  Cache-aided coded multicast leverages side information at wireless edge
caches to efficiently serve multiple groupcast demands via common multicast
transmissions, leading to load reductions that are proportional to the
aggregate cache size. However, the increasingly 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 a source
compression with distributed side information problem that specifically
accounts for the correlation among the content files. It is shown how joint
file compression during the caching and delivery phases can provide load
reductions that go beyond those achieved with existing schemes. This is
accomplished through a lower bound on the fundamental rate-memory trade-off as
well as a correlation-aware achievable scheme, shown to significantly
outperform state-of-the-art correlation-unaware solutions, while approaching
the limiting rate-memory trade-off.
