A base station traffic prediction method and related device
By selecting neighboring base stations based on geographical distance and causal relationships, and by utilizing attention mechanisms and multi-scale decomposition methods, the problems of single and blind feature selection in base station traffic prediction are solved, thereby improving prediction accuracy and efficiency.
CN116744325BActive Publication Date: 2026-05-29CHINA MOBILE COMM LTD RES INST +2
2 Cites 2 Cited by
Patent Information
- Application Number
- CN202210210062.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-03-04
- Publication Date
- 2026-05-29
- Estimated Expiration
- 2042-03-04
AI Technical Summary
Technical Problem
Existing base station traffic prediction methods suffer from limited or blind selection of feature data, resulting in poor prediction accuracy.
Method used
By filtering neighboring base stations based on geographical distance and causal relationships between them, extracting feature data using an attention mechanism, and employing multiple predictors for multi-scale decomposition and weighted summation, base station traffic can be predicted.
Benefits of technology
It improves the accuracy and efficiency of base station traffic prediction, reduces interference from redundant features, and enhances the effectiveness of feature selection.
✦ Generated by Eureka AI based on patent content.
Abstract
The application provides a base station traffic prediction method and related equipment, and relates to the field of communication, wherein the base station traffic prediction method comprises the following steps: determining the adjacent base stations of a to-be-predicted base station according to the geographical distance information between base stations; determining the neighbor base stations in the adjacent base stations, and the historical traffic records of the neighbor base stations and the historical traffic record of the to-be-predicted base station have a causal relationship; performing feature extraction on the historical traffic records of the to-be-predicted base station and the neighbor base stations to obtain feature data; and predicting the predicted traffic of the to-be-predicted base station according to the feature data. In the screening process of the feature data object, the spatial factor is fully considered to avoid the singularity of feature data selection, and the causal relationship between the base station traffics is fully considered, so that the blindness of feature data selection is avoided, the redundant feature interference is reduced, the effectiveness of feature selection is improved, and the base station traffic prediction accuracy and efficiency are improved.
Need to check novelty before this filing date? Find Prior Art