Entropy (Dec 2020)

Cache-Aided General Linear Function Retrieval

  • Kai Wan,
  • Hua Sun,
  • Mingyue Ji,
  • Daniela Tuninetti,
  • Giuseppe Caire

DOI
https://doi.org/10.3390/e23010025
Journal volume & issue
Vol. 23, no. 1
p. 25

Abstract

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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.

Keywords