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Millimeter wave (mmWave) communication technique has been developed rapidlybecause of many advantages of high speed, large bandwidth, and ultra-low delay.However, mmWave communications systems suffer from fast fading and frequentblocking. Hence, the ideal communication environment for mmWave is line ofsight (LOS) channel. To improve the efficiency and capacity of mmWave system,and to better build the Internet of Everything (IoE) service network, thispaper focuses on the channel identification technique in line-of- sight (LOS)and non-LOS (NLOS) environments. Considering the limited computing ability ofuser equipments (UEs), this paper proposes a novel channel identificationarchitecture based on eigen features, i.e. eigenmatrix and eigenvector (EMEV)of channel state information (CSI). Furthermore, this paper explores clustereddelay line (CDL) channel identification with mmWave, which is defined by the3rd generation partnership project (3GPP). Ther experimental results show thatthe EMEV based scheme can achieve identification accuracy of 99.88% assumingperfect 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 architecturebased on EMEV feature will reduce the comprehensive overhead by about 90%.

A Novel Channel Identification Architecture for mmWave Systems Based on Eigen Features