In this paper, the problem of distributed caching in dense wireless small cell networks (SCNs) is studied using mean eld games (MFGs). In the considered SCN, small base stations (SBSs) are equipped with data storage units and cooperate to serve users' requests either from les cached in the storage or directly from the capacity-limited backhaul. The aim of the SBSs is to de ne a caching policy that reduces the load on the capacitylimited backhaul links. This cache control problem is formulated as a stochastic di erential game (SDG). In this game, each SBS takes into consideration the storage state of the other SBSs to decide on the fraction of content it should cache. To solve this problem, the formulated SDG is reduced to an MFG by considering an ultradense network of SBSs in which the existence and uniqueness of the mean-eld equilibrium is shown to be guaranteed. Simulation results show that this framework allows an e cient use of the available storage space at the SBSs while properly tracking the les' popularity. The results also show that, compared to a baseline model in which SBSs are not aware of the instantaneous system state, the proposed framework increases the number of served les from the SBSs by more than 69%.
The authors of REF have studied the problem of distributed caching in ultra-dense wireless small cell networks using mean field games; however, this formulation requires us to take base station density to infinity (which may not be true in practice), and it does not provide any guarantee on the optimality of this caching strategy.
Mean-Field Games for Distributed Caching in Ultra-Dense Small Cell Networks
2016 American Control Conference (ACC)
2016 American Control Conference (ACC)
Computer Science Mathematics