  Cache-aided coded multicast leverages side information at wireless edge
caches to efficiently serve multiple unicast demands via common multicast
transmissions, leading to load reductions that are proportional to the
aggregate cache size. However, the increasingly dynamic, unpredictable, and
personalized nature of the content that users consume challenges the efficiency
of existing caching-based solutions in which only exact content reuse is
explored. This paper generalizes the cache-aided coded multicast problem to
specifically account for the correlation among content files, such as, for
example, the one between updated versions of dynamic data. It is shown that (i)
caching content pieces based on their correlation with the rest of the library,
and (ii) jointly compressing requested files using cached information as
references during delivery, can provide load reductions that go beyond those
achieved with existing schemes. This is accomplished via the design of a class
of correlation-aware achievable schemes, shown to significantly outperform
state-of-the-art correlation-unaware solutions. Our results show that as we
move towards real-time and/or personalized media dominated services, where
exact cache hits are almost non-existent but updates can exhibit high levels of
correlation, network cached information can still be useful as references for
network compression.
