  Millimeter wave (MmWave) has been regarded as a promising technology to
support high-capacity communications in 5G era. However, its high-layer
performance such as latency and packet drop rate in the long term highly
depends on resource allocation because mmWave channel suffers significant
fluctuation with rotating users due to mmWave sparse channel property and
limited field-of-view (FoV) of antenna arrays. In this paper, downlink
transmission scheduling considering rotation of user equipments (UE) and
limited antenna FoV in an mmWave system is optimized via a novel approximate
Markov decision process (MDP) method. Specifically, we consider the joint
downlink UE selection and power allocation in a number of frames where future
orientations of rotating UEs can be predicted via embedded motion sensors. The
problem is formulated as a finite-horizon MDP with non-stationary state
transition probabilities. A novel low-complexity solution framework is proposed
via one iteration step over a base policy whose average future cost can be
predicted with analytical expressions. It is demonstrated by simulations that
compared with existing benchmarks, the proposed scheme can schedule the
downlink transmission and suppress the packet drop rate efficiently in
non-stationary mmWave links.
