Intelligent Hierarchical Neighbor Cell Planning Based on Neural Network

In order to improve the timeliness of communication network neighbor planning, solve neighbor omission, enhance planning accuracy, and effectively deal with challenges such as excessive neighbors, this paper proposes an intelligent hierarchical neighbor cell planning method based on neural networks. This method fully utilizes the engineering parameters of communication base stations, existing network indicator data, and existing network neighbor configuration data. Different from traditional planning methods that only consider distance and azimuth, it innovatively introduces factors such as Delaunay triangulation, distance multiple, overlapping coverage area coefficient, and neighbor hierarchy. By using a neural network model, the existing network experience is deeply learned, and new base station neighbors in the communication network are planned intelligently. This method introduces new planning factors, greatly improving the accuracy and timeliness of neighbor planning, and better coping with the evolving communication network environment.