5G/6G大规模MIMO波束形成发射机多角度复杂性降低数字预失真

IF 3.4 0 ENGINEERING, ELECTRICAL & ELECTRONIC
Zehao Chen;Cuiping Yu;Ke Tang;Hao Li;Feifei Li;Xunnan Zhang;Yuanan Liu
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引用次数: 0

摘要

本文提出了一种用于线性化5G/6G大规模多输入多输出(mMIMO)波束成形发射机的多角度数字预失真(DPD)方法。采用由主箱和子箱调谐网络组成的级联结构对主波束和各功率放大器进行线性化。主盒是一种改进的全基传播选择(IFBPS) DPD模型,具有低复杂度和准确的建模特性。子盒调优网络可以根据阈值决策结果,通过与聚类类别相对应的多个异构dpd对pa进行线性化。测量是在基于单用户两流和四链MIMO系统的实验室自制PAs上进行的。结果表明,该方法在不需要实时更新系数的情况下,提高了系统的线性化性能,降低了系统的复杂度,保持了系统的多角度线性度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiangle Complexity-Reduced Digital Predistortion for 5G/6G Massive MIMO Beamforming Transmitters
This letter presents a multiangle digital predistortion (DPD) method for linearizing 5G/6G massive multiple-input–multiple-output (mMIMO) beamforming transmitters. The cascade structure composed of a main box and the subbox tuning network is applied to linearize the main beam and all power amplifiers (PAs). The main box is a proposed improved full basis-propagating selection (IFBPS) DPD model with low complexity and accurate modeling properties. The subbox tuning network can linearize the PAs by several heterogeneous DPDs corresponding to the clustering categories based on the threshold decision results. The measurements were carried out on the laboratory-made PAs based on a single-user two-stream and four-chain MIMO system. Compared with the state-of-the-art DPDs, the results show that the proposed method can improve linearization performance with lower complexity and keep the multiangle linearity of systems without updating the coefficients in real time.
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