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Mean-field game theoretic edge caching in ultra-dense networks

Version 2 2024-06-05, 07:14
Version 1 2020-07-06, 16:12
journal contribution
posted on 2024-06-05, 07:14 authored by H Kim, Jihong ParkJihong Park, M Bennis, SL Kim, M Debbah
This paper investigates a cellular edge caching problem under a very large number of small base stations (SBSs) and users. In this ultra-dense edge caching network (UDCN), conventional caching algorithms are inapplicable as their computational complexity increases with the number of small base stations (SBSs). Furthermore, the performance of UDCN is highly sensitive to the dynamics of user demand. To overcome such difficulties, we propose a distributed caching algorithm under a stochastic geometric network model, as well as a spatio-temporal user demand model that characterizes the content popularity dynamics. By leveraging mean-field game (MFG) theory, the complexity of the proposed UDCN caching algorithm becomes independent of the number of SBSs. Numerical evaluations validate this consistent complexity of the proposed algorithm with respect to the number of SBSs. Also, it shows that the proposed caching algorithm reduces not only the long run average cost of the network but also the redundant cached data respectively by 24% and 42%, compared to a baseline caching algorithm. Additionally, the simulation results show that the proposed caching algorithm is robust to imperfect popularity information while ensuring a low computational complexity.

History

Journal

IEEE transactions on vehicular technology

Volume

69

Pagination

935-947

Location

Piscataway, N.J.

ISSN

0018-9545

eISSN

1939-9359

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

1

Publisher

IEEE

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