Information acquisition method and communication apparatus

By using reference signal density to characterize reference signal pattern design and channel reconstruction model between terminal equipment and network equipment, and utilizing neural network model to determine communication resources, the problem of inaccurate channel information reconstruction in existing technologies is solved, achieving efficient and flexible channel information reconstruction and improved communication efficiency.

WO2026138648A1PCT designated stage Publication Date: 2026-07-02HUAWEI TECH CO LTD
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
HUAWEI TECH CO LTD
Filing Date
2025-12-18
Publication Date
2026-07-02

AI Technical Summary

Technical Problem

In existing technologies, reference signal pattern design or channel reconstruction based on neural networks lacks matching between terminal equipment and access network equipment, resulting in insufficient accuracy of channel information reconstruction, and lacks corresponding technical details and standard support.

Method used

By using reference signal density to characterize the reference signal pattern design model and channel reconstruction model between terminal equipment and network equipment, and utilizing neural network models to determine the reference signal pattern and communication resources, efficient reconstruction of channel information is achieved, signaling overhead is reduced, and communication efficiency is improved.

Benefits of technology

It improves the accuracy of channel information reconstruction and communication efficiency, enhances the flexibility and accuracy of neural network models, and ensures the alignment and synchronization of information between terminal devices and network devices.

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Abstract

The present application provides an information acquisition method and a communication apparatus. The method relates to the technical field of communications. The method comprises: a terminal device or an access network device determining a first neural network model, the first neural network model being associated with a first reference signal density, and the first neural network model being used for determining a first reference signal pattern; then, acquiring a communication resource of the first reference signal in the first reference signal pattern; and further, on the basis of the communication resource of the first reference signal, receiving the first reference signal on a first channel. By means of the method, a reference signal pattern design implemented on the basis of a neural network can be efficiently used between a terminal device and an access network device, thereby reducing signaling overheads, and helping to ensure the accuracy of reconstructed channel information.
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