Cache-Aided General Linear Function Retrieval

Coded Caching, proposed by Maddah-Ali and Niesen (MAN), has the potential to reduce network traffic by pre-storing content in the users’ local memories when the network is underutilized and transmitting coded multicast messages that simultaneously benefit many users at once during peak-hour times. T...

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Bibliographic Details
Main Authors: Kai Wan, Hua Sun, Mingyue Ji, Daniela Tuninetti, Giuseppe Caire
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/23/1/25
Description
Summary:Coded Caching, proposed by Maddah-Ali and Niesen (MAN), has the potential to reduce network traffic by pre-storing content in the users’ local memories when the network is underutilized and transmitting coded multicast messages that simultaneously benefit many users at once during peak-hour times. This paper considers the linear function retrieval version of the original coded caching setting, where users are interested in retrieving a number of linear combinations of the data points stored at the server, as opposed to a single file. This extends the scope of the authors’ past work that only considered the class of linear functions that operate element-wise over the files. On observing that the existing cache-aided scalar linear function retrieval scheme does not work in the proposed setting, this paper designs a novel coded caching scheme that outperforms uncoded caching schemes that either use unicast transmissions or let each user recover all files in the library.
ISSN:1099-4300