This paper presents an adaptive digital predistortion (DPD) linearizer for user equipment (UE) power amplifiers (PAs) assuming a realistic 5G scenario with dynamic frequency and signal bandwidth reallocation and frequent voltage standing wave ratio (VSWR) variations. The DPD model is composed of a well-matched DPD model and an adaptive mismatched DPD model. The well-matched model is scalable and bandwidth- and frequency-dependent. For every frequency and bandwidth of interest, it provides the best trade-off between computational complexity and linearization performance, optimized for the PA operating under well-matched condition. We demonstrate that a proper well-matched DPD model can also reduce the complexity and challenges associated with the mismatched DPD model. To address the uncertain behavior of PA mismatching, the mismatched DPD model is designed to be simple and adaptable. It includes a finite impulse response (FIR) filter with two memory taps to compensate for the reflected wave and a memoryless AM-AM and AM-PM nonlinear model to handle changes in the nonlinear behavior. The linearization performance is evaluated on a PA system-on-chip (SoC), considering 5G new radio signals at different frequency locations and with different signal bandwidths, i.e., ranging from 5 MHz to 100 MHz contiguous bandwidth along a 300 MHz channel around a center frequency of 3.65 GHz. Experimental robustness tests show the benefits of the proposed method, allowing the adaptation to be conducted less frequently or only on-demand while always meeting the linearization specifications.

This work was supported in part by Huawei Technologies from July 2023 to August 2024, in part by MCIN/AEI/10.13039/50110001103 under Project PID2020-113832RB-C21, in part by MICIU/AEI/ 10.13039/501100011033/FEDER, UE, under project PID2023-146245OB- C21, in part by the Government of Catalonia, and in part by the European Social Fund under Grant 2021-FI-B-137.

Peer Reviewed