Improved bounds on the size of sparse parity check matrices

Assaf Naor, Jacques Verstraete

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Let Ndouble-struck F sign(n, k, r) denote the maximum number of columns in an n-row matrix with entries in a finite field double-struck F sign in which each column has at most r nonzero entries and every k columns are linearly independent over double-struck F sign. Such sparse parity check matrices are fundamental tools in coding theory, derandomization and complexity theory. We obtain near-optimal theoretical upper bounds for N double-struck F sign(n, k, r) in the important case k > r, i.e. when the number of correctible errors is greater than the weight. Namely, we show that Ndouble-struck F sign(n, k, r) = O(nr/2+4r/3k). The best known (probabilistic) lower bound is N double-struck F sign(n, k, r) = Ω(nr/2+r/2k-2), while the best known upper bound in the case k > r was for k a power of 2, in which case Ndouble-struck F sign(n, k, r) = Ω(n r/2+1/2). Our method is based on a novel reduction of the problem to the extremal problem for cycles in graphs, and yields a fast algorithm for finding short linear dependences in large sets of sparse vectors. In the full version of this paper we present additional applications of this method to problems in combinatorial number theory.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05
Pages1749-1752
Number of pages4
DOIs
StatePublished - Dec 1 2005
Externally publishedYes
Event2005 IEEE International Symposium on Information Theory, ISIT 05 - Adelaide, Australia
Duration: Sep 4 2005Sep 9 2005

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2005
ISSN (Print)2157-8099

Other

Other2005 IEEE International Symposium on Information Theory, ISIT 05
Country/TerritoryAustralia
CityAdelaide
Period9/4/059/9/05

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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