Statistical Digital Predistortion of 5G Millimeter-Wave RF Beamforming Transmitter Under Random Amplitude Variations

The nonlinearity of the fifth-generation (5G) millimeter-wave (mmWave) phased array transmitter (TX) depends on variations in beamforming coefficients, e.g., due to unwanted amplitude errors phase shifters or purposely introduced shape beam, as well other analog component variations. Therefore, also digital predistortion (DPD) coefficients depend and require a continuous update for different beamsteering directions conventional DPD. We propose robust DPD approach that uses average response training. is estimated using known experimental histogram power amplifier (PA) input variation resulting from beamforming. training based makes insensitive proposed strategy requires shared feedback path only single set linearize all directions. performance validated by over-the-air (OTA) measurements 28-GHz TX over steering angles. Experimental results show method one provides similar linearization across angles compared with trained through OTA reference antenna.