A simplified adaptive digital predistorter for a high power amplifier with memory effects based on direct learning architecture

This paper presents an adaptive Digital Predistorter (DPD) to handle the nonlinearity and memory challenges that effect the transmitted signal in High Power Amplifier (HPA) system. The proposed scheme first handles the nonlinearity effect by estimating the reverse error, then the obtained signal is processed by the FIR filter to diminish the memory effect. The simulation results of the proposed method present a superior performance compared with state-of-the-art methods used in compensating nonlinearity and memory effects. These results suggest that the proposed approach is more suitable to transmit a standard signal with less error by using traditional HPA.