Clustering method for weak coverage problem area, and station planning method

Abstract

The invention discloses a clustering method for a weak coverage problem area, comprising the following steps: rasterizing a map; mapping coverage data into grids to determine weak coverage grids; and identifying, by using a clustering algorithm, successive weak coverage areas. The invention also relates to a station planning method comprising obtaining weak coverage problem areas by using the above method; calculating the distance between each grid in the weak coverage problem area and the station within the network, selecting the grid, in the problem area, with a minimum distance to the station within the network in a threshold range as an alternative planning point, retaining the problem areas with the alternative planning points, and deleting the others, wherein the threshold is determined according to the coverage distance of a macro station and a micro station. The method achieves unified planning area through the clustering algorithm, carries out the correlation analysis of the problematic grids, and reduces the analysis difficulty and the workload by means of the contiguous processing. The method automatically performs the planning grid selection, and improves the efficiency of the pre-planning points.

Description

technical field [0001] The invention relates to the technical field of network planning of communication technology, in particular to a clustering method and a site planning method for weak coverage problem areas. Background technique [0002] With the development of mobile network technology, deep and continuous coverage has become the basis for ensuring user perception. The weak coverage problem caused by insufficient network planning and site deployment will directly affect the user's service perception and speed experience. Therefore, in the network planning work, how to identify the relevant scenarios where the planned site deployment is insufficient and carry out pre-planning has always been an important part of the work. [0003] In the prior art, manually plan and select points (in this application, point selection refers to selecting a site), compare the map, grid it, and conduct comprehensive analysis with related different types of data, and then perform a compre...

AI Technical Summary

Problems solved by technology

[0005] 1. The efficiency is very low, hundreds of sites are manually operated, the workload is heavy, and it takes up a lot of labor costs;

[0006] 2. The result of filling points is too subjective, there is no uniform standard for manual filling points, and the points made by different people vary greatly;

[0007] 3. Working with a single grid greatly increases the difficulty and workload of analysis

Images