Big data analysis based self-organizing network and information returning method thereof

Abstract

The invention relates to a big data analysis based self-organizing network, which mainly solves the problems of singleness of the collected information and low information returning efficiency in the prior art. The self-organizing network comprises an element management system (EMS), a base station, a terminal, a multipurpose device and a dedicated device, wherein the base station comprises a microcellular, a pico cellular, a femto cellular, and a macro cellular, the EMS is in wired connection with the macro cellular, the multipurpose device is connected with the macro cellular, the pico cellular and the microcellular, the dedicated device is connected with the femto cellular, the multipurpose device and the dedicated device are used for collecting terminal business data information and network operation and maintenance information and ranking the information, so that the business data information and network operation and maintenance information with high priority are returned back to the base station rapidly. Through adoption of the self-organizing network, performance parameters of the network are enriched, information returning efficiency is improved, self-healing function of the self-organizing network can be realized in advance, network self-evolution is finished, and the self-organizing network is applicable to 4G communication.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to an ad hoc network for realizing self-evolution of the network. Background technique [0002] The mobile self-organizing network improves the self-organizing ability of the network through the self-configuration, self-optimization and self-healing of the mobile communication network, ensures the reliable operation of the network, provides a flexible network resource allocation mechanism and good quality of service QoS, and ensures mobile services. Manual intervention of high-cost network operators can effectively reduce network deployment and operation costs. [0003] However, with the rapid development of mobile Internet, Internet of Things and cloud computing technologies, the amount of data generated in the network is increasing exponentially, and the "big data era" is officially coming. However, in terms of data presentation, it is more one-dimensional. Only...

AI Technical Summary

Problems solved by technology

However, in terms of data presentation, it is more one-dimensional. Only macrocells in self-organizing networks collect network operation and maintenance information, while microcells, picocells, and femtocells only collect and process business data information. These network performance parameters cannot describe network information. The details, but can not reflect the customer's perception

Therefore, the existing self-organizing network architecture and equipment can no longer meet the needs of users, and the existing information return method is inefficient, so that the base station cannot quickly obtain these key information, which in turn affects the self-healing function of the self-organizing network, and cannot Realize network self-evolution

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