  Coded caching utilizes proper file subpacketization and coded delivery to
make full use of the multicast opportunities in content delivery, to alleviate
file transfer load in massive content delivery scenarios. Most existing work
considers deterministic environments. An important practical topic is to
characterize the impact of the uncertainty from user inactivity on coded
caching. We consider a one server cache-enabled network under homogeneous file
and network settings in presence of user inactivity. Unlike random or
probabilistic caching studied in the literature, deterministic coded caching is
considered, with the objective to minimize the worst-case backhaul load by
optimizing the file subpacketization and the caching strategy. First, a coded
caching method is used, where each file is split into the same type of
fragments labeled using sets with fixed cardinality, and the optimality of the
selected cardinality is proved. Optimal file subpacketization by splitting the
file into multiple types of fragments labeled with multiple cardinalities is
then discussed. We show that the closed-form optimum turns out to be given by a
fixed cardinality -- optimizing for user inactivity only affects file delivery,
cache placement is not affected. A decentralized version is also discussed and
analyzed, where each user fills its storage independently at random without
centralized coordination, and user inactivity is taken into account in file
delivery. Simulation results show that the optimization based centralized coded
caching scheme provides performance comparable to the ideal scenario assuming
full knowledge of user inactivity in the placement phase, while decentralized
caching performs slightly worse against user inactivity.
