A traffic adaptive method between LTE systems

Abstract

The invention provides a method for traffic self-adaptation between LTE systems. The method includes: obtaining the data source to be analyzed based on the matching degree between the current service and the forecast result of the historical service; and based on the data source to be analyzed, adjusting according to a predetermined step to obtain the current interoperability parameter value. The present invention proposes a flow self-adaptive method between LTE systems, and adjusts the matching degree of historical service prediction results and current services in combination with optimization targets to obtain interoperable parameter values; use the obtained interoperable parameter values ​​to perform LTE system interoperability, The purpose of the implementation is to allow users to stay on the LTE network as much as possible. The method of the present invention performs dynamic evaluation based on historical data, does not need to rely on manual optimization experience, realizes self-adaptive adjustment of traffic, and can achieve stable adjustment effect.

Description

technical field [0001] The present invention relates to the field of computer technology, and more specifically, to a method for traffic self-adaptation between LTE systems. Background technique [0002] At present, 4G-2G traffic control is mainly controlled by LTE interoperability parameters. The purpose of interoperability parameters at the current stage is to allow data users to reside on the LTE network as much as possible. At present, the configuration of 4G-2G network interoperability parameters is mainly evaluated by network optimization engineers based on recent indicators, and static configuration is adopted based on approximate values ​​based on optimization experience. [0003] The optimization of existing interoperability parameters has the following disadvantages: [0004] (1) For a wireless network whose business model is constantly changing, it is unreasonable to evaluate a static value based on recent indicators for configuration. In order to cope with the ...

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Problems solved by technology

[0004] (1) For a wireless network whose business model is constantly changing, it is unreasonable to evaluate a static value based on recent indicators for configuration

In order to cope with the ever-changing business model, the number of evaluations needs to be very frequent, and the amount of data is too large to evaluate. In addition, the evaluation of static configuration values ​​is relatively high in certain periods of time, which is likely to cause the deterioration of indicators, and in certain periods The relative configuration is too low to attract enough users

[0005] (2) Rough adjustment based on manual optimization experience, relying too much on the optimization experience of network optimization engineers, it is difficult to guarantee a stable adjustment effect, and it cannot be accurately evaluated based on historical big data, and there is a certain adjustment deviation

[0006] (3) At the same time, the scale of wireless networks continues to expand, multi-network integration, and the workload of network optimization continue to increase. Most of the energy is devoted to network expansion and maintenance, and it is difficult to spare more personnel and time to improve network performance.

[0007] At present, many automatic parameter adjustment studies are limited to making corresponding adjustments for real-time business changes, without considering historical optimization big data and actual parameter adjustment effects, making it difficult to optimize network index performance

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