Augmenting Multiple-Transmitter Coded Caching using Popularity Knowledge at the Transmitters
Berksan Serbetci, Eleftherios Lampiris, Thrasyvoulos Spyropoulos, Petros Elia · Graduate School and Research Center in Digital Science (EURECOM) · 2020
The work presents a new way of exploiting non-uniform file popularity in caching networks. Focusing on the interference channel with cache-enabled transmitters and receivers, we show how non-uniform file popularity can be used to accelerate the impact of transmitter-side data redundancy in coded caching. This approach is motivated by the recent discovery that under realistic file-size constraints, having content appear in multiple transmitters can boost multiplicatively the speed-up factor attributed to coded caching.We formulate the problem through an optimization algorithm, which seeks to optimize the number of transmitters each file is cached at, as a function of that file’s popularity. Part of the optimization effort involves a biconvex problem; such problems are traditionally solved by heuristic Alternate Convex Search methods that generally do not guarantee the global optimum. To avoid this, we follow a more involved path which includes the design of a new search algorithm that exploits the properties of the caching problem itself. The overall optimization algorithm provably achieves the globally optimal solution, and does so with a complexity that scales as a polynomial function of the logarithm of the size of the file catalog. In the end, the optimal transmitter-side cache placement yields multiplicative speedup factors over traditional multi-transmitter coded caching algorithms.