Detection of Impaired OFDM Waveforms Using Deep Learning Receiver

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

15 Lataukset (Pure)

Abstrakti

With wireless networks evolving towards mmWave and sub-THz frequency bands, hardware impairments such as IQ imbalance, phase noise (PN) and power amplifier (PA) nonlinear distortion are increasingly critical implementation challenges. In this paper, we describe deep learning based physical-layer receiver solution, with neural network layers in both time- and frequency-domain, to efficiently demodulate OFDM signals under coexisting IQ, PN and PA impairments. 5G NR standard-compliant numerical results are provided at 28 GHz band to assess the receiver performance, demonstrating excellent robustness against varying impairment levels when properly trained.

AlkuperäiskieliEnglanti
Otsikko2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication, SPAWC 2022
KustantajaIEEE
ISBN (elektroninen)9781665494557
ISBN (painettu)9781665494564
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE International Workshop on Signal Processing Advances in Wireless Communication - Oulu, Suomi
Kesto: 4 heinäk. 20226 heinäk. 2022

Julkaisusarja

NimiSPAWC
ISSN (painettu)1948-3244
ISSN (elektroninen)1948-3252

Conference

ConferenceIEEE International Workshop on Signal Processing Advances in Wireless Communication
Maa/AlueSuomi
KaupunkiOulu
Ajanjakso4/07/226/07/22

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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