On the Average Rate for Coded Caching with Heterogeneous User Profiles

Coded caching utilizes pre-fetching during off-peak hours and multi-casting for delivery in order to balance the traffic load in communication networks. Most of the existing research focuses on reducing the peak transmission rates with homogeneous file popularities, despite modern systems are often able to categorize users by their preferences and tend to care more about the average rather than peak rate. This paper considers a scenario with heterogeneous user profiles and analyzes the average transmission rates for three coded caching schemes under the assumption that each user can only request a subset of the total available files. In addition, it evaluates the average rate of the three schemes when the number of files is much larger than the number of users and the amount of cache memory. Furthermore, it proposes methods of cache allocations which minimize the average rate when the users have relatively small storage. Our results demonstrate connections between cache distributions which result in minimal average rate and peak rate.