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Joint Transceiver Design for Full-Duplex Amplify-and-Forward Cooperative Systems with Frequency-Selective Fading Channels

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

1 Scopus citations

Abstract

To boost the spectral efficiency of cooperative communication systems, full duplex relays (FDRs) have been widely considered due to the concurrent signal transmission and reception at the relay. However, the self-interference (SI) is always a main problem that deteriorates the system performance. Most conventional FDR designs focus on narrowband transmission and treat SI as a harmful signal, consequently aiming to cancel SI as clear as possible. However, the relay transceiver can be inherently modeled as an infinite impulse response (IIR) filter by recognizing SI as a delayed desired signal. Based on this concept, we propose a novel design where the finite-length source, FDR filters, and the linear minimum mean-squared error (MMSE) equalizer are jointly optimized for frequency-selective fading channels. Simulations demonstrate the effectiveness of our design that preserving partial SI indeed enables further performance improvement.

Original languageEnglish
Title of host publication2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728194844
DOIs
StatePublished - Nov 2020
Event92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada
Duration: 18 Nov 2020 → …

Publication series

NameIEEE Vehicular Technology Conference
Volume2020-November
ISSN (Print)1550-2252

Conference

Conference92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
Country/TerritoryCanada
CityVirtual, Victoria
Period18/11/20 → …

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Amplify-and-forward (AF)
  • Frequency selective fading channel
  • Full-duplex relay (FDR)
  • Infinite impulse response (IIR)
  • Joint source/relay filters
  • Minimum mean-squared error (MMSE).
  • Self-interference (SI)

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