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Projecte llegit

Títol: Linealització d'un amplificador de potència pseudo-Doherty mitjançant xarxes neuronals

Estudiants que han llegit aquest projecte:


Departament: TSC

Títol: Linealització d'un amplificador de potència pseudo-Doherty mitjançant xarxes neuronals

Data inici oferta: 12-07-2023     Data finalització oferta: 12-03-2024

Estudis d'assignació del projecte:
Tipus: Individual
Lloc de realització: EETAC
Paraules clau:
Amplificador de potència, linealització, models comportamentals, xarxes neuronals
Descripció del contingut i pla d'activitats:
El treball a realitzar durant el projecte consisteix en la linealització d'un amplificador de potència altament eficient, basat en un arquitectura del tipus pseudo-Doherty. Aquesta arquitectura amplificadora requereix de dues entrades de RF, una és la del senyal principal i l'altra és la del senyal de control responsable de dur a terme la modulació de càrrega. Quan s'amplifiquen senyal de gran ample de banda (centenars de MHz) és necessari aplicar tècniques de linealització com la predistorsió digital. En aquest projecte s'estudiarà l'ús de xarxes neuronals per a la predistorsió digital d'aquest amplificador de potència.
Overview (resum en anglès):
The objective of this final year project has been to improve the linearity of power amplifiers (PA) using the digital predistortion (DPD) technique, which is a technique that uses mathematical models that model the behaviour of the PA to linearize it.

Different behavioral models will be worked on and compared, as a correct selection of the PA behavioral model can be important when improving the linearization of the DPD. Among the different models that will be seen during the project, we will delve into artificial neural networks (ANN), which is a technique that is inspired by the behavior of neurons in the human brain. The ANN are characterized by having many hyperparameters or configurations, during this work we will see how each hyperparameters and configurations affect the linearization of the amplifier.

The power amplifier is a critical subsystem in both wireless and wired transmission systems. It is not only one of the components that consumes the most energy in the transmitter, but it is also responsible for the main non-linear effects in the transmitter chain.

Nowadays, DPD (Digital Pre-Distortion) is one of the most used techniques due to its simplicity, its ability to work with large bandwidths, and its high energy efficiency. The main idea of DPD is to apply a pre-distortion to the input signal before it passes through the power amplifier, in such a way that it can counteract the non-linear distortions that the amplifier will subsequently introduce, so that the output signal is as similar as possible to the original signal.

To check the effectiveness of digital predistortion with the use of neural networks and to compare them with other behavioral models, they will be simulated in Matlab and later validated by real hardware in the laboratory. These simulations will allow us to obtain results of values such as the ACPR or EVM, with which we will check if they meet the specifications of the ETSI standard.

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