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An Improved Parameter Extraction Optimization Algorithm for RF Devices.

Shengsen Yang¹, Zihan Xu¹, Kun Ren¹

¹Innovation Center for Electronic Design Automation Technology, Hangzhou Dianzi University, Hangzhou 310018, China.

|April 26, 2025

Summary

This summary is machine-generated.

This study introduces an advanced optimization algorithm for radio frequency (RF) device parameter extraction. The new method enhances accuracy and speeds up convergence, outperforming traditional techniques for RF device modeling.

Keywords:

Ka-band filter RF devices deterministic optimization algorithm parameter extraction

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Area of Science:

Electrical Engineering
Computational Electromagnetics

Background:

Parameter extraction for radio frequency (RF) devices is crucial for accurate modeling.
Traditional deterministic optimization algorithms face limitations like low efficiency and convergence instability.
Accurate RF device parameter extraction is essential for designing high-performance RF circuits and systems.

Purpose of the Study:

To propose an improved parameter extraction optimization algorithm for RF devices.
To enhance optimization accuracy, convergence speed, and stability in RF device modeling.
To address the inherent limitations of existing deterministic optimization methods.

Main Methods:

The proposed algorithm integrates parameter classification and correction.
It incorporates gradient-based performance handling, bias-aware updates, and group-based optimization.
Validation was performed using a Ka-band filter performance curve fitting case study.

Main Results:

The algorithm demonstrated enhanced optimization accuracy and accelerated convergence.
It achieved improved stability compared to traditional optimization algorithms.
Curve fitting accuracy and computational efficiency were significantly improved in the case study.

Conclusions:

The developed algorithm offers a superior approach to RF device parameter extraction optimization.
It effectively overcomes the limitations of conventional methods, showing practical application value.
The method provides a more accurate, efficient, and stable solution for RF device modeling.