Power Amplifier

Power amplifiers (PAs) are crucial components in wireless communication systems, but their inherent non-linearity degrades signal quality. Current research focuses on mitigating this nonlinearity using digital pre-distortion (DPD), employing advanced machine learning models like deep neural networks (DNNs), including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), for improved accuracy and efficiency. These techniques aim to enhance signal fidelity, reduce power consumption, and improve spectral efficiency, particularly in wideband systems and massive MIMO architectures, leading to more energy-efficient and higher-capacity wireless communication. The development of open-source frameworks and hardware-friendly architectures further accelerates the practical implementation and widespread adoption of these improved PAs.