Modeling and predistortion of envelope tracking power amplifiers using a memory binomial model

Nowadays envelope tracking (ET) is considered one of the most appealing techniques for the efficiency enhancement of RF power amplifiers (PAs), but it also introduces a number of additional challenges for the system simulation and implementation. In this context, this paper aims to provide a new behavioral model capable of an improved performance when used for the modeling and predistortion of RF PAs deployed in ET transceivers. The proposed solution consists in a 2D behavioral model having as a dual-input the PA complex baseband envelope and the modulated supply waveform, peculiar of the ET case. The model definition is based on binomial series, hence the name of memory binomial model (MBM). The MBM is here applied to measured data-sets acquired from an ET measurement set-up. When used as a PA model the MBM showed an NMSE (Normalized Mean Squared Error) as low as -40dB and an ACEPR (Adjacent Channel Error Power Ratio) below -51 dB. The simulated predistortion results showed that the MBM can improve the compensation of distortion in the adjacent channel of 5.8 dB and 5.7 dB compared to a memory polynomial predistorter (MPPD). The predistortion performance in the time domain showed an NMSE improvement of 2.5 dB against the MPPD.