Efficient Maximum Likelihood Algorithm for Estimating Carrier Frequency Offset of Generalized Frequency Division Multiplexing Systems

Yung Yi Wang*, Bo Rui Chen, Chih Hsiang Hsu

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

Abstract

This study presents a computationally efficient maximum likelihood (ML) algorithm for estimating the carrier frequency offset (CFO) of generalized frequency division multiplexing systems. The proposed algorithm uses repetitive subsymbols and virtual carriers to estimate the fractional and integer CFOs, respectively. Through the use of repetitive subsymbols, this study first calculates the ML estimate of the fractional CFO in the time domain and then, accordingly, compensates for it from the received signal. The integer CFO can then be estimated through a virtual-carrier-mapping process in the frequency domain. In addition to improving performance in terms of estimation accuracy and computational complexity, the proposed non-data-aided algorithm is spectrally efficient relative to traditional algorithms.

Original languageEnglish
Article number3426
JournalMathematics
Volume11
Issue number15
DOIs
StatePublished - 08 2023

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

Keywords

  • frequency synchronization
  • generalized frequency division multiplexing systems
  • maximum likelihood estimation
  • multicarrier modulations
  • null space

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