Linear-Decomposition Digital Predistortion of Power Amplifiers for 5G Ultrabroadband Applications
Linear-Decomposition Digital Predistortion of Power Amplifiers for 5G Ultrabroadband Applications
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DOI：
10.1109/tmtt.2020.2975637
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发表时间：
2020-03
影响因子：
4.3
通讯作者：
Chao Yu;Qianyun Lu;H. Yin;Jialin Cai;Jixin Chen;Xiaowei Zhu;W. Hong
中科院分区：
文献类型：
--
作者：
Chao Yu;Qianyun Lu;H. Yin;Jialin Cai;Jixin Chen;Xiaowei Zhu;W. Hong
本文提出了一种新的线性分解数字预失真（LD-DPD）的线性化功率放大器（PA）在超宽带应用。LD-DPD能够以低复杂度在仅为1.5\times $的过采样率下表现出色。它将前导项与交叉项的线性分解相结合，即使在采样率不足的情况下也可以减少频谱混叠。所提出的模型的模型复杂性量化的浮点运算。在低于6 GHz和毫米波频率的宽带PA上进行的实验通过采用5G新无线电（NR）波形对所提出的模型进行了有效验证。特别是，在28 GHz的调制带宽（BW）800 MHz的信号的线性化进行了演示。LD-DPD实现了归一化的均方根误差（NRMSE）为3.34%的连续800 MHz的调制信号，采样率仅为1.2 GHz。与已有的DPD方法相比，该方法在有限的采样率下具有较高的精度，大大降低了系统带宽要求。此外，它的复杂性要低得多，这将减少硬件费用，非常适合5G超宽带应用。
This article proposes a novel linear-decomposition digital predistortion (LD-DPD) for the linearization of power amplifiers (PAs) in ultra broadband applications. LD-DPD is able to perform excellently with low complexity at the oversampling rate of only $1.5\times $ . It combines leading terms with a linear decomposition of cross-terms, which can reduce the spectrum aliasing even when sampling rates are insufficient. The model complexity of the proposed model is quantified by floating-point operations. Experiments on broadband PAs at both sub-6-GHz and millimeter-wave frequencies have provided effective validations of the proposed model by employing the 5G New Radio (NR) waveforms. Particularly, the linearization of a signal with modulated bandwidth (BW) 800 MHz at 28 GHz was demonstrated. LD-DPD achieved a normalized root-mean-square error (NRMSE) of 3.34% for continuous 800-MHz modulated signal at the sampling rate of only 1.2 GHz. Compared with the already published DPDs, the proposed method is featured by high accuracy with limited available sampling rates to significantly reduce the system BW requirements. Also, it presents much lower complexity that will reduce expenses on hardware, which is very suitable for 5G ultra broadband applications.