In order to adjust the parameters of cell antennas dynamically according to the real-time coverage in the new generation mobile wireless network, it is necessary to predict the wireless coverage efficiently and accurately. The traditional solution method is to judge the antenna parameters by accurate field strength prediction in the target area. The method is accurate but wastes large amounts of computing resources, which cannot meet the actual needs of 5G and beyond 5G mobile networks to dynamically adjust the radio frequency parameters through real-time coverage prediction. Here the algorithm based on deep neural network was proposed to predict the coverage under given antenna parameters in order to replace the accurate field strength prediction of the target area. Numerical results show that the algorithm can keep the accuracy of the calculation while significantly reducing the computing resources, which provides basic reference data for 5G dynamic network planning.