Analysing self interference cancellation in full duplex radios

Nurul H. Mahmood, Imran S. Ansari, Gilberto Berardinelli, Preben Mogensen, Khalid A. Qaraqe

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

18 Citations (Scopus)

Abstract

Full duplex communication promises a theoretical 100% throughput gain by doubling the number of simultaneous transmissions. Such compelling gains are conditioned on perfect cancellation of the self interference power resulting from simultaneous transmission and reception. Generally, self interference power is modelled as a noise-like constant level interference floor. However, experimental validations have shown that the self interference power is in practice a random variable depending on a number of factors such as the surrounding wireless environment and the degree of interference cancellation. In this study, we derive an analytical model for the residual self interference power, and demonstrate various applications of the derived model in analysing the performance of a Full Duplex radio. In general, full duplex communication is found to provide only modest throughput gains over half duplex communication in a dense network scenario with practical self interference cancellation models.

Original languageEnglish
Title of host publication2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467398145
DOIs
Publication statusPublished - 12 Sept 2016
Externally publishedYes
Event2016 IEEE Wireless Communications and Networking Conference, WCNC 2016 - Doha, Qatar
Duration: 3 Apr 20167 Apr 2016

Publication series

NameIEEE Wireless Communications and Networking Conference, WCNC
Volume2016-September
ISSN (Print)1525-3511

Conference

Conference2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Country/TerritoryQatar
CityDoha
Period3/04/167/04/16

Keywords

  • 5G
  • Full duplex
  • interference model
  • self interference model

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