  Optimal cache content placement in a wireless small cell base station (sBS)
with limited backhaul capacity is studied. The sBS has a large cache memory and
provides content-level selective offloading by delivering high data rate
contents to users in its coverage area. The goal of the sBS content controller
(CC) is to store the most popular contents in the sBS cache memory such that
the maximum amount of data can be fetched directly form the sBS, not relying on
the limited backhaul resources during peak traffic periods. If the popularity
profile is known in advance, the problem reduces to a knapsack problem.
However, it is assumed in this work that, the popularity profile of the files
is not known by the CC, and it can only observe the instantaneous demand for
the cached content. Hence, the cache content placement is optimised based on
the demand history. By refreshing the cache content at regular time intervals,
the CC tries to learn the popularity profile, while exploiting the limited
cache capacity in the best way possible. Three algorithms are studied for this
cache content placement problem, leading to different exploitation-exploration
trade-offs. We provide extensive numerical simulations in order to study the
time-evolution of these algorithms, and the impact of the system parameters,
such as the number of files, the number of users, the cache size, and the
skewness of the popularity profile, on the performance. It is shown that the
proposed algorithms quickly learn the popularity profile for a wide range of
system parameters.
