  We develop mobility-aware routing and caching strategies to solve the network
cost minimization problem for dense small-cell networks. The challenge mainly
stems from the insufficient backhaul capacity of small-cell networks and the
limited storing capacity of small-cell base stations (SBSs). The optimization
problem is NP-hard since both the mobility patterns of the mobilized users
(MUs), as well as the MUs' preference for contents, are unknown. To tackle this
problem, we start by dividing the entire geographical area into small sections,
each of which containing one SBS and several MUs. Based on the concept of
one-stop-shop (OSS), we propose a federated routing and popularity learning
(FRPL) approach in which the SBSs cooperatively learn the routing and
preference of their respective MUs, and make caching decision. Notably, FRPL
enables the completion of the multi-tasks in one shot, thereby reducing the
average processing time per global aggregation. Theoretical and numerical
analyses show the effectiveness of our proposed approach.
