A base station clustering method based on density and minimum distance in an ultra-dense network

Abstract

The invention discloses a base station clustering method based on density and minimum distance in an ultra-dense network, comprising the following steps: firstly, calculating the distribution densityand clustering density threshold value of each micro-cell base station in the ultra-dense network, so that the micro-cell base stations of which the distribution density is greater than the clusteringdensity threshold value form an initial clustering center pool; calculating the minimum value of the distance between each micro-cell base station in the initial cluster center pool and the micro-cell base station with the distribution density higher than that of the micro-cell base station, defining the product of the distribution density of the micro-cell base stations and the minimum distanceas the weighted distribution density, and obtaining a to-be-selected cluster center pool according to the weighted distribution density; calculating a cluster center isolation distance, and sequentially removing the cluster center with a smaller weighted distribution density value in two cluster centers of which the distance between every two cluster centers is greater than the cluster center isolation distance in the to-be-selected cluster center pool from the to-be-selected cluster center pool; and finally, taking the number of cluster centers in the to-be-selected cluster center pool and the geographic position of the cluster center base station as parameters of traditional K-means algorithm, and executing K-means algorithm to obtain a clustering result. According to the method, the problem of non-uniform clustering is solved.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, is applied to the management of micro-cell base stations in an ultra-dense network, and specifically relates to a base station clustering method based on density and minimum distance in an ultra-dense network. Background technique [0002] With the rapid development of mobile communication technology, the communication devices connected to the network are increasing explosively, which makes the already huge network structure more complicated. At the same time, users' demand for data traffic is also increasing sharply, and wireless networks will face enormous pressure and challenges. In an ultra-dense network, the system capacity of the wireless network can be greatly improved by densely deploying micro-cell base stations in the cell. However, due to the dense deployment of a large number of base stations, the interference problem in the network is becoming more and more serious, a...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a base station clustering method based on density and minimum distance in an ultra-dense network, which can dynamically cluster a large number of base stations according to changes in the network topology, and avoid falling into a local optimal solution by screening the cluster center points It improves the accuracy of clustering and accelerates the convergence speed of clustering, and solves the problem of uneven clustering results in traditional solutions. It is suitable for efficient management of base stations in ultra-dense networks. The specific technical solutions are as follows:

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