Multidimensional mappings for iteratively decoded BICM on multiple-antenna channels

Nicolas Gresset, Joseph Boutros, Loïc Brunel

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Multidimensional binary mappings for bit-interleaved coded modulations (BICMs) on ergodic multiple-antenna channels with iterative decoding are presented. After derivation of a closed-form expression for the pairwise error probability under ideal maximum-likelihood (ML) decoding, the design criterion for mapping optimization is established from the ML performance of the ideally interleaved channel. It coincides with the figure of merit derived from the genie condition when the iterative receiver converges to perfecta prion information. Multidimensional mapping constructions that exhibit high signal-to-noise ratio (SNR) gains without increasing the complexity of the a posterion probability (APP) detection are proposed. They allow for a reduced decoding complexity as they achieve near turbo code performance with a single convolutional code.

Original languageEnglish
Pages (from-to)3337-3346
Number of pages10
JournalIEEE Transactions on Information Theory
Volume51
Issue number9
DOIs
Publication statusPublished - 1 Sep 2005
Externally publishedYes

Fingerprint

Modulation
Antennas
Maximum likelihood
Decoding
performance
Iterative decoding
Turbo codes
Convolutional codes
recipient
Signal to noise ratio
Prions
Error probability

Keywords

  • Binary mapping
  • Bit-interleaved coded modulation
  • Multiple-antenna channels
  • Pairwise error probability

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Cite this

Multidimensional mappings for iteratively decoded BICM on multiple-antenna channels. / Gresset, Nicolas; Boutros, Joseph; Brunel, Loïc.

In: IEEE Transactions on Information Theory, Vol. 51, No. 9, 01.09.2005, p. 3337-3346.

Research output: Contribution to journalArticle

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