  For wireless caching networks, the scheme design for content delivery is
non-trivial in the face of the following tradeoff. On one hand, to optimize
overall throughput, users can associate their nearby APs with great channel
capacities; however, this may lead to unstable queue backlogs on APs and
prolong request delays. On the other hand, to ensure queue stability, some
users may have to associate APs with inferior channel states, which would incur
throughput loss. Moreover, for such systems, how to conduct predictive
scheduling to reduce delays and the fundamental limits of its benefits remain
unexplored. In this paper, we formulate the problem of online user-AP
association and resource allocation for content delivery with predictive
scheduling under a fixed content placement as a stochastic network optimization
problem. By exploiting its unique structure, we transform the problem into a
series of modular maximization sub-problems with matroid constraints. Then we
devise PUARA, a Predictive User-AP Association and Resource Allocation scheme
which achieves a provably near-optimal throughput with queue stability. Our
theoretical analysis and simulation results show that PUARA can not only
perform a tunable control between throughput maximization and queue stability
but also incur a notable delay reduction with predicted information.
