Simulation and Performance Optimization of Memory Nonlinear Distortion Compensation Algorithm for Wideband Power Amplifier

Abstract

The power amplifier (PA) is one of the most important nonlinear devices in wireless communication field. The memory-nonlinearity of the PA deteriorates the transmission performance of the communication system. The use of pre-distortion technology can reduce the system performance loss caused by the memory-nonlinearity of the PA. In this paper, the adaptive predistortion technique of PA’s memory-nonlinearity is studied and an adaptive predistortion model based on full kernel Volterra series is established. The parameters of the full-core Volterra predistortion model are identified by LS, RLS, LMS and Kalman filtering algorithms. The four algorithms are deeply optimized with the minimum mean square error (MSE) as an indicator. The simulation results show that the Kalman filtering algorithm has the best parameter identification accuracy. In the noise environment, the adaptive predistorter based on Kalman filter can still effectively compensate the memory-nonlinearity of PA. The research in this paper provides a reference for further understanding and research on adaptive predistortion technology of wireless communication systems.