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arXiv 1804.02178eess.SP
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混合MIMO发射机的数字预失真

Digital Predistortion for Hybrid MIMO Transmitters

Mahmoud Abdelaziz, Lauri Anttila, Alberto Brihuega, Fredrik Tufvesson, Mikko Valkama

备注：
Accepted for publication in IEEE Journal of Selected Topics in Signal Processing
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摘要：

本文研究了混合波束形成大规模天线发射机的数字预失真（DPD）线性化。我们提出了一种新的DPD处理和学习技术的天线子阵列，它利用了一个组合的信号的各个功率放大器（PA）的输出结合基于去相关的学习规则。实际上，所提出的方法导致在预期接收器的方向上的非线性失真最小化。该特征是非常期望的，因为其他方向上的发射由于波束成形而自然较弱。所提出的参数学习技术只需要一个单一的观察接收器，因此支持简单的硬件实现。它也被证明是明显优于目前的国家的最先进的技术，它只利用一个单一的PA学习。反馈网络的幅度和相位不平衡的分析表明，该技术是强大的，甚至高水平的这种不平衡。最后，我们还表明，阵列系统的带外发射在所有空间方向上都表现良好，基本上低于相应的单天线发射机，由于DPD和波束成形的综合效应。

英文摘要：

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.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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