The microwave radiative transfer modeling PWR (P. W. Rosenkranz) and back propagation neural network method are used to construct the models of forward modeling of downward radiance brightness temperature and inversion of atmospheric relative humidity profile respectively, and the channel selection of inversion of atmospheric relative humidity profile by hyperspectral microwave radiometer under clear sky conditions is studied. The research results show that the information content of 200 channels is greater than the information content of 7 channels of microwave radiometer and the increase of the detection channel can improve the inversion accuracy of the atmospheric relative humidity profile. When we use the first 120 channels of information content for simulation experiments, the inversion accuracy of the atmospheric relative humidity profile in the range of 0-2 km and 6-10 km increases by 4%~10%, and the inversion accuracy of the relative humidity profile in the range of 2-6 km increases by about 10%. When the channel continues to increase, the inversion accuracy of atmospheric relative humidity profile not improves much.