AI Beam Model Matching for Accurate Terminal Beam Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In communication systems, the accuracy of beam measurement using AI models is compromised due to the terminal's inability to obtain the necessary information for the AI beam model, leading to inaccurate beam prediction results.
Innovation Solution
A method for determining an AI beam model involves a terminal receiving an AI beam model from a network side device and determining a first receive beam characteristic, which includes sending an AI beam model request and/or a second receive beam characteristic to the network side device, and using indication information or default rules to establish a matching receive beam characteristic, thereby improving beam prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the terminal uses an AI model for beam measurement prediction, then the beam prediction capability is enhanced, but the accuracy is compromised due to the terminal's inability to obtain necessary AI beam model information
Solution Approach 1:
The network side device performs preliminary action by determining the AI beam model in advance and sending it to the terminal before beam measurement prediction is performed. This ensures the terminal has the necessary model information to achieve accurate predictions without requiring complex real-time information exchange during measurement.
Solution Approach 2:
The AI beam model acts as an intermediary that bridges the network side device and terminal. The network side device determines the model based on network conditions and parameters, then transmits it to the terminal, which uses the model for local prediction. This intermediary approach allows accurate predictions while keeping the terminal's information requirements manageable.
2Measurement precision
If the terminal obtains detailed AI beam model information, then the beam prediction accuracy improves, but the device complexity and information processing requirements increase
Solution Approach 1:
The complex AI beam model determination process is extracted from the terminal and performed exclusively by the network side device. The terminal only needs to receive and use the pre-determined model, avoiding the complexity of model creation while still benefiting from accurate predictions. This extraction resolves the contradiction by centralizing complexity where it can be managed most effectively.
Data Source
AI summary
The present disclosure provides an AI beam model determination method, a device, and a storage medium. The method includes receiving an AI beam model sent by a network side device, and determining a first receive beam characteristic corresponding to the AI beam model.