5G Wireless Intelligent Propagation Model and Application of Simulation Engine in Production

Abstract

As an important means of evaluating 5G networks, simulation has always been a difficult problem in the industry. In order to improve the accuracy of simulation, this paper proposes a method based on the combination of live network test data and deep neural network to study the wireless propagation characteristics of wireless electromagnetic signals. The network test data reflects the real propagation of radio waves. Based on this data, cell characteristics and geographic characteristics are constructed, and the 5G wireless intelligent propagation model is established through the deep neural network training model to achieve accurate prediction of signal level values. Finally, through the test set data verification, the mean square error can reach 5.328, and the accuracy is significantly improved compared with the traditional propagation model.