Linealización de un amplificador balanceado con modulación de carga mediante un predistorsionador digital basado en redes neuronales para comunicaciones en vehículos aereos no tripulados

This final degree project focuses on the analysis and linearization of a load modulated balanced amplifier (LMBA), designed to operate with wide bandwidth signals without degrading the amplifier's efficiency. This type of amplifier can be used in unmanned aerial vehicles that require a high data transmission rate, where it is critical to maintain high levels of efficiency to minimize consumption and maximize flight autonomy, as well as in base stations to be used with the new 5G standard. In this project the parameters involved in the LMBA (the phase shift between the two signals that control the amplifier and the relationship between these two amplitudes) and its effects on the linearity and efficiency are analyzed. In addition, a number of steps are proposed to follow for proper settings and get the most out of this amplifier. Finally, the linearization of the amplifier is performed with a digital predistorter based on an artificial neural network made up of several hidden layers, and these results are compared to the results obtained with the GMP (Generalized Memory Polynomial) method for different LTE signals.