Mohammad Mohammadi Amiri

Fundamental Limits of Coded Caching: Improved Delivery Rate-Cache Capacity Tradeoff

A centralized coded caching system, consisting of a server delivering N popular files, each of size F bits, to K users through an error-free shared link, is considered. It is assumed that each user is equipped with a local cache memory with capacity MF bits, and contents can be proactively cached into these caches over a low traffic period; however, without the knowledge of the user demands. During the peak traffic period each user requests a single file from the server. The goal is to minimize the number of bits delivered by the server over the shared link, known as the delivery rate, over all user demand combinations. A novel coded caching scheme for the cache capacity of M= (N-1)/K is proposed. It is shown that the proposed scheme achieves a smaller delivery rate than the existing coded caching schemes in the literature when K > N >= 3. Furthermore, we argue that the delivery rate of the proposed scheme is within a constant multiplicative factor of 2 of the optimal delivery rate for cache capacities 1/K N >= 3.

Audience retention rate aware coded video caching

Users often do not watch an online video content in its entirety, and abort the video before it is completed. This is captured by the notion of audience retention rate, which indicates the portion of a video users watch on average. A decentralized coded caching scheme, called partial coded caching (PCC), is proposed here to take into account both the popularity, and the audience retention rate of the video files in a database. The achievable average delivery rate of PCC is characterised over all possible demand combinations. Two different cache allocation schemes, called the optimal cache allocation (OCA) and the popularity based cache allocation (PCA), are proposed to allocate cache capacities among the different chunks of video files. Numerical results validate that the proposed coded caching scheme, either with the OCA or the PCA, outperforms conventional uncoded caching, as well as the state-of-the-art coded caching schemes that consider only file popularities.

Decentralized Caching and Coded Delivery With Distinct Cache Capacities

Decentralized proactive caching and coded delivery is studied in a content delivery network, where each user is equipped with a cache memory, not necessarily of equal capacity. Cache memories are filled in advance during the off-peak traffic period in a decentralized manner, i.e., without the knowledge of the number of active users, their identities, or their particular demands. User demands are revealed during the peak traffic period, and are served simultaneously through an error-free shared link. The goal is to find the minimum delivery rate during the peak traffic period that is sufficient to satisfy all possible demand combinations. A group-based decentralized caching and coded delivery scheme is proposed, and it is shown to improve upon the state of the art in terms of the minimum required delivery rate when there are more users in the system than files. Numerical results indicate that the improvement is more significant as the cache capacities of the users become more skewed. A new lower bound on the delivery rate is also presented, which provides a tighter bound than the classical cut-set bound.

Decentralized caching and coded delivery over Gaussian broadcast channels

A cache-aided K-user Gaussian broadcast channel (BC) is considered. The transmitter has a library of N equal-rate files, from which each user demands one. The impact of the equal-capacity receiver cache memories on the minimum required transmit power to satisfy all user demands is studied. Decentralized caching with uniformly random demands is considered, and both the minimum average power (averaged over all demand combinations) and the minimum peak power (minimum power required to satisfy the worst-case demand combination) are studied. Upper and lower bounds are presented on the minimum required average and peak transmit power as a function of the cache capacity, assuming uncoded cache placement. The gaps between the upper and lower bounds on both the minimum peak and average power values are shown to be relatively small through numerical results, particularly for large cache capacities.