Computer Science – Information Theory
Scientific paper
2011-04-04
Computer Science
Information Theory
5 pages, submitted to ISIT 2011
Scientific paper
Convolutional Low-Density-Parity-Check (LDPC) ensembles have excellent performance. Their iterative threshold increases with their average degree, or with the size of the coupling window in randomized constructions. In the later case, as the window size grows, the Belief Propagation (BP) threshold attains the maximum-a-posteriori (MAP) threshold of the underlying ensemble. In this contribution we show that a similar phenomenon happens for the growth rate of coupled ensembles. Loosely speaking, we observe that as the coupling strength grows, the growth rate of the coupled ensemble comes close to the concave hull of the underlying ensemble's growth rate. For ensembles randomly coupled across a window the growth rate actually tends to the concave hull of the underlying one as the window size increases. Our observations are supported by the calculations of the combinatorial growth rate, and that of the growth rate derived from the replica method. The observed concavity is a general feature of coupled mean field graphical models and is already present at the level of coupled Curie-Weiss models. There, the canonical free energy of the coupled system tends to the concave hull of the underlying one. As we explain, the behavior of the growth rate of coupled ensembles is exactly analogous.
Hassani Steven H.
Macris Nicolas
Mori Ryuhei
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