On the Optimality of Coded Caching With Heterogeneous User Profiles

TL;DR

This paper analyzes a coded caching system with users having diverse interests, providing a new converse bound and demonstrating near-optimality of uncoded caching strategies within a constant factor.

Contribution

It introduces a novel information-theoretic converse for heterogeneous user profiles and improves the known bounds on uncoded caching optimality.

Findings

Developed a new converse bound for worst-case communication load.

Achieved a constant factor approximation (within 2) of the optimal load.

Enhanced understanding of uncoded caching effectiveness in heterogeneous settings.

Abstract

In this paper, we consider a coded caching scenario where users have heterogeneous interests. Taking into consideration the system model originally proposed by Wang and Peleato, for which the end-receiving users are divided into groups according to their file preferences, we develop a novel information-theoretic converse on the optimal worst-case communication load under uncoded cache placement. Interestingly, the developed converse bound, jointly with one of the coded schemes proposed by Wang and Peleato, allows us to characterize the optimal worst-case communication load under uncoded prefetching within a constant multiplicative gap of $2$. Although we restrict the caching policy to be uncoded, our work improves the previously known order optimality results for the considered caching problem.