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

Pablo Pascual Campo, Vesa Lampu, Alexandre Meirhaeghe, Jani Boutellier, Lauri Anttila, Mikko Valkama

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
55 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)475–486
Number of pages12
JournalJournal of Signal Processing Systems
Volume92
Early online date2019
DOIs
Publication statusPublished - 2020
Publication typeA1 Journal article-refereed

Keywords

  • 5G
  • Digital predistortion (DPD)
  • GPU
  • High data rate
  • Real-time

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Signal Processing
  • Information Systems
  • Modelling and Simulation
  • Hardware and Architecture

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