  Mobile edge caching (MEC) has been introduced to support ever-growing
end-users' needs. To reduce the backhaul traffic demand and content delivery
latency, cache-enabled edge servers at base stations (BSs) are employed to
provision popular contents at the network edge. In this paper,
multiple-input-multiple-output (MIMO) operation and user association policy are
linked to the underlying cache placement strategy to ensure a good trade-off
between load balancing and backhaul traffic taking into account the underlying
wireless channel and the finite cache capacity at edge servers. Due to the
coupled interference among mobile stations, the binary nature of the underlying
cache placement and user association matrices, the resulting mixed-timescale
mixed integer optimization problem is nonconvex and NP-hard. To solve this
problem, we decompose the joint optimization problem into a long-term content
placement sub-problem and a short-term content delivery sub-problem. A novel
iterative algorithm is introduced by leveraging the alternating direction
method of multipliers together with a stochastic parallel successive convex
approximation-based algorithm. The introduced scheme enables all BSs to update
their optimization variables in parallel by solving a sequence of convex
subproblems. Simulation evaluation demonstrates the efficiency of our strategy.
