Linear minimum-mean-squared error estimation of phase noise, which has a symmetric levy distribution and a possibly large magnitude, from observables at irregular instants

Yeong Tzay Su, Yang Song, Kainam Thomas Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


This study extends an algorithm, previously proposed by the present authors, for 'linear minimum-mean-squared error' estimation of phase noise of (possibly) temporal non-stationarity, large magnitude, 'non'-identical increments that have a Levy distribution, of which the Wiener distribution represents a special case. This estimator-taps may be pre-set to any number, may be pre-computed offline with no matrix inversion, based on the prior knowledge of only the signal-to-(additive)- noise ratio and the phase-noise's characteristic function. That estimator may be set to various degrees of latency. This is here generalised to allow observables at irregular time-instants (e.g. because of the irregular placement of pilot symbols in the transmitted waveform), under which the phase-noise increments become non-identically distributed. This study handles this more complicated scenario.
Original languageEnglish
Pages (from-to)1487-1496
Number of pages10
JournalIET Communications
Issue number14
Publication statusPublished - 24 Sep 2013

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this