On the Optimal Load-Memory Tradeoff of Coded Caching for Location-Based Content

Caching at the wireless edge nodes is a promising way to boost the spatial and spectral efficiency, for the sake of alleviating networks from content-related traffic. Coded caching originally introduced by Maddah-Ali and Niesen significantly speeds up communication efficiency by transmitting multicast messages simultaneously useful to multiple users. Most prior works on coded caching are based on the assumption that each user may request all content in the library. However, in many applications the users are interested only in a limited set of content items that depends on their location. For example, visitors in a museum may stream audio and video related to the artworks in the room they are visiting, or assisted self-driving vehicles may access super-high definition maps of the area through which they are travelling. Motivated by these considerations, this paper formulates the coded caching problem for location-based content with edge cache nodes. The considered problem includes a content server with access to N location-based files, K edge cache nodes located at different regions, and K users each of which is in the serving region of one cache node and can retrieve the cached content of this cache node with negligible cost. Depending on the location, each user only requests a file from a location-dependent subset of the library. The objective is to minimize the worst-case load transmitted from the content server among all possible demands. We propose a highly non-trivial converse bound under uncoded cache placement, which shows that a simple achievable scheme is optimal. In addition, this achievable scheme is generally order optimal within 3. Finally, we extend the coded caching problem for location-based content to the multiaccess coded caching topology, where each user is connected to L nearest cache nodes. When $L \geq 2$ we characterize the exact optimality on the worst-case load.