Lower Bounds on the Error Probability of Block Codes Based on Improvements on de Caen's Inequality

Asaf Cohen, Neri Merhav

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

New lower bounds on the error probability of block codes with maximum-likelihood decoding are proposed. The bounds are obtained by applying a new lower bound on the probability of a union of events, derived by improving on de Caen's lower bound. The new bound includes an arbitrary function to be optimized in order to achieve the tightest results. Since the optimal choice of this function is known, but leads to a trivial and useless identity, we find several useful approximations for it, each resulting in a new lower bound. For the additive white Gaussian noise (AWGN) channel and the binary-symmetric channel (BSC), the optimal choice of the optimization function is stated and several approximations are proposed. When the bounds are further specialized to linear codes, the only knowledge on the code used is its weight enumeration. The results are shown to be tighter than the latest bounds in the current literature, such as those by Seguin and by Keren and Litsyn. Moreover, for the BSC, the new bounds widen the range of rates for which the union bound analysis applies, thus improving on the bound to the error exponent compared with the de Caen-based bounds.

Original languageEnglish
Pages (from-to)290-310
Number of pages21
JournalIEEE Transactions on Information Theory
Volume50
Issue number2
DOIs
StatePublished - 1 Feb 2004
Externally publishedYes

Keywords

  • Binary-symmetric channel (BSC)
  • Error exponent
  • Gaussian channel
  • Maximum-likelihood decoding
  • Probability of a union
  • Probability of error

ASJC Scopus subject areas

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

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