  Neural networks have been applied to the physical layer of wireless
communication systems to solve complex problems. In millimeter wave (mmWave)
massive multiple-input multiple-output (MIMO) systems, hybrid precoding has
been considered as an energy-efficient technology to replace fully-digital
precoding. The way of designing hybrid precoding in mmWave massive MIMO systems
by multi-layer neural networks has not been investigated. Based on further
decomposing the baseband precoding matrix, an idea is proposed in this paper to
map hybrid precoding structure to a multi-layer neural network. Considering the
deterioration in the throughput and energy efficiency of mmWave massive MIMO
systems, the feasibility of the proposed idea is analyzed. Moreover, a singular
value decomposition (SVD) based decomposing (SVDDE) algorithm is proposed to
evaluate the feasibility of the proposed idea. Simulation results indicate that
there is an optimal number of users which can minimize the performance
deterioration. Moreover, the simulation results also show that slight
deterioration in the throughput and energy efficiency of mmWave massive MIMO
systems is caused by further decomposing the baseband precoding matrix. In
other words, further decomposing the baseband precoding matrix is a feasible
way to map the hybrid precoding structure to a multi-layer neural network.
