Digital Predistortion for 5G Small Cell: GPU Implementation and RF Measurements

被引：11

作者：

Pascual Campo, Pablo ^{[1
]}

Lampu, Vesa ^{[1
]}

Meirhaeghe, Alexandre ^{[2
]}

Boutellier, Jani ^{[2
,3
]}

Anttila, Lauri ^{[1
]}

Valkama, Mikko ^{[1
]}

机构：

[1] Tampere Univ, Dept Elect Engn, Tampere, Finland

[2] Tampere Univ, Dept Comp Sci, Tampere, Finland

[3] Univ Vaasa, Dept Comp Sci, Vaasa, Finland

来源：

JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY | 2020年 / 92卷 / 05期

关键词：

Digital predistortion (DPD); 5G; GPU; Real-time; High data rate; LOW-COMPLEXITY; MODEL;

D O I：

10.1007/s11265-019-01502-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present a high data rate implementation of a digital predistortion (DPD) algorithm on a modern mobile multicore CPU containing an on-chip GPU. The proposed implementation is capable of running in real-time, thanks to the execution of the predistortion stage inside the GPU, and the execution of the learning stage on a separate CPU core. This configuration, combined with the low complexity DPD design, allows for more than 400 Msamples/s sample rates. This is sufficient for satisfying 5G new radio (NR) base station radio transmission specifications in the sub-6 GHz bands, where signal bandwidths up to 100 MHz are specified. The linearization performance is validated with RF measurements on two base station power amplifiers at 3.7 GHz, showing that the 5G NR downlink emission requirements are satisfied.

引用

页码：475 / 486

页数：12

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