  Cache-aided wireless device-to-device (D2D) networks allow significant
throughput increase, depending on the concentration of the popularity
distribution of files. Many studies assume that all users have the same
preference distribution; however, this may not be true in practice. This work
investigates whether and how the information about individual preferences can
benefit cache-aided D2D networks. We examine a clustered network and derive a
network utility that considers both the user distribution and channel fading
effects into the analysis. We also formulate a utility maximization problem for
designing caching policies. This maximization problem can be applied to
optimize several important quantities, including throughput, energy efficiency
(EE), cost, and hit-rate, and to solve different tradeoff problems. We provide
a general approach that can solve the proposed problem under the assumption
that users coordinate, then prove that the proposed approach can obtain the
stationary point under a mild assumption. Using simulations of practical
setups, we show that performance can improve significantly with proper
exploitation of individual preferences. We also show that different types of
tradeoffs exist between different performance metrics and that they can be
managed through caching policy and cooperation distance designs.
