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Caching and multicasting are two promising methods to support massive contentdelivery in multi-tier wireless networks. In this paper, we consider a randomcaching and multicasting scheme with caching distributions in the two tiers asdesign parameters, to achieve efficient content dissemination in a two-tierlarge-scale cache-enabled wireless multicasting network. First, we derivetractable expressions for the successful transmission probabilities in thegeneral region as well as the high SNR and high user density region,respectively, utilizing tools from stochastic geometry. Then, for the case of asingle operator for the two tiers, we formulate the optimal joint cachingdesign problem to maximize the successful transmission probability in theasymptotic region, which is nonconvex in general. By using the block successiveapproximate optimization technique, we develop an iterative algorithm, which isshown to converge to a stationary point. Next, for the case of two differentoperators, one for each tier, we formulate the competitive caching design gamewhere each tier maximizes its successful transmission probability in theasymptotic region. We show that the game has a unique Nash equilibrium (NE) anddevelop an iterative algorithm, which is shown to converge to the NE under amild condition. Finally, by numerical simulations, we show that the proposeddesigns achieve significant gains over existing schemes.

Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks