  Millimeter wave (mmWave) communication technique has been developed rapidly
because of many advantages of high speed, large bandwidth, and ultra-low delay.
However, mmWave communications systems suffer from fast fading and frequent
blocking. Hence, the ideal communication environment for mmWave is line of
sight (LOS) channel. To improve the efficiency and capacity of mmWave system,
and to better build the Internet of Everything (IoE) service network, this
paper focuses on the channel identification technique in line-of- sight (LOS)
and non-LOS (NLOS) environments. Considering the limited computing ability of
user equipments (UEs), this paper proposes a novel channel identification
architecture based on eigen features, i.e. eigenmatrix and eigenvector (EMEV)
of channel state information (CSI). Furthermore, this paper explores clustered
delay line (CDL) channel identification with mmWave, which is defined by the
3rd generation partnership project (3GPP). Ther experimental results show that
the EMEV based scheme can achieve identification accuracy of 99.88% assuming
perfect CSI. In the robustness test, the maximum noise can be tolerated is SNR=
16 dB, with the threshold acc \geq 95%. What is more, the novel architecture
based on EMEV feature will reduce the comprehensive overhead by about 90%.
