Iterative frequency offset estimation based on singular value decomposition

Masataka Hasebe, Satoshi Denno, Shigeru Tomisato, Masaharu Hata

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

3 Citations (Scopus)

Abstract

This paper proposes an iterative frequency offset estimation based on singular value decomposition (SVD). The proposed technique achieves high resolution estimation of frequency offset even in the presence of strong co-channel and inter-symbol interference. Moreover, the proposed technique can estimate large frequency offset, e.g., ΔfT = 12.8 with high precision. The proposed technique comprises two new ideas. One is frequency offset estimation by using SVD and an adaptive filter. The other is iteration of the above frequency offset estimation followed by a frequency offset reduction. The iteration of the frequency offset estimation improves the estimation performance. In fact, it is evaluated by computer simulation that estimate the frequency offset normalized by a symbol duration, ΔfT = 12.8, in wireless sensor networks with direct sequence spread spectrum (DS-SS).

Original languageEnglish
Title of host publicationISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems
Pages125-130
Number of pages6
DOIs
Publication statusPublished - Dec 1 2013
Event2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013 - Naha, Okinawa, Japan
Duration: Nov 12 2013Nov 15 2013

Publication series

NameISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems

Other

Other2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013
Country/TerritoryJapan
CityNaha, Okinawa
Period11/12/1311/15/13

Keywords

  • co-channel interference
  • frequency offset
  • sensor network
  • singular value decomposition

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing

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