Wireless Node CSI Reporting Timing for AI-Based Feedback
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Solution Overview
Problem
The integration of ML/AI-based CSI reporting in wireless communication systems requires different processing capabilities and unit occupation times compared to traditional CSI reporting, leading to inefficiencies and potential waste of processing resources.
Innovation Solution
A method and apparatus that dynamically adjust the processing unit occupation time based on the type of CSI reporting, whether it is ML/AI-based or traditional, ensuring optimal allocation and utilization of processing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ML/AI-based CSI reporting is introduced to enhance CSI feedback accuracy, then CSI feedback accuracy is improved, but processing unit occupation time increases
Solution Approach 1:
The patent applies dynamics by making the processing unit occupation time configurable and adaptable based on the CSI reporting type. The system dynamically adjusts the time resources allocated for processing between traditional and ML/AI-based CSI reporting methods, allowing the processing duration to be optimized according to whether machine learning techniques are employed, thereby resolving the contradiction between improved accuracy and increased time consumption.
2Device complexity
If a unified processing time is allocated for all CSI reporting types, then system design is simplified, but processing resources are wasted
Solution Approach 1:
The patent implements local quality by allocating different processing time resources to different CSI reporting types based on their specific needs. Instead of applying a uniform processing time across all CSI reports, the system tailors the processing duration to match the computational requirements of each reporting type (traditional vs. ML/AI-based), thereby avoiding waste of processing resources while maintaining manageable system design through structured time allocation.
3Reliability
If processing unit occupation time is extended to accommodate ML/AI calculations, then calculation completion is ensured, but system productivity decreases
Solution Approach 1:
The patent applies periodic action by implementing a structured time allocation mechanism where processing units are assigned to ML/AI-based CSI reporting during specific time periods and to traditional CSI reporting during other periods. This periodic scheduling ensures that ML/AI calculations receive sufficient time to complete reliably while preventing continuous occupation of processing units, thereby maintaining system productivity through organized temporal distribution of computational tasks.
Data Source
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AI summary
Disclosed in the present application are a method and apparatus used in a node for wireless communication. The method comprises: a first node receiving first signaling; receiving a first RS in a first RS resource; and sending first channel information, wherein the starting of a first symbol which carries the first channel information is not earlier than a Y-th symbol after the last symbol which is occupied by the first signaling; the value of Y is related to whether the first channel information comprises a first type, and the first type meets at least one of the following conditions: channel information which is recovered by a receiver on the basis of the received first type is unknown to the first node; a generator for generating the first type is obtained on the basis of training; and the first type does not belong to CSI which is defined by 3GPP Rel-17 or a previous version. The present application improves the processing of CSI reporting in different scenarios, and optimizes the occupation time of a processing unit according to requirements, thereby avoiding the waste of the processing capability while meeting the requirements of CSI reporting for the processing capability.