Behavioral modeling of RF power amplifiers based on SVM

Abstract

RF power amplifiers (PA) are a major source of nonlinearity in a communication system. Accurate behavioral models are indispensable for PA linearization. To describe nonlinear characteristics of power amplifiers, a support vector machine (SVM) based modeling method is presented. The kernel approach and duality theory are employed to train the PA model. Simulation results show that the proposed model provides more accurate prediction of PA output signal compared with classic neural network models.