Physics-informed neural network assisted automated design of power amplifier by user defined specifications

IF 1.6 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC International Journal of Numerical Modelling-Electronic Networks Devices and Fields Pub Date : 2024-05-22 DOI:10.1002/jnm.3246

Gaurav Bhargava, Hemant Kumari, Valeria Vadalà, Shubhankar Majumdar, Giovanni Crupi

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Abstract

This article presents a model that can automatically produce a power amplifier's (PA) design parameters, that is, transmission lines (TLs) dimension, from a dataset of user-specified design goals like gain, efficiency, linearity, and scattering (S-) parameters. Based on the applied boundary conditions, a synthetic dataset is generated with the best range of design parameters (W and L). This dataset is utilized for training the physics-informed neural network (PINN) model with user-specified design goals as input and design parameters as target to produce the optimum value of W and L as the resultant output. Furthermore, utilizing the obtained dimensions, design, simulation, fabrication, and measurement of a PA are performed to validate our proposed model. The results of large signal measurements of PA are drain efficiency (DE) of 26.9%, power added efficiency (PAE) of 24.7%, output power (P_out) of 30.98 dBm at an input power $(P_{in})$ of 19 dBm, and gain of 12.41 dB at an operating frequency of 1.625 GHz. It has been observed that the design parameters produced by the model have a significant agreement with the validated output. Also, the statistical error analysis is done by calculating the error metrics between the validated output and the actual output of the PA design.

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由用户定义规格的物理信息神经网络辅助自动设计功率放大器

本文介绍了一种模型，该模型可根据用户指定的增益、效率、线性度和散射（S-）参数等设计目标数据集，自动生成功率放大器（PA）的设计参数，即传输线（TL）尺寸。根据应用的边界条件，生成具有最佳设计参数范围（W 和 L）的合成数据集。利用该数据集，以用户指定的设计目标为输入，以设计参数为目标，训练物理信息神经网络（PINN）模型，以产生 W 和 L 的最佳值作为结果输出。此外，利用获得的尺寸，对功率放大器进行了设计、模拟、制造和测量，以验证我们提出的模型。功率放大器的大信号测量结果为：漏极效率 (DE) 为 26.9%，功率附加效率 (PAE) 为 24.7%，输入功率 P in $$\left({P}_{in}\right) $$$ 为 19 dBm 时的输出功率 (Pout) 为 30.98 dBm，工作频率为 1.625 GHz 时的增益为 12.41 dB。据观察，该模型生成的设计参数与验证输出具有显著的一致性。此外，还通过计算验证输出与功率放大器设计实际输出之间的误差指标进行了统计误差分析。

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来源期刊

International Journal of Numerical Modelling-Electronic Networks Devices and Fields 工程技术-工程：电子与电气

CiteScore

4.60

自引率

6.20%

发文量

101

审稿时长

>12 weeks

期刊介绍： Prediction through modelling forms the basis of engineering design. The computational power at the fingertips of the professional engineer is increasing enormously and techniques for computer simulation are changing rapidly. Engineers need models which relate to their design area and which are adaptable to new design concepts. They also need efficient and friendly ways of presenting, viewing and transmitting the data associated with their models. The International Journal of Numerical Modelling: Electronic Networks, Devices and Fields provides a communication vehicle for numerical modelling methods and data preparation methods associated with electrical and electronic circuits and fields. It concentrates on numerical modelling rather than abstract numerical mathematics. Contributions on numerical modelling will cover the entire subject of electrical and electronic engineering. They will range from electrical distribution networks to integrated circuits on VLSI design, and from static electric and magnetic fields through microwaves to optical design. They will also include the use of electrical networks as a modelling medium.