AI Beam Prediction Using Dynamic Reference Signal Groups
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Solution Overview
Problem
Conventional wireless communication networks face challenges in accurately predicting optimal receive beams due to the use of fixed beam patterns, which can lead to blocked beams and reduced measurement accuracy, especially during cell handovers and beam management.
Innovation Solution
A communication method and apparatus that integrates artificial intelligence to dynamically select groups of reference signal resources for model inference, allowing terminals to use different beams for each prediction, thereby avoiding blocked beams and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed beam patterns are used for model inference, then device complexity is reduced, but measurement precision deteriorates due to blocked beams
Solution Approach 1:
The patent applies dynamics by transitioning from fixed beam patterns to dynamic beam selection. The terminal device dynamically determines different groups of reference signal resources for different model inference operations, allowing the system to adapt to changing channel conditions and avoid blocked beams, thereby improving measurement precision while maintaining manageable complexity through structured resource groups.
2Measurement precision
If multiple groups of reference signal resources are configured, then measurement precision is improved by avoiding blocked beams, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing reference signal resources into multiple distinct groups, where each group contains reference signals that can be independently selected. This segmentation allows the terminal to choose appropriate groups based on channel conditions, improving measurement precision by avoiding blocked beams while managing complexity through organized resource categories.
Solution Approach 2:
The patent applies parameter changes by varying the selection of reference signal resource groups based on different operational conditions. The terminal device changes which group of reference signals is used for model inference depending on channel state, handover scenarios, and beam blocking conditions, thereby optimizing measurement precision without requiring all possible resource configurations to be simultaneously active.
3Measurement precision
If different groups of reference signal resources are selected for each prediction, then measurement precision is improved, but loss of time increases due to additional selection overhead
Solution Approach 1:
The patent applies preliminary action by pre-organizing reference signal resources into multiple groups before actual beam prediction operations. This preliminary structuring allows for rapid selection during model inference without requiring complex real-time analysis, thereby improving measurement precision through diverse resource selection while minimizing time loss through advance preparation of resource groups.
Data Source
AI summary
A communication method and apparatus are provided. The method includes: A first communication apparatus determines a first group of reference signal resources from multiple groups of reference signal resources. The first communication apparatus determines a first reference signal resource based on the first group of reference signal resources and a model. According to the method in this application, a group of reference signal resources is selected from the multiple groups of reference signal resources, and model inference is performed by using the selected group of reference signal resources.