  This article investigates digital predistortion (DPD) linearization of hybrid
beamforming large-scale antenna transmitters. We propose a novel DPD processing
and learning technique for an antenna sub-array, which utilizes a combined
signal of the individual power amplifier (PA) outputs in conjunction with a
decorrelation-based learning rule. In effect, the proposed approach results in
minimizing the nonlinear distortions in the direction of the intended receiver.
This feature is highly desirable, since emissions in other directions are
naturally weak due to beamforming. The proposed parameter learning technique
requires only a single observation receiver, and therefore supports simple
hardware implementation. It is also shown to clearly outperform the current
state-of-the-art technique which utilizes only a single PA for learning.
Analysis of the feedback network amplitude and phase imbalances reveals that
the technique is robust even to high levels of such imbalances. Finally, we
also show that the array system out-of-band emissions are well-behaving in all
spatial directions, and essentially below those of the corresponding
single-antenna transmitter, due to the combined effects of the DPD and
beamforming.
