  Caching and multicasting at base stations are two promising approaches to
support massive content delivery over wireless networks. However, existing
analysis and designs do not fully explore and exploit the potential advantages
of the two approaches. In this paper, we consider the analysis and optimization
of caching and multicasting in a large-scale cache-enabled wireless network. We
propose a random caching and multicasting scheme with a design parameter. By
carefully handling different types of interferers and adopting appropriate
approximations, we derive a tractable expression for the successful
transmission probability in the general region, utilizing tools from stochastic
geometry. We also obtain a closed-form expression for the successful
transmission probability in the high signal-to-noise ratio (SNR) and user
density region. Then, we consider the successful transmission probability
maximization, which is a very complex non-convex problem in general. Using
optimization techniques, we develop an iterative numerical algorithm to obtain
a local optimal caching and multicasting design in the general region. To
reduce complexity and maintain superior performance, we also derive an
asymptotically optimal caching and multicasting design in the asymptotic
region, based on a two-step optimization framework. Finally, numerical
simulations show that the asymptotically optimal design achieves a significant
gain in successful transmission probability over some baseline schemes in the
general region.
