4.7 Article

Wireless Coded Caching Can Overcome the Worst-User Bottleneck by Exploiting Finite File Sizes

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 21, Issue 7, Pages 5450-5466

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2022.3140895

Keywords

Signal to noise ratio; Wireless communication; Gain; Manganese; Time division multiplexing; Multicast communication; Libraries; Coded-caching; finite SNR; shared caches; worst-user bottleneck; effective coded caching gain

Funding

  1. European Research Council under the EU Horizon 2020 Research and Innovation Program/ERC (ERC Project DUALITY) [725929]

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This paper addresses the bottleneck of worst-user in wireless coded caching and proposes a novel scheme to recover the caching gains by utilizing the shared side information brought about by the file-size constraint. The worst-user effect is replaced by the effect of worst-group-of-users, which is fixed before the channel or the demands are known. The proposed scheme can be applied to other coded caching schemes and scenarios in the future.
We address the worst-user bottleneck of wireless coded caching, which is known to severely diminish cache-aided multicasting gains due to the fundamental worst-channel limitation of multicasting. We consider the quasi-static Rayleigh fading Broadcast Channel, for which we first show that the effective coded caching gain of the standard XOR-based coded-caching scheme completely vanishes in the low signal-to-noise ratio (SNR) regime. Then, we reveal that this collapse is not intrinsic to coded caching. We do so by presenting a novel scheme that can fully recover the coded caching gains by capitalizing on one aspect that has remained unexploited to date: the shared side information brought about by the effectively unavoidable file-size constraint. As a consequence, the worst-user effect is dramatically ameliorated, as it is substituted by a much more subtle worst-group-of-users effect, where the suggested grouping is fixed, and it is decided before the channel or the demands are known. Furthermore, the theoretical gains are completely recovered as the number of users increases, and this is done without any user selection technique. We analyze the rate performance of the proposed scheme and derive approximations which prove to be very precise. Importantly, this novel approach can be translated to other coded caching schemes and scenarios, including decentralized scenarios.

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