Linear-Decomposition Digital Predistortion of Power Amplifiers for 5G Ultrabroadband Applications

• Published in: IEEE transactions on microwave theory and techniques Vol. 68; no. 7; pp. 2833 - 2844
• Main Authors: Yu, Chao, Lu, Qianyun, Yin, Hang, Cai, Jialin, Chen, Jixin, Zhu, Xiao-Wei, Hong, Wei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Aliasing; Bandwidths; Broadband; Broadband communication; Complexity; Complexity theory; Decomposition; Digital predistortion (DPD); Floating point arithmetic; Linearization; Mathematical model; Millimeter wave communication; Millimeter wave technology; Millimeter waves; millimeter-wave; Oversampling; Power amplifiers; power amplifiers (PAs); Predistortion; ultrabroadband; Waveforms
• ISSN: 0018-9480; 1557-9670
• DOI: 10.1109/TMTT.2020.2975637

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 <inline-formula> <tex-math notation="LaTeX">1.5\times </tex-math></inline-formula>. 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.