  We propose an intelligent proactive content caching scheme to reduce the
energy consumption in wireless downlink. We consider an online social network
(OSN) setting where new contents are generated over time, and remain
\textit{relevant} to the user for a random lifetime. Contents are downloaded to
the user equipment (UE) through a time-varying wireless channel at an energy
cost that depends on the channel state and the number of contents downloaded.
The user accesses the OSN at random time instants, and consumes all the
relevant contents. To reduce the energy consumption, we propose
\textit{proactive caching} of contents under favorable channel conditions to a
finite capacity cache memory. Assuming that the channel quality (or
equivalently, the cost of downloading data) is memoryless over time slots, we
show that the optimal caching policy, which may replace contents in the cache
with shorter remaining lifetime with contents at the server that remain
relevant longer, has certain threshold structure with respect to the channel
quality. Since the optimal policy is computationally demanding in practice, we
introduce a simplified caching scheme and optimize its parameters using policy
search. We also present two lower bounds on the energy consumption. We
demonstrate through numerical simulations that the proposed caching scheme
significantly reduces the energy consumption compared to traditional reactive
caching tools, and achieves close-to-optimal performance for a wide variety of
system parameters.
