Digital self-interference cancellation via dynamic regression for in-band full-duplex system

You Hsien Lin, Yuan Te Liao, Jian Ya Chu, Po Ju Su, Terng-Yin Hsu

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

2 Scopus citations

Abstract

For enhancing spectrum efficiency, in-band full-duplex technology is one of the candidate technical solution. But, self-interference (SI) signal causes dramatically degrade the performance. In practically, memory effect which cause harmonic in amplifier will be hard to be estimated. Therefore, we utilizes the dynamic regression (DR) to implement digital interference cancellation (DIC) for mitigate the memory effect. Two platforms are constructed to evaluate this mechanism. In both platforms, the SI signal could effectively reduction and the residual signal could be attenuated close to noise floor. In software-defined radio (SDR) platform also proves that the proposed dynamic regression based DIC (DRDIC) is sufficient to attenuate the SI signal, where successfully perform video streaming demonstration.

Original languageEnglish
Title of host publication2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509023332
DOIs
StatePublished - 27 Dec 2016
Event5th IEEE Global Conference on Consumer Electronics, GCCE 2016 - Kyoto, Japan
Duration: 11 Oct 201614 Oct 2016

Publication series

Name2016 IEEE 5th Global Conference on Consumer Electronics, GCCE 2016

Conference

Conference5th IEEE Global Conference on Consumer Electronics, GCCE 2016
CountryJapan
CityKyoto
Period11/10/1614/10/16

Keywords

  • In-band full-duplex
  • dynamic regression
  • self-interference cancellation
  • software-defined radio

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