Measurement Feedback Report Types for AI Beam Prediction
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Solution Overview
Problem
When artificial intelligence is introduced for beam prediction in communication systems, network side devices struggle to accurately understand the measurement reports sent by terminals due to varying types and quantities of information, such as reference signal and channel quality information, leading to misinterpretation.
Innovation Solution
A measurement feedback processing method and apparatus that includes sending and receiving first information to determine association information of measurement reports, which includes measurement feedback function information, a first quantity, and a second quantity, to clarify the type and quantity of target information, such as reference signal and channel quality information, ensuring accurate interpretation by the network side device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AI model is introduced for beam prediction with multiple measurement report types, then beam prediction capability is improved, but network side device interpretation accuracy deteriorates
Solution Approach 1:
The patent segments the measurement report structure by introducing distinct report types (normal, prediction, enhanced) with specific identification mechanisms. Each report type has defined characteristics regarding quantity of target information, allowing the network side device to accurately identify and interpret the appropriate report format based on the report type indicator.
Solution Approach 2:
The patent introduces an intermediary mechanism (report type indicator and quantity information) that mediates between the terminal's diverse measurement reports and the network side device's interpretation requirements. This intermediary layer enables accurate mapping between different report types and their corresponding information quantities, resolving the interpretation ambiguity.
2Adaptability or versatility
If quantity of target information varies with measurement report type, then measurement report flexibility is improved, but network side device understanding accuracy deteriorates
Solution Approach 1:
The patent implements dynamic measurement report structures where the quantity of target information adapts based on the report type. The network side device receives dynamic information about the quantity of target information along with each report, enabling accurate interpretation despite varying information quantities across different report types.
Solution Approach 2:
The patent changes key parameters (report type indicator, quantity of target information) to enable the network side device to accurately interpret measurement reports with varying information quantities. By explicitly signaling these parameters, the system maintains both flexibility in report content and accuracy in interpretation.
Data Source
AI summary
A measurement feedback processing method includes: a first device sends first information to a second device, where the first information is used to determine at least one of the following of a measurement report: measurement feedback function information indicating a measurement report type; a first quantity; and a second quantity, where the measurement report type includes any one of the following: a normal measurement report, a prediction measurement report, and an enhanced measurement report, the first quantity is determined based on a measurement report configuration.