Maximum Likelihood Decoding for Gaussian Noise Channels with Gain or Offset Mismatch

Jos H. Weber, Kees A. Schouhamer Immink

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)
169 Downloads (Pure)

Abstract

Besides the omnipresent noise, other important inconveniences in communication and storage systems are formed by gain and/or offset mismatches. In the prior art, a maximum likelihood (ML) decision criterion has already been developed for Gaussian noise channels suffering from unknown gain and offset mismatches. Here, such criteria are considered for Gaussian noise channels suffering from either an unknown offset or an unknown gain. Furthermore, ML decision criteria are derived when assuming a Gaussian or uniform distribution for the offset in the absence of gain mismatch.

Original languageEnglish
Pages (from-to)1128-1131
Number of pages4
JournalIEEE Communications Letters
Volume22
Issue number6
DOIs
Publication statusPublished - 2018

Bibliographical note

Accepted Author Manuscript

Keywords

  • Maximum likelihood decoding
  • Euclidean distance
  • Gaussian noise
  • Receivers
  • Maximum likelihood detection
  • Standards

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