Modeling the Behavior of a Power Amplifier for 5G Using Machine Learning

Authors

  • Miguel Angel Chiri Yupanqui Universidad Mayor de San Andrés
  • Hugo Orlando Condori Quispe Universidad Mayor de San Andrés

DOI:

https://doi.org/10.52428/20758944.v20i55.1101

Keywords:

Machine Learning, ADS, Amplificador, Modelado, 5G

Abstract

The main purpose of this research is to model the behavior of a radio frequency (RF) amplifier using machine learning techniques. To achieve this goal, we use Keysight's ADS software. First, relevant data from graphs is obtained and transformed into tabular data. This data is essential for training the model. The obtained results show a remarkable agreement with the expected behavior of the RF amplifier, which confirms the effectiveness of the proposed approach. This finding not only validates the feasibility of modeling amplifiers, but also suggests the applicability of these techniques in the modeling of diverse electronic systems with a high degree of accuracy and reliability.

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Published

27-06-2024

How to Cite

Chiri Yupanqui, M. A., & Condori Quispe, H. O. (2024). Modeling the Behavior of a Power Amplifier for 5G Using Machine Learning. Journal Boliviano De Ciencias, 20(55), 6–14. https://doi.org/10.52428/20758944.v20i55.1101

Issue

Section

Applied Engineering Project