Precoded SRS for Interference Covariance Prediction in URLLC
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently configuring control signals for reference signal precoding, particularly in ultra-reliable low-latency communications (URLLC), where CSI reporting increases latency and signaling overhead, impacting service reliability.
Innovation Solution
A method where user equipment (UE) predicts interference covariance matrices at future times and precodes sounding reference signals (SRS) based on these predictions, allowing base stations to determine optimal CSI parameters for reduced latency and improved reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CSI reporting is performed in conventional wireless communication systems, then channel quality information is obtained for reliable communication, but signaling overhead and latency increase
Solution Approach 1:
The UE performs interference measurements and determines interference covariance matrices in advance for future time instances before actual data transmission occurs. This preliminary action allows the base station to have pre-computed precoding information ready, reducing the need for extensive real-time CSI reporting and lowering signaling overhead while maintaining reliable communication.
Solution Approach 2:
The UE transmits SRS signals that are precoded using the predicted interference covariance matrix, effectively creating a copy of the interference conditions at future time instances. This allows the base station to infer channel state information from the precoded SRS without requiring complete CSI reporting, thereby reducing signaling overhead while preserving communication reliability.
2Reliability
If CSI reporting is performed in conventional wireless communication systems, then channel quality information is obtained for reliable communication, but latency increases
Solution Approach 1:
The system computes interference covariance matrices for future time instances in advance, before actual data transmission is needed. This preliminary computation eliminates the need for time-consuming real-time CSI processing and reporting, thereby reducing latency while ensuring reliable communication through pre-optimized precoding.
Solution Approach 2:
The interference covariance matrices are dynamically predicted for multiple future time instances, allowing the system to adapt to changing channel conditions without requiring continuous real-time feedback. This dynamic approach reduces latency by eliminating repeated CSI reporting cycles while maintaining communication reliability through updated precoding information.
3Measurement precision
If interference measurements are performed for future time instances, then accurate interference covariance matrices are obtained, but processing complexity increases
Solution Approach 1:
The UE performs interference measurements and computes interference covariance matrices in advance for future time instances. By doing this preliminary work before actual data transmission, the system achieves accurate interference characterization without the need for complex real-time processing during critical transmission periods, thus balancing measurement precision with manageable processing complexity.
Solution Approach 2:
The UE autonomously performs interference measurements and computes its own interference covariance matrices without requiring complex network-side processing assistance. This self-service approach allows accurate interference measurement while keeping the overall system processing complexity distributed and manageable, rather than concentrating it in the base station.
Data Source
AI summary
Methods, systems, and devices for wireless communications are described. A user equipment (UE) may precode sounding reference signals using an interference covariance matrix to report channel quality information to a base station. For example, a UE may receive an indication of a future time from a base station. The future time may correspond to a future time for which the UE may predict an interference covariance matrix. In some cases, based on receiving the indication, the UE may monitor for interference in one or more interference measurement resources. In some examples, the UE may then determine the predicted interference covariance matrix and may transmit a sounding reference signal to the base station. The sounding reference signal may be precoded based on the predicted interference covariance matrix. In some cases, the UE may receive a downlink signal from the base station at the future time or at a second time.