Coded Caching with Shared Caches from Generalized Placement Delivery Arrays

Peter, Elizabath; Rajan, B. Sundar

doi:10.1109/pimrc50174.2021.9569690

Cited by 8 publications

(1 citation statement)

References 21 publications

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“…In [9], Jin et al proposed a decentralized sharedcache scheme for the subpacketization-constrained (finite file size) scenario, while [43] revealed for the first time that in the presence of multiple antennas the shared-cache approach can dramatically alleviate the subpacketization problem while simultaneously exploiting both multiplexing and caching gains in their entirety. Recently, [44] analyzed the case in which there exist both dedicated and shared caches, and [45] studied the case where the library files are correlated. Other related works can be found in [46], [47].…”

Section: A the Shared Cache Model For Coded Cachingmentioning

confidence: 99%

Fundamental Limits of Topology-Aware Shared-Cache Networks

Parrinello¹,

Bazco-Nogueras²,

Elia³

2023

Preprint

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This work studies a well-known shared-cache coded caching scenario where each cache can serve an arbitrary number of users, analyzing the case where there is some knowledge about such number of users (i.e., the topology) during the content placement phase. Under the assumption of regular placement and a cumulative cache size that can be optimized across the different caches, we derive the fundamental limits of performance by introducing a novel cache-size optimization and placement scheme and a novel information-theoretic converse. The converse employs new index coding techniques to bypass traditional uniformity requirements, thus finely capturing the heterogeneity of the problem, and it provides a new approach to handle asymmetric settings. The new fundamental limits reveal that heterogeneous topologies can in fact outperform their homogeneous counterparts where each cache is associated to an equal number of users. These results are extended to capture the scenario of topological uncertainty where the perceived/estimated topology does not match the true network topology. This scenario is further elevated to the stochastic setting where the user-to-cache association is random and unknown, and it is shown that the proposed scheme is robust to such noisy or inexact knowledge on the topology.

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