Network optimization intelligent decision wizard system and automatic analysis method

Abstract

The invention belongs to the technical field of wireless communication network optimization and particularly relates to a network optimization intelligent decision wizard system and an automatic analysis method. The system comprises a database unit, an index library unit, a rule library unit, a node library unit and a wizard library unit, wherein the database unit is used for storing telephone traffic statistic data, Abis data, warning data and various parameter data in a wireless communication network; the index library unit is used for storing various telephone traffic indexes, an Abis data index, a warning data index and various parameter indexes, which are summarized and abstracted from the database unit; the rule library unit is used for acquiring data indexes from the index library unit and generating various rules through function calculation; the node library unit is used for generating independent and reusable nodes according to certain or combination of some of rules in the rule library unit; and the wizard unit is used for sequencing nodes according to an analysis flow and forming an intelligent decision analysis wizard. The system and the method can regulate a network problem processing flow, improve network optimization rate and network benefits and improve network service quality and continuous development capability.

Description

Technical field [0001] The invention belongs to a wireless communication network optimization technology, and specifically relates to a network optimization intelligent decision-making guide system and an automated analysis method. Background technique [0002] The scale of wireless communication networks has grown rapidly and greatly, and the complexity of networks has continued to increase, making network optimization as a long-term step-by-step practical system engineering, requiring advanced hardware equipment and testing methods, complete and powerful software support methods and relevant experience of optimization personnel , All of which pose a higher challenge to network optimization. [0003] The existing network optimization work basically adopts manual analysis methods, discovering problems through conventional means such as drive testing, complaints, indicator analysis, and alarm maintenance. The relevant information is not logically strong, has poor relevance, repetit...

AI Technical Summary

Problems solved by technology

[0005] Existing network optimization methods cannot objectively and comprehensively reflect the quality of network services. They are only based on KP index optimization, and the quality of optimization results depends entirely on the quality of the optimizers themselves.

Daily optimization work usually needs to extract indicators first, and then analyze the indicators. For network optimization personnel, these daily operations waste a lot of time

When optimizing, the specific optimization plan does not have a standard and strict plan, and the problem cannot be solved from the root cause. The problem cannot be solved, and the work efficiency is low, which brings about the loss of manpower, material resources and financial resources.

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