Dual-carrier and carrier aggregation adaptive adjustment method, device and apparatus and medium

Abstract

The invention discloses a dual-carrier and carrier aggregation adaptive adjustment method, device and apparatus and a medium. The method comprises the following steps: acquiring a real-time service index of a cell; matching the real-time service index with a historical service index; if the matching result meets the preset condition, predicting the service according to a preset algorithm, and obtaining a prediction result of the service index value; according to the prediction result and the cell type to be expanded, when the cell reaches a threshold corresponding to the type of the cell, outputting a corresponding pre-adjusted dual-carrier and carrier aggregation model; and obtaining an index value of each service index under the same condition as the configuration of the method for pre-adjusting the dual-carrier and carrier aggregation, and correcting the model of the pre-adjusting dual-carrier and carrier aggregation according to each index value so as to obtain a self-adaptive adjustment model of the dual-carrier and carrier aggregation.

Description

technical field [0001] The present invention relates to the field of communication technologies, and in particular to an adaptive adjustment method, device, equipment and medium for dual-carrier and carrier aggregation. Background technique [0002] With the gradual increase of 4G users, LTE single-carrier in hotspot areas will not be able to meet users' demands for large bandwidth and high capacity. Without adding hardware, the base station is equipped with dual-carrier function and carrier aggregation (CA) function, which can make full use of existing frequency resources and offload users on a single carrier to improve system throughput, cell capacity and user perception. Purpose. [0003] For the configuration adjustment of LTE dual-carrier and carrier aggregation, at present, network optimization engineers mainly evaluate according to recent indicators, estimate approximate values ​​based on optimization experience, and configure dual-carrier and carrier aggregation (CA...

AI Technical Summary

Problems solved by technology

[0005] 1. Corresponding to the wireless network whose business model is constantly changing, it is unreasonable to configure dual-carrier and carrier aggregation (CA) based on recent indicators to evaluate a static service demand value

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 static configuration based on empirical evaluation is relatively high in certain periods of time, which easily leads to waste of software license resources. ; and in certain periods of time, dual-carrier and carrier aggregation (CA) function configuration is insufficient, and it is difficult to absorb enough users and provide better network service quality

[0006] 2. Roughly adjust based on manual optimization experience, relying on the optimization experience of network optimization engineers, it is difficult to guarantee a stable adjustment effect, and it is impossible to make accurate evaluations based on historical big data, and there are certain adjustment deviations

[0007] 3. The cost of dual-carrier and carrier aggregation (CA) software license (license) is relatively expensive, and the importance of manually evaluating the rationality and efficiency of resource allocation puts more and more pressure on the configuration and maintenance of network resources.

[0008] 4. Manual wireless resource management, the process from evaluation to optimization is complicated and takes a long time, it is difficult to dynamically adapt to the business, and the amount of data analysis is large, so it is difficult to accurately configure each cell

It is difficult to realize real-time adjustment and dynamic configuration of license resources in dual-carrier and carrier aggregation (CA) manually

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