Beam-Aware Interference Data Collection for ML-Based Prediction
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Solution Overview
Problem
Existing wireless communication systems, particularly 5G NR, face challenges in efficiently collecting interference data for machine learning-based interference prediction, which is crucial for improving network performance and resource allocation.
Innovation Solution
A method and apparatus are provided to configure user equipment (UE) to report interference measurement information and receive beam information, transmit interference measurement reference signals, and collect corresponding data for ML-based interference prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beam information is collected for each interference measurement resource to improve ML-based interference prediction accuracy, then measurement precision is improved, but device complexity increases due to additional reporting requirements
Solution Approach 1:
The interference measurement process is segmented by associating different receive beams with different interference measurement resources. Each interference measurement resource is specifically linked to a receive beam configuration, allowing the UE to report interference measurements in a structured, beam-specific manner. This segmentation enables precise interference measurement per beam while organizing the reporting process to manage complexity through standardized procedures.
Solution Approach 2:
The system implements feedback mechanisms where the UE reports both interference measurement results and corresponding receive beam information to the network. This feedback loop enables the network to accumulate training data for ML-based interference prediction models. The feedback includes detailed beam information that helps the network understand the spatial characteristics of interference, improving prediction accuracy while using standardized feedback formats to control reporting complexity.
2Measurement precision
If detailed beam information is reported for each interference measurement, then interference prediction accuracy is improved, but loss of time increases due to extended measurement and reporting procedures
Solution Approach 1:
The network configures the UE with multiple interference measurement resources and associated receive beam configurations in advance, before actual interference measurements are performed. This preliminary configuration allows the UE to have ready-to-use beam settings and measurement parameters, reducing the time required during actual measurement and reporting phases. The pre-configuration includes linking specific receive beams with specific interference measurement resources, enabling efficient execution.
Solution Approach 2:
The system enables continuous accumulation of interference measurement data and beam information across multiple measurement instances. Rather than performing complete measurement cycles repeatedly, the UE continuously reports interference measurements and beam information as data becomes available. This continuous data collection feeds the ML-based prediction model in real-time, maintaining high measurement precision while minimizing idle time between measurements through overlapping measurement and reporting operations.
Data Source
AI summary
An apparatus for wireless communication at a UE is provided. The apparatus is configured to receive a configuration to report interference measurement information indicating interference measurements for each interference measurement resource of a set of interference measurement resources and Rx beam information used by the UE for performing interference measurements on each interference measurement resource of the set of interference measurement resources. The apparatus is configured to receive a set of interference measurement reference signals on the set of interference measurement resources, and to measure interference on each interference measurement resource of the set of interference measurement resources to obtain the interference measurement information. Each interference measurement is through one Rx beam of a set of Rx beams. The apparatus is configured to transmit, in response to the received set of interference reference signals on the set of interference measurement resources, the interference measurement information, and corresponding Rx beam information.