131 research outputs found
Absorbing Set Analysis and Design of LDPC Codes from Transversal Designs over the AWGN Channel
In this paper we construct low-density parity-check (LDPC) codes from
transversal designs with low error-floors over the additive white Gaussian
noise (AWGN) channel. The constructed codes are based on transversal designs
that arise from sets of mutually orthogonal Latin squares (MOLS) with cyclic
structure. For lowering the error-floors, our approach is twofold: First, we
give an exhaustive classification of so-called absorbing sets that may occur in
the factor graphs of the given codes. These purely combinatorial substructures
are known to be the main cause of decoding errors in the error-floor region
over the AWGN channel by decoding with the standard sum-product algorithm
(SPA). Second, based on this classification, we exploit the specific structure
of the presented codes to eliminate the most harmful absorbing sets and derive
powerful constraints for the proper choice of code parameters in order to
obtain codes with an optimized error-floor performance.Comment: 15 pages. arXiv admin note: text overlap with arXiv:1306.511
On the Minimum Distance of Array-Based Spatially-Coupled Low-Density Parity-Check Codes
An array low-density parity-check (LDPC) code is a quasi-cyclic LDPC code
specified by two integers and , where is an odd prime and . The exact minimum distance, for small and , has been calculated, and
tight upper bounds on it for have been derived. In this work, we
study the minimum distance of the spatially-coupled version of these codes. In
particular, several tight upper bounds on the optimal minimum distance for
coupling length at least two and , that are independent of and
that are valid for all values of where depends on , are
presented. Furthermore, we show by exhaustive search that by carefully
selecting the edge spreading or unwrapping procedure, the minimum distance
(when is not very large) can be significantly increased, especially for
.Comment: 5 pages. To be presented at the 2015 IEEE International Symposium on
Information Theory, June 14-19, 2015, Hong Kon
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