Pliable Index Coding via Conflict-Free Colorings of Hypergraphs

TL;DR

This paper introduces a hypergraph coloring approach to pliable index coding, providing new bounds and algorithms that improve transmission efficiency by leveraging conflict-free colorings and graph parameters.

Contribution

It presents a novel hypergraph coloring framework for PICOD, deriving new upper bounds and randomized algorithms that outperform previous methods in certain parameter regimes.

Findings

Achieves PICOD length of O(log^2 Γ) for single request case

Provides an MDS code of length max(O(log Γ log m), O(t log m)) for t-request case

Offers near-optimal codes with length within a logarithmic factor of the best possible

Abstract

In the pliable index coding (PICOD) problem, a server is to serve multiple clients, each of which possesses a unique subset of the complete message set as side information and requests a new message which it does not have. The goal of the server is to do this using as few transmissions as possible. This work presents a hypergraph coloring approach to the scalar PICOD problem. A \textit{conflict-free coloring} of a hypergraph is known from literature as an assignment of colors to its vertices so that each hyperedge of the graph contains one uniquely colored vertex. For a given PICOD problem represented by a hypergraph consisting of messages as vertices and request-sets as hyperedges, we present achievable PICOD schemes using conflict-free colorings of the PICOD hypergraph. Various graph theoretic parameters arising out of such colorings (and some new coloring variants) then give a number of upper bounds on the optimal PICOD length, which we study in this work. Suppose the PICOD hypergraph has $m$ vertices and $n$ hyperedges, where every hyperedge overlaps with at most $\Gamma$ other hyperedges. We show easy to implement randomized algorithms for the following: (a) For the single request case, we give a PICOD of length $O(\log^2\Gamma)$. This result improves over known achievability results for some parameter ranges, (b) For the $t$-request case, we give an MDS code of length $\max(O(\log \Gamma \log m), O(t \log m))$. Further if the hyperedges (request sets) are sufficiently large, we give a PICOD of the same length as above, which is not based on MDS construction. In general, this gives an improvement over prior achievability results. Our codes are of near-optimal length (up to a multiplicative factor of $\log t$).