Method and device for obtaining cell relation model and method and device for recommending cell handover guidance parameter

Abstract

The invention provides a method and device for obtaining a cell relation model and a method and device for recommending a cell handover guidance parameter, and relates to the field of artificial intelligence (AI) and the technical field of data communication. The method for obtaining a cell relation model comprises the following steps: separately carrying out feature extraction on a topological graph representing historical traffic statistic data of N cells in a specified area and a dual graph corresponding to the topological graph through a GCN (graph convolutional neural network) to obtain first feature information of the topological graph and second feature information of the dual graph; based on the first feature information and the second feature information, determining fusion feature information of the N cells; fitting the fusion feature information of the N cells and the historical handover guidance parameters of the N cells to obtain a cell relation model used for indicating the function relation among the network state parameters, the handover guidance parameters and the performance indexes of the N cells in the specified area; and finally, based on the cell relation model, determining a target handover guidance parameter through a gradient descent algorithm. The network performance obtained by the method is better in effect.

Description

technical field [0001] The present application relates to the field of artificial intelligence (AI) and the field of data communication technology, and in particular to a method and device for obtaining a cell relationship model and recommending cell handover guidance parameters. Background technique [0002] In a wireless cellular network, uneven distribution of users leads to unbalanced load among cells (that is, areas covered by the wireless network). Due to the large number of users and large business demand in high-load cells, it is easy to cause insufficient network resources, and it is difficult to guarantee the quality of service for users; at the same time, the number of users in surrounding idle cells is small and the load is small, and its network resources cannot be fully utilized. . [0003] For this reason, a handover optimization (handover optimization, HO) technology is currently proposed, and the HO technology plays an important role in both inter-cell load...

AI Technical Summary

Problems solved by technology

[0004] Usually, in order to configure the handover guidance parameters on each cell, the network status and performance indicators to be achieved of each cell can be analyzed, and the handover guidance parameters can be configured based on expert experience or preset configuration rules, but this method can only For a simple network environment, for a complex network environment, the mutual influence between cells is not fully considered, so after the handover parameters are configured, the user may not be able to switch to a high-quality cell or the service quality of the cell after the handover still cannot meet the needs of the user

Images