A Method for Evaluating Operational Quality of Complex Wireless Communication Networks Based on Fuzzy Analysis

Abstract

The invention discloses a complex wireless communication network operation quality evaluation method based on fuzzy analysis. The complex wireless communication network operation quality evaluation method is characterized by comprising the following steps: acquiring latest data from a database, and performing clustering, association analysis, prediction and data mining so as to obtain a clustering result data set; evaluating indexes of different cells to be evaluated according to the clustering result data set, obtaining an index weight omega by using a weight hierarchy fuzzy analysis method, performing reliability analysis on index evaluation personnel, thereby obtaining an evaluation personnel reliability coefficient C. The invention discloses a compressive complex wireless communication network operation quality evaluation method based on combination of comprehensive weight hierarchy fuzzy analysis and association variation, and aims at evaluating wireless communication network operation quality indexes of an overall area and subareas by virtue of multiple data mining techniques and wireless communication network knowledge such as the fuzzy theory and the association variation coefficient, and decision support can be provided for optimization of wireless communication networks.

Description

Technical field: [0001] The invention relates to the fields of wireless network and data mining, and is specifically used in a mobile communication network optimization system to evaluate the operation quality of complex wireless communication networks, as a basis for adjusting network quality, so that the network can reach the best operation state. Background technique: [0002] The mobile communication network is a dynamic and complex wireless network. Due to factors such as uneven distribution of traffic density, increasingly tight frequency resources, complex and diverse network configurations, and long-term changes, the service quality of the existing network cannot achieve the best, and the huge investment has not obtained the highest return. All of these Operators are required to collect and analyze data on the mobile communication network to find out the reasons that affect network quality in order to make various adjustments, optimize resource allocation, and set ne...

AI Technical Summary

Problems solved by technology

Each tool can only focus on one aspect and realize a single function; ②data cannot be shared and integrated, and the analysis efficiency is low

There is no integration of drive test data, traffic statistics data, network resource data, etc., and no comprehensive analysis and utilization; ③The degree of automation is not high

There is no historical data of network operation, no accumulation of experience, no knowledge management function, so work suggestions for network optimization cannot be automatically formed, and there are too many places that require manual intervention; ④Network management personnel cannot timely understand network operation performance

There are many types of network operation performance indicators, and the calculation methods are relatively complex and often change. The management cannot obtain the actual operation indicators of the network in a timely and correct manner; Accurate, lack of historical data, lack of organization and utilization of network optimization data

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