HybridDeepRx: Deep Learning Receiver for High-EVM Signals

Jaakko Pihlajasalo, Dani Korpi, Mikko Honkala, Janne M.J. Huttunen, Taneli Riihonen, Jukka Talvitie, Alberto Brihuega, Mikko A. Uusitalo, Mikko Valkama

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

In this paper, we propose a machine learning (ML) based physical layer receiver solution for demodulating OFDM signals that are subject to a high level of nonlinear distortion. Specifically, a novel deep learning based convolutional neural network receiver is devised, containing layers in both time- and frequency domains, allowing to demodulate and decode the transmitted bits reliably despite the high error vector magnitude (EVM) in the transmit signal. Extensive set of numerical results is provided, in the context of 5G NR uplink incorporating also measured terminal power amplifier characteristics. The obtained results show that the proposed receiver system is able to clearly outperform classical linear receivers as well as existing ML receiver approaches, especially when the EVM is high in comparison with modulation order. The proposed ML receiver can thus facilitate pushing the terminal power amplifier (PA) systems deeper into saturation, and thereon improve the terminal power-efficiency, radiated power and network coverage.

Original languageEnglish
Title of host publication2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021
PublisherIEEE
Pages622-627
Number of pages6
ISBN (Electronic)9781728175867
DOIs
Publication statusPublished - 13 Sept 2021
Publication typeA4 Article in conference proceedings
EventIEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications - Helsinki, Finland
Duration: 13 Sept 202116 Sept 2021

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume2021-September
ISSN (Electronic)2166-9589

Conference

ConferenceIEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications
Country/TerritoryFinland
CityHelsinki
Period13/09/2116/09/21

Keywords

  • 5G NR
  • deep learning
  • EVM
  • machine learning
  • nonlinear distortion
  • OFDM
  • power amplifier
  • power-efficiency

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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