In-Band, Full-Duplex Self-Interference Mitigation Using Sparse Tap-Delay Models with Quantized and Power Constrained Weights

Andrew Herschfelt, Alex Chiriyath, Alyosha Christopher Molnar, David G. Landon, Daniel W. Bliss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In-band, full-duplex (IBFD) radio frequency (RF) users generate self-interference that obstructs receiver operations. This interference may be mitigated using several techniques, including antenna isolation, circulators, digital mitigation, and analog mitigation at the carrier frequency. We apply an analog mitigation technique that uses a sparse tap-delay model to reduce power and computational complexity. We demonstrate that optimizing the weights of the resulting equalizer achieves sufficient self-interference mitigation, even under realistic hardware limitations. The performance is limited by i) how many delay taps are chosen, ii) how closely this discrete model matches the actual channel, iii) the dynamic range of the weighting coefficients, and iv) the timing precision of the system. We compare the achievable performance of this technique under different combinations of these limitations. We propose a sparse, constrained optimization solution that offers sufficient self-interference mitigation and significantly reduces the power consumption.

Original languageEnglish (US)
Title of host publicationConference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1260-1264
Number of pages5
ISBN (Electronic)9780738131269
DOIs
StatePublished - Nov 1 2020
Event54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020 - Pacific Grove, United States
Duration: Nov 1 2020Nov 5 2020

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2020-November
ISSN (Print)1058-6393

Conference

Conference54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
Country/TerritoryUnited States
CityPacific Grove
Period11/1/2011/5/20

Keywords

  • channel matching filter
  • constrained optimization
  • full-duplex
  • In-band
  • self-interference mitigation
  • sparse channel estimation

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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