arXiv subjects

Nicolas Charpenay

Publications and source records attributed to Nicolas Charpenay.

4 recordsLinked to original sources

arXiv2025

On the Additivity of Optimal Rates for Independent Zero-Error Source and Channel Problems

Zero-error coding encompasses a variety of source and channel problems where the probability of error must be exactly zero. This condition is stricter than that of the vanishing error regime, where the error probability goes to zero as the code blocklength goes to infinity. In general, zero-error coding is an open combinatorial question. We investigate two unsolved zero-error problems: the source coding problem with side information and the channel coding problem. We focus our attention on families of independent problems for which the probability distribution decomposes into a product of probability distributions. A crucial step is the additivity property of the optimal rate, which does not always hold in the zero-error regime, unlike in the vanishing error regime. When the additivity holds, the concatenation of optimal codes is optimal. We derive a condition under which the additivity of the complementary graph entropy $\overline{H}$ for the AND product of graphs and for the disjoint union of graphs are equivalent. Then we establish the connection with a recent result obtained by Wigderson and Zuiddam and by Schrijver, for the zero-error capacity $C_0$. As a consequence, we provide new single-letter characterizations of $\overline{H}$ and $C_0$, for example when the graph is a product of perfect graphs, which is not perfect in general, and for the class of graphs obtained by the product of a perfect graph $G$ with the pentagon graph $C_5$. By building on Haemers result for $C_0$, we also show that the additivity of $\overline{H}$ does not hold for the product of the Schläfli graph with its complementary graph.

cs.IT↗

arXiv2023

Complementary Graph Entropy, AND Product, and Disjoint Union of Graphs

In the zero-error Slepian-Wolf source coding problem, the optimal rate is given by the complementary graph entropy $\overline{H}$ of the characteristic graph. It has no single-letter formula, except for perfect graphs, for the pentagon graph with uniform distribution $G_5$, and for their disjoint union. We consider two particular instances, where the characteristic graphs respectively write as an AND product $\wedge$, and as a disjoint union $\sqcup$. We derive a structural result that equates $\overline{H}(\wedge \: \cdot)$ and $\overline{H}(\sqcup \: \cdot)$ up to a multiplicative constant, which has two consequences. First, we prove that the cases where $\overline{H}(\wedge \:\cdot)$ and $\overline{H}(\sqcup \: \cdot)$ can be linearized coincide. Second, we determine $\overline{H}$ in cases where it was unknown: products of perfect graphs; and $G_5 \wedge G$ when $G$ is a perfect graph, using Tuncel et al.'s result for $\overline{H}(G_5 \sqcup G)$. The graphs in these cases are not perfect in general.

cs.IT↗

arXiv2022

Optimal Zero-Error Coding for Computing under Pairwise Shared Side Information

We study the zero-error source coding problem in which an encoder with Side Information (SI) $g(Y)$ transmits source symbols $X$ to a decoder. The decoder has SI $Y$ and wants to recover $f(X,Y)$ where $f,g$ are deterministic. We exhibit a condition on the source distribution and $g$ that we call "pairwise shared side information", such that the optimal rate has a single-letter expression. This condition is satisfied if every pair of source symbols "share" at least one SI symbol for all output of $g$. It has a practical interpretation, as $Y$ models a request made by the encoder on an image $X$, and $g(Y)$ corresponds to the type of request. It also has a graph-theoretical interpretation: under "pairwise shared side information" the characteristic graph can be written as a disjoint union of OR products. In the case where the source distribution is full-support, we provide an analytic expression for the optimal rate. We develop an example under "pairwise shared side information", and we show that the optimal coding scheme outperforms several strategies from the literature.

cs.IT↗

arXiv2020

Variable-Length Coding for Zero-Error Channel Capacity

The zero-error channel capacity is the maximum asymptotic rate that can be reached with error probability exactly zero, instead of a vanishing error probability. The nature of this problem, essentially combinatorial rather than probabilistic, has led to various researches both in Information Theory and Combinatorics. However, the zero-error capacity is still an open problem, for example the capacity of the noisy-typewriter channel with 7 letters is unknown. In this article, we propose a new approach to construct optimal zero-error codes, based on the concatenation of words of variable-length, taken from a generator set. Three zero-error variable-length coding schemes, referred to as "variable-length coding", "intermingled coding" and "automata-based coding", are under study. We characterize their asymptotic performances via linear difference equations, in terms of simple properties of the generator set, e.g. the roots of the characteristic polynomial, the spectral radius of an adjacency matrix, the inverse of the convergence radius of a generator series. For a specific example, we construct an "intermingled" coding scheme that achieves asymptotically the zero-error capacity.

cs.IT↗