Optimal geographic caching in cellular networks

By B. Błaszczyszyn, Anastasios Giovanidis. 2015 IEEE International Conference on Communications (ICC), 2014

427 citations recorded by the source corpus.

In this work we consider the problem of an optimal geographic placement of content in wireless cellular networks modelled by Poisson point processes. Specifically, for the typical user requesting some particular content and whose popularity follows a given law (e.g. Zipf), we calculate the probability of finding the content cached in one of the base stations. Wireless coverage follows the usual signal-to-interference-and noise ratio (SINR) model, or some variants of it. We formulate and solve the problem of an optimal randomized content placement policy, to maximize the user's hit probability. The result dictates that it is not always optimal to follow the standard policy “cache the most popular content, everywhere”. In fact, our numerical results regarding three different coverage scenarios, show that the optimal policy significantly increases the chances of hit under high-coverage regime, i.e., when the probabilities of coverage by more than just one station are high enough.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/6dde36c3c95c4277861717e64fce3f97caff0485

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Citations in the corpus

Modeling and Analysis of Cellular Networks Using Stochastic Geometry: A Tutorial (2016, methodology): “Recently, models for hitting probability via stochastic geometry are developed and used to propose solutions to the caching problems based on file popularity [179].”
Cache-enabled small cell networks: modeling and tradeoffs (2014, background): “Additionally, the related work [25] was made public after the submission of this work.”
Optimal and Scalable Caching for 5G Using Reinforcement Learning of Space-Time Popularities (2017, background): “Beyond [6], [7], and [8] that deal with deterministic caching, [9] and [10] introduce probabilistic alternatives.”
Analysis on Cache-Enabled Wireless Heterogeneous Networks (2015, background): “[17] considers the scenario where a user in the overlapping coverage area can connect to any of the stations covering it.”
Contract-Based Small-Cell Caching for Data Disseminations in Ultra-Dense Cellular Networks (2019, background): “We note that in [3], [32] an MU can associate with multiple SBSs for searching its desired file.”
Wireless caching: technical misconceptions and business barriers (2016, background): “In addition to initially studied single-tier network [23], the more detailed modeling and analysis of heterogeneous networks [24], [25], online caching policies [26], uniform caching [27], power consumption [28], and a Markovian mobility [29] are some recent examples in this direction.”
Caching at the wireless edge: design aspects, challenges, and future directions (2016, methodology): “One way to deal with this problem is to employ a probabilistic caching policy [13], rather than the deterministic caching policy used in wired networks.”
Cooperative Caching and Transmission Design in Cluster-Centric Small Cell Networks (2016, background): “The cache hit ratio can be improved by adopting an optimal probabilistic placement policy to increase content diversity in the caches of potential serving SBSs [5], [6].”