Evaluation method and device for network key performance indicators

Abstract

Embodiments of the invention provide an evaluation method and a device for network key performance indicators. The method includes: acquiring multidimensional evaluation indicotor parameters of an evaluated network; acquiring a target KPI evaluation chart matched with the multidimensional evaluation indicotor parameters of the evaluated network from a preset network KPI evaluation chart generated form the source data of implemented networks; and acquiring KPI evaluation results corresponding to the multidimensional evaluation indicotor parameters of the evaluated network from the target KPI evaluation chart. By the embodiments, the target KPI evaluation chart mathched with the multidimensional evaluation indicotor parameters of the evaluated network is acquired from the preset network KPI evaluation chart generated form the source data of the implemented networks, thus increasing the matching degree of the actual business model of the present network and improving the accuracy of the network KPI evaluation.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a method and device for evaluating network key performance indicators. Background technique [0002] Before the implementation of the network engineering project, pre-evaluate the network KPI (Key Performance Indicators, key performance indicators), which can quantitatively evaluate the performance indicators and gains after the implementation of the network engineering project, so as to allocate resources reasonably. The commonly used network KPI evaluation, according to the experience data of the network, obtains the KPI evaluation data of the live network, and divides the KPI evaluation data into A / B / C network scenarios correspondingly, and the basic characteristic information of the network engineering project to be evaluated (such as frequency reuse Closeness or distance between stations) corresponds to one of the A / B / C network scenarios. For example, A / B / C ne...

AI Technical Summary

Problems solved by technology

The commonly used network KPI evaluation, according to the experience data of the network, obtains the KPI evaluation data of the live network, and divides the KPI evaluation data into A / B / C network scenarios correspondingly, and the basic characteristic information of the network engineering project to be evaluated (such as frequency reuse Closeness or distance between stations) corresponds to one of the A / B / C network scenarios. For example, A / B / C network scenarios are divided into loose multiplexing, medium multiplexing, and tight multiplexing according to the frequency reuse tightness. Three types of network scenarios, or divided into three types of network scenarios according to the distance between stations, long distance between stations, medium distance between stations, and near distance between stations, and then obtain the network KPI evaluation results. The evaluation data is divided into A / B / C network scenarios. The classification is too rough and simple, which reduces the accuracy of network KPI evaluation

[0003] In the prior art, before the implementation of the network engineering project, a static simulation is carried out for the set application scenario, and the theoretical value of the static index such as the load-to-interference ratio or signal noise is output, and then the theoretical value of the static index is used as the input value to import the network KPI In the dynamic simulation platform, the dynamic simulation index value is obtained, and the system performance evaluation of the network engineering project is carried out according to the obtained dynamic simulation index value, and the performance effect of the dynamic simulation evaluation is realized at the same time as the static simulation evaluation. However, the implementation of the network engineering project It is necessary to obtain accurate engineering parameters, electronic maps and other information before the implementation of the network engineering project, and it is difficult to obtain detailed engineering parameter information of the network engineering project when performing the KPI pre-evaluation of the bidding stage of the network engineering project before the implementation of the network engineering project, and because the network KPI It is difficult to match the dynamic simulation platform with the real network engineering business model, such as traffic distribution and traffic migration in the real network engineering business, resulting in a large difference between the dynamic simulation index value and the performance of the real network, reducing the accuracy of network KPI evaluation

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