Interfered by a variety of factors, indoor positioning has been a research hotspot in wireless network. To improve the indoor positioning effect, aiming at the problem that the neural network has in indoor positioning accuracy of the wireless network, this paper designs a wireless network based on artificial neural networks. The first indoor wireless network collects relevant information, extracts indoor positioning data, and then uses neural network for data learning. It sets up a wireless network positioning model to improve the defects of the neural network. Finally, the simulation is carried out on the Matlab platform. The results show that the improved neural network overcomes the limitations of the traditional indoor localization methods, and achieves higher indoor localization accuracy of wireless networks. Moreover, the indoor localization efficiency has also been improved significantly.