  The fog radio access network (Fog-RAN) has been considered a promising
wireless access architecture to help shorten the communication delay and
relieve the large data delivery burden over the backhaul links. However,
limited by conventional inflexible communication design, Fog-RAN cannot be used
in some complex communication scenarios. In this study, we focus on
investigating a more intelligent Fog-RAN to assist the communication in a
high-speed railway environment. Due to the train's continuously moving, the
communication should be designed intelligently to adapt to channel variation.
Specifically, we dynamically optimize the power allocation in the remote radio
heads (RRHs) to minimize the total network power cost considering multiple
quality-of-service (QoS) requirements and channel variation. The impact of
caching on the power allocation is considered. The dynamic power optimization
is analyzed to obtain a closed-form solution in certain cases. The inherent
tradeoff among the total network cost, delay and delivery content size is
further discussed. To evaluate the performance of the proposed dynamic power
allocation, we present an invariant power allocation counterpart as a
performance comparison benchmark. The result of our simulation reveals that
dynamic power allocation can significantly outperform the invariant power
allocation scheme, especially with a random caching strategy or limited caching
resources at the RRHs.
