A Nonlinear Memory Power Amplifier Behavior Modeling and Identification Based on Memory Polynomial Model in Soft-Defined Shortwave Transmitter

General Volterra series based models have been successfully applied for radio frequency (RF) power amplifier behave-oral modeling, but their high complexity tends to limit their applications to "weakly" nonlinear systems. To model a soft-defined shortwave PA with strong nonlinearities and long memory effects, we propose a memory polynomial model (MP model) which is a simplified Volterra series based model for RF power amplifiers by employing a diagonal pruning algorithm, therefore dramatically reducing the complexity of the behavioral model. The comparison between the simulation results by MP Model and the measured result by the test platform based on DSP and FPGA shows that MP model and adaptive RLS algorithm can describe the nonlinear memory power amplifier behavior characterizes for the soft-defined short-wave amplifier system accurately and effectively. Furthermore, the identification method for soft-defined shortwave transmitter is simple, few parameters, steady algorithm, and practical.