Periodic Interference Cancellation With Drift Estimation Based on Super-Resolution Techniques in Frequency Domain

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

Abstract

This paper proposes a novel interference cancellation technique that keeps radio receivers from periodic interference signals caused by electromagnetic waves emitted from high power circuits. The proposed technique cancels periodic interference signals in the frequency domain, even if the periodic interference signals are drifted in the time domain. We propose a drift estimation based on a super resolution technique such as ESPRIT. The proposed technique employs a linear filter based on the minimum mean square error criterion with assistance of the estimated drifts for the interference cancellation. The performance of the proposed technique is confirmed by computer simulation. The proposed technique achieves a gain of more than 40 dB at the higher frequency index.

Original languageEnglish
Title of host publication2022 IEEE 95th Vehicular Technology Conference - Spring, VTC 2022-Spring - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665482431
DOIs
Publication statusPublished - 2022
Event95th IEEE Vehicular Technology Conference - Spring, VTC 2022-Spring - Helsinki, Finland
Duration: Jun 19 2022Jun 22 2022

Publication series

NameIEEE Vehicular Technology Conference
Volume2022-June
ISSN (Print)1550-2252

Conference

Conference95th IEEE Vehicular Technology Conference - Spring, VTC 2022-Spring
Country/TerritoryFinland
CityHelsinki
Period6/19/226/22/22

Keywords

  • Asynchronous interference signals
  • Frequency Domain
  • Minimum mean square Error (MMSE) estimation
  • Periodic Interference
  • Super resolution estimation

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Periodic Interference Cancellation With Drift Estimation Based on Super-Resolution Techniques in Frequency Domain'. Together they form a unique fingerprint.

Cite this