5][6], antenna arrays [7,8], filters [9,10], phase shifters [11,12], different resonators [13], delay lines [14], sensor arrays [15] and others. The main research directions are usually considered to be reconfigurability or tenability and miniaturization by searching for new constructions [16] or materials [17]. The miniaturization is especially important for the growing network of internet of things (IoT) devices [18,19].…”

Section: Introductionmentioning

confidence: 99%

Trends of Microwave Devices Design Based on Artificial Neural Networks: A Review

et al. 2022

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The usage of techniques of the artificial neural networks (ANNs) in the field of microwave devices has recently increased. The advantages of ANNs in comparison with traditional full-wave methods are that the prediction speed when the traditional time-consuming iterative calculations are not required and also the complex mathematical model of the microwave device is no longer needed. Therefore, the design of microwave device could be repeated many times in real time. However, methods of artificial neural networks still lag behind traditional full-wave methods in terms of accuracy. The prediction accuracy depends on the structure of the selected neural network and also on the obtained dataset for the training of the network. Therefore, the paper presents a systematic review of the implementation of ANNs in the field of the design and analysis of microwave devices. The guidelines for the systematic literature review and the systematic mapping research procedure, as well as the Preferred Report Items for Systematic Reviews and Meta-Analysis statements (PRISMA) are used to conduct literature search and report the results. The goal of the paper is to summarize the application areas of usage of ANNs in the field of microwave devices, the type and structure of the used artificial neural networks, the type and size of the dataset, the interpolation and the augmentation of the training dataset, the training algorithm and training errors and also to discuss the future perspectives of the usage of ANNs in the field of microwave devices.

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Section: Introductionmentioning

confidence: 99%

Trends of Microwave Devices Design Based on Artificial Neural Networks: A Review

et al. 2022

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Solution of an Electrodynamic Problem for a Homogeneous Equivalent Segment of a Coaxial Load, Considering Heat Losses in the Conductors

Tatarenko

Татаренко

2022

Mathematics

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Mathematical aspects of solving an electrodynamic problem in the field of designing coaxial devices in the microwave range are considered. The solution of the electrodynamic problem for a homogeneous equivalent segment of a coaxial load in the single-mode approximation, considering the heat losses in the central and outer conductors, was obtained. A mathematical model of the microwave load, linking the high-frequency and design-technological parameters of the device, was built. To refine the model, we consider second-order effects associated with considering inhomogeneities that occur in places where the cross-section of the coaxial structure changes. The design of the 50-Ω load and the results of its experimental investigation are presented for comparison with theoretical calculations.

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Modelling of Tunable CPW Structure Dielectric Phase Shifters

Cited by 2 publications

References 18 publications

Trends of Microwave Devices Design Based on Artificial Neural Networks: A Review

Trends of Microwave Devices Design Based on Artificial Neural Networks: A Review

Solution of an Electrodynamic Problem for a Homogeneous Equivalent Segment of a Coaxial Load, Considering Heat Losses in the Conductors

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