Fundamental Structure of Optimal Cache Placement for Coded Caching with Heterogeneous Demands

This paper studies the caching system of multiple cache-enabled users with heterogeneous demands. Under nonuniform file popularity, we thoroughly characterize the structure of the optimal uncoded cache placement for the coded caching scheme (CCS). Formulating the cache placement as an optimization problem to minimize the average delivery rate, we identify the file grouping structure under the optimal solution. We show that, regardless of file popularity, there are at most three file groups under the optimal cache placement. We further characterize the complete structure of the optimal cache placement and obtain the closed-form solution in each possible file grouping case. A simple algorithm is developed to obtain the final optimal cache placement, which only computes a set of candidate closed-form solutions in parallel. We provide insights into the file groups formed by the optimal cache placement. The optimal placement solution also indicates that coding between file groups may be explored during delivery, in contrast to the existing heuristic file grouping schemes. Using the file grouping in the optimal cache placement, we propose a new information-theoretic converse bound for coded caching that is tighter than existing ones. Moreover, using the optimal cache placement solution, we characterize the file subpacketization in the optimal CCS and show that the maximum subpacketization level in the worst case scales as $\mathcal{O}(2^K/\sqrt{K})$ for $K$ users.Comment: 19 pages, 12 figures, submitted to IEEE Trans. Information Theor

Content Caching and Delivery over Heterogeneous Wireless Networks

Emerging heterogeneous wireless architectures consist of a dense deployment of local-coverage wireless access points (APs) with high data rates, along with sparsely-distributed, large-coverage macro-cell base stations (BS). We design a coded caching-and-delivery scheme for such architectures that equips APs with storage, enabling content pre-fetching prior to knowing user demands. Users requesting content are served by connecting to local APs with cached content, as well as by listening to a BS broadcast transmission. For any given content popularity profile, the goal is to design the caching-and-delivery scheme so as to optimally trade off the transmission cost at the BS against the storage cost at the APs and the user cost of connecting to multiple APs. We design a coded caching scheme for non-uniform content popularity that dynamically allocates user access to APs based on requested content. We demonstrate the approximate optimality of our scheme with respect to information-theoretic bounds. We numerically evaluate it on a YouTube dataset and quantify the trade-off between transmission rate, storage, and access cost. Our numerical results also suggest the intriguing possibility that, to gain most of the benefits of coded caching, it suffices to divide the content into a small number of popularity classes.Comment: A shorter version is to appear in IEEE INFOCOM 201