  Caching popular files in small base stations (SBSs) has been proved to be an
effective way to reduce bandwidth pressure on the backhaul links of dense small
cell networks (DSCNs). Many existing studies on cache-enabled DSCNs attempt to
improve user experience by optimizing end-to-end file delivery delay. However,
under practical scenarios where files (e.g., video files) have diverse quality
of service requirements, energy consumption at SBSs should also be concerned
from the network perspective. In this paper,we attempt to optimize these two
critical metrics in cache-enabled DSCNs. Firstly, we formulate the energy-delay
optimization problem as a Mixed Integer Programming (MIP) problem, where file
placement, user association and power control are jointly considered. To model
the tradeoff relationship between energy consumption and end-to-end file
delivery delay, a utility function linearly combining these two metrics is used
as an objective function of the optimization problem. Then, we solve the
problem in two stages, i.e. caching stage and delivery stage, based on the
observation that caching is performed during off-peak time. At the caching
stage, a local popular file placement policy is proposed by estimating user
preference at each SBS. At the delivery stage, with given caching status at
SBSs, the MIP problem is further decomposed by Benders' decomposition method.
An efficient algorithm is proposed to approach the optimal association and
power solution by iteratively shrinking the gap of the upper and lower bounds.
Finally, extension simulations are performed to validate our analytical and
algorithmic work. The results demonstrate that the proposed algorithms can
achieve the optimal tradeoff between energy consumption and end-to-end file
delivery delay.
