Network performance evaluation method and device

Abstract

The invention discloses a network performance evaluation method which is characterized by comprising the following steps of collecting evaluation data at a sampling point, performing classified processing on the collected evaluation data and storing the collected evaluation data; establishing an evaluation model of network performance evaluation standards, wherein the evaluation model is a corresponding relation between the evaluation data and perceptibitity of the user; after receiving query information, performing corresponding analysis on the evaluation data in the query information according to the evaluation model and outputting analysis results. The invention further discloses a network performance evaluation device. By means of the network performance evaluation method and device, network performance and using feeling of the user are combined, therefore, perceptibitity of the user is reflected truly, and accuracy on network performance evaluation is increased.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a method and device for evaluating network performance. Background technique [0002] Grasping the real experience of customers using the network is the driving force and direction of network optimization development. The optimization work at this stage is mainly based on data such as drive tests, performance, alarms, complaints, and signaling to locate network problems in their respective dimensions. When analyzing these data, there are the following problems: [0003] 1. Drive test data can directly reflect user perception, and the data message parameters are complete, but because the data is a sampled simulation test, it has large limitations and is difficult to accurately evaluate; [0004] 2. Performance data, MR data, parameter configuration and alarm data can better evaluate network quality, but it is difficult to reflect user perception and accurately loca...

AI Technical Summary

Problems solved by technology

[0003] 1. Drive test data can directly reflect user perception, and the data message parameters are complete, but because the data is a sampled simulation test, it has large limitations and is difficult to accurately evaluate;

[0004] 2. Performance data, MR data, parameter configuration and alarm data can better evaluate network quality, but it is difficult to reflect user perception and accurately locate users;

[0005] 3. Complaint data can directly reflect the user's perceived situation, but it can only express the phenomenon of network problems, and cannot locate the specific cause of the problem;

[0006] 4. Signaling data can analyze network anomalies in detail, but due to the large amount of information, it is not conducive to quickly assessing the perception of the entire network

[0008] 1. The relevance of various types of data has not been fully explored, and in the process of being used for customer perception, it only reflects problems in their own dimensions, and cannot be fully combined to get as close to customer perception as possible;

[0009] 2. Due to the variety of data and the large amount of data, manual extraction and analysis will face a great consumption of manpower and time;

[0010] 3. The current methods are all based on professional testing equipment and platforms, and are collected and analyzed by professionals, which have great limitations in coverage;

[0011] 4. Subjectively equate the network indicators with the customer's use experience directly, which cannot truly reflect the customer's real perception

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