Base station location optimization is a research hotspot in mobile communication. A good base station location scheme can not only save resources, but also improve users' communication experience. However, the base station layout is often faced with a complex problem of multi-parameter, multi-constraint and nonlinearity, which is difficult to be solved by traditional optimization methods. In this paper, an intelligent base station layout method based on big data is proposed. Firstly, the radio wave propagation model based on deep learning is built according to the measured big data of electromagnetic environment, which makes the propagation model more accurate. Then, the spatial adaptive learning method is utilized to construct the base station location optimization model on the basis of the propagation model. By selecting the base station placement points having poor performance with a small probability in each iteration process, the algorithm can avoid falling into local optimality. The experimental simulation results show that the proposed base station layout method has fast convergence speed, wide coverage rate and good user communication experience.