Modeling the Behavior of a Power Amplifier for 5G Using Machine Learning
DOI:
https://doi.org/10.52428/20758944.v20i55.1101Keywords:
Machine Learning, ADS, Amplificador, Modelado, 5GAbstract
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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Copyright (c) 2024 Miguel Angel Chiri Yupanqui, Hugo Orlando Condori Quispe
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