PREPRINT

# Zero-Error Coding for Computing with Encoder Side-Information

Nicolas Charpenay, Maël le Treust, Aline Roumy

Submitted on 7 November 2022

## Abstract

We study the zero-error source coding problem in which an encoder with Side Information (SI) $g\left(Y\right)$ transmits source symbols $X$ to a decoder. The decoder has SI $Y$ and wants to recover $f\left(X,Y\right)$ 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 $g\left(Y\right)$ 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.

## Preprint

Subject: Computer Science - Information Theory