On the Tanner Graph Cycle Distribution of Random LDPC, Random Protograph-Based LDPC, and Random Quasi-Cyclic LDPC Code Ensembles
Ali Dehghan, Amir H. Banihashemi

TL;DR
This paper analyzes the cycle distribution in various LDPC code ensembles, proving asymptotic independence of cycle counts and highlighting differences in cycle behavior among random, protograph-based, and quasi-cyclic LDPC codes.
Contribution
It provides a rigorous theoretical framework for understanding cycle distributions in different LDPC code ensembles, including asymptotic bounds and comparisons.
Findings
Cycle counts tend to independent Poisson distributions as graph size increases.
Asymptotic cycle distributions depend only on degree distribution and cycle length.
Cycle distribution in QC-LDPC codes can differ significantly from other ensembles.
Abstract
In this paper, we study the cycle distribution of random low-density parity-check (LDPC) codes, randomly constructed protograph-based LDPC codes, and random quasi-cyclic (QC) LDPC codes. We prove that for a random bipartite graph, with a given (irregular) degree distribution, the distributions of cycles of different length tend to independent Poisson distributions, as the size of the graph tends to infinity. We derive asymptotic upper and lower bounds on the expected values of the Poisson distributions that are independent of the size of the graph, and only depend on the degree distribution and the cycle length. For a random lift of a bi-regular protograph, we prove that the asymptotic cycle distributions are essentially the same as those of random bipartite graphs as long as the degree distributions are identical. For random QC-LDPC codes, however, we show that the cycle distribution…
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Taxonomy
TopicsError Correcting Code Techniques · Cooperative Communication and Network Coding · Caching and Content Delivery
