Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11246
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Main Title: Cache-Aided General Linear Function Retrieval
Author(s): Wan, Kai
Sun, Hua
Ji, Mingyue
Tuninetti, Daniela
Caire, Giuseppe
Type: Article
Language Code: en
Abstract: 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.
URI: https://depositonce.tu-berlin.de/handle/11303/12404
http://dx.doi.org/10.14279/depositonce-11246
Issue Date: 26-Dec-2020
Date Available: 11-Jan-2021
DDC Class: 600 Technik, Technologie
Subject(s): coded caching
linear function retrieval
uncoded cache placement
Sponsor/Funder: EC/H2020/789190/EU/Content-Aware Wireless Networks: Fundamental Limits, Algorithms, and Architectures/CARENET
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Entropy
Publisher: MDPI
Publisher Place: Basel
Volume: 23
Issue: 1
Article Number: 25
Publisher DOI: 10.3390/e23010025
EISSN: 1099-4300
Appears in Collections:FG Theoretische Grundlagen der Kommunikationstechnik » Publications

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