Base station classification and identification method and system based on user parameter characteristics

Abstract

The present invention relates to a method for establishing a base station classification model based on user parameter characteristics, including collecting demand parameters of terminal users; performing preprocessing on the demand parameters according to a predefined base station type, and obtaining a training sample set containing training sample data; Wherein, the training sample data includes the terminal user demand information and the base station type information corresponding to the terminal user demand information; the iterative training of the model is performed by using the training data set, and a base station classification model is obtained.

Description

technical field [0001] The invention relates to the technical fields of communication and computer, in particular to a base station classification and identification method and system based on user parameter characteristics. Background technique [0002] With the continuous advancement of science and technology, communication network technology has also developed rapidly. In order to meet the increasing mobile data traffic, the number of device connections and the needs of differentiated new business applications, it is foreseeable that a large number of base stations will be established to serve End users will become the basis for building the future era of human-machine-thing interconnection. [0003] In the prior art, the base stations established in the communication network usually have unified functions, but the service requirements of the end users served by the base stations are various. For example, in application scenarios such as smart homes and smart grids, end u...

AI Technical Summary

Problems solved by technology

[0004] However, the current wireless communication network implements the establishment of a unified base station. Due to the lack of classification and selection methods for base stations with different functional categories, it is impossible to specifically divide the functional categories of base stations according to different end user service scenarios.

However, this unified type of base station will lead to low resource utilization and poor user performance. In practical applications, it may not be able to meet terminal diversity and extreme service requirements, and also cause waste of base station resources. Reasonable allocation of base station resources not only reduces service efficiency, but also increases the cost burden

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