Predictive Interference Modeling for CSI Reporting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless communication systems, particularly in 5G NR and LTE, face challenges in accurately reporting channel state information (CSI) due to rapid changes in interference levels, which reduce the effectiveness of channel quality indicator (CQI) reports and impact communication reliability.
Innovation Solution
The implementation of predictive modeling and interference estimation techniques by user equipment (UE) to forecast candidate interference levels for upcoming slots, using observed interference patterns and machine learning algorithms, enhances the accuracy of CSI reporting and improves communication reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional CSI reporting methods are used, then the system is simple to implement, but the accuracy of channel quality indicator reports deteriorates due to rapid interference changes
Solution Approach 1:
The patent applies preliminary action by having the network device pre-configure multiple interference measurement resource sets and multiple CSI report configurations before interference changes occur. The UE uses these pre-configured resources to measure interference and generate CSI reports proactively, rather than reactively responding to interference changes. This allows the system to anticipate and prepare for interference variations, improving measurement accuracy while managing complexity through structured pre-planning.
Solution Approach 2:
The patent implements dynamics by enabling the UE to dynamically select from multiple pre-configured interference measurement resource sets based on current channel conditions. The system transitions from static single-resource CSI reporting to dynamic multi-resource selection, where the UE can adaptively choose the most appropriate interference measurement resources according to rapidly changing interference patterns, thereby maintaining high measurement accuracy in dynamic environments.
2Measurement precision
If multiple interference measurement resources are configured, then the accuracy of interference estimation improves, but the signaling overhead and processing complexity increase
Solution Approach 1:
The patent applies segmentation by dividing the interference measurement resources into multiple distinct resource sets, where each set is configured for specific interference measurement purposes. Instead of overwhelming the system with a single large configuration, the interference measurement resources are segmented into manageable sets that can be selectively activated. This reduces signaling overhead by only transmitting and processing relevant resource configurations while maintaining comprehensive interference measurement coverage through multiple specialized sets.
3Speed
If CSI reporting is performed frequently, then the timeliness of channel state information improves, but the interference estimation accuracy deteriorates due to insufficient measurement time
Solution Approach 1:
The patent merges multiple interference measurement resource sets with different temporal characteristics to achieve both timeliness and accuracy. By combining resources that allow for both rapid reporting and extended measurement periods, the system can generate frequent CSI reports without sacrificing measurement precision. The merged resource configuration enables the UE to perform measurements over sufficient time intervals while still meeting timely reporting requirements through efficient resource utilization.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Certain aspects of the present disclosure provide techniques for enhancements to channel state information (CSI) reporting. A method that may be performed by a user equipment (UE) includes obtaining, from a network entity, a CSI reporting configuration for reporting CSI for a channel. The method further includes generating a model of an interference pattern for the channel, and predicting one or more candidate interference levels for one or more upcoming slots using the model. The method further includes reporting information regarding the candidate interference levels to the network entity.