Computer Science – Information Theory
Scientific paper
2006-02-26
Computer Science
Information Theory
Submitted to IEEE Transactions on Information Theory, February 25, 2006
Scientific paper
In order to understand the performance of a code under maximum-likelihood (ML) decoding, one studies the codewords, in particular the minimal codewords, and their Hamming weights. In the context of linear programming (LP) decoding, one's attention needs to be shifted to the pseudo-codewords, in particular to the minimal pseudo-codewords, and their pseudo-weights. In this paper we investigate some families of codes that have good properties under LP decoding, namely certain families of low-density parity-check (LDPC) codes that are derived from projective and Euclidean planes: we study the structure of their minimal pseudo-codewords and give lower bounds on their pseudo-weight.
Smarandache Roxana
Vontobel Pascal O.
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