Coded Caching With Full Heterogeneity: Exact Capacity of the Two-User/Two-File Case

Chang, Ching Jer; Peleato, Borja; Wang, Chih-Chun

doi:10.1109/tit.2022.3181411

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…The average rate of a system with heterogeneous users was addressed in [6], [11], [12], but just for the case of two users. This paper considers a system with a single server connected to K end users through an error-free broadcast link.…”

Section: System Modelmentioning

confidence: 99%

On the Average Rate for Coded Caching with Heterogeneous User Profiles

Zhang

Peleato

2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

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Coded caching utilizes pre-fetching during off-peak hours and multi-casting for delivery in order to balance the traffic load in communication networks. Most of the existing research focuses on reducing the peak transmission rates with homogeneous file popularities, despite modern systems are often able to categorize users by their preferences and tend to care more about the average rather than peak rate. This paper considers a scenario with heterogeneous user profiles and analyzes the average transmission rates for three coded caching schemes under the assumption that each user can only request a subset of the total available files. In addition, it evaluates the average rate of the three schemes when the number of files is much larger than the number of users and the amount of cache memory. Furthermore, it proposes methods of cache allocations which minimize the average rate when the users have relatively small storage. Our results demonstrate connections between cache distributions which result in minimal average rate and peak rate.

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Section: System Modelmentioning

confidence: 99%

On the Average Rate for Coded Caching with Heterogeneous User Profiles

Zhang

Peleato

2020

ICC 2020 - 2020 IEEE International Conference on Communications (ICC)

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“…This is particularly true in heterogeneous scenarios like the one we consider here, where one expects to find larger caches that serve the many users of large office buildings coexisting with smaller caches that serve smaller pockets of population. It is worth remarking that deriving fundamental limits for asymmetric settings is a challenging topic, as it has been shown in the recent work [51], where the authors fully characterized the exact capacity of the 2-file/2-user setting simultaneously allowing for heterogeneous files sizes, heterogeneous cache sizes, and user-dependent file popularities.…”

Section: B Memory Allocation In Cache-aided Networkmentioning

confidence: 99%

“…Since under the regular assumption of Definition 1 it holds that t is integer (i.e., t ∈ [Λ] 0 ), we first note that t = t. Furthermore, this assumption implies that āt = 1 and āj = 0 for any j ∈ {[Λ] 0 \t}. We can lower bound (51) by fixing p to p = t, which reduces (51) to…”

Section: Proof Of Theoremmentioning

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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