The fingerprint feature analysis of wireless channels of sensors in mobile communications is the basis to support the application of sensors in mobile communication technology. In this paper, we propose a set of analytical research methods including the modeling, feature analysis, and scene identification of wireless channels for the realization of different fading characteristics of signals when transmitted in different wireless channels. (1) According to the transmission process of a signal in a wireless channel, considering the effect of the signal by noise interference in the wireless channel, a global wireless channel signal transmission model that introduces time-varying nature is established. (2) We proposed a wavelet noise reduction method based on singular value decomposition to attenuate the interference effect of noisy signals on channel characterization. (3) We proposed a method for extracting wireless channel features from the perspectives of Doppler expansion, time delay expansion, path loss, path gain, and signal peak analysis, and extracted wireless channel “fingerprint” features under three different scenarios through simulation analysis. (4) Finally, we established a fingerprint feature evaluation model on the basis of weight assignment and verified the feasibility of this evaluation model through example analysis. In this paper, we focused on the systematic research and analysis of the wireless channel features of sensors. The overall research idea still needs a large number of tests for verification, but it can provide an important reference for research on channel feature extraction.