Sidelink Beam Blockage Prediction for AI-Assisted Beam Management
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Solution Overview
Problem
Wireless communication networks face interference and congestion due to beam blockage, which degrades performance and is particularly challenging for lower capability UEs with limited power and coverage.
Innovation Solution
Utilize sidelink channels for beam blockage prediction and mitigation by sharing beam blockage information between network nodes, enabling AI/ML-assisted predictive beam management to anticipate and resolve blockages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beam blockage prediction is implemented using traditional uplink channels, then beam management accuracy is improved, but network complexity and latency increase due to direct feedback requirements
Solution Approach 1:
The patent introduces a sidelink channel as an intermediary communication path between UEs and network nodes. Instead of requiring direct uplink feedback from blocked UEs, the system uses sidelink channels to relay beam blockage information through intermediate network nodes, reducing the complexity burden on individual UEs while maintaining detection accuracy.
Solution Approach 2:
The system performs beam blockage prediction in advance using measurement information from sidelink channels before actual communication failures occur. By predicting blockages proactively and using AI/ML models to anticipate issues, the system can prepare mitigation strategies beforehand, reducing the need for complex real-time feedback mechanisms.
2Reliability
If AI/ML-based predictive beam management is deployed, then beam failure reduction is improved, but computational resources and processing complexity increase
Solution Approach 1:
The patent applies AI/ML models selectively at different network nodes based on their specific functions and capabilities. Rather than uniformly deploying complex computational models throughout the entire network, the system implements predictive beam management only where needed, optimizing the balance between reliability improvement and computational resource consumption.
Solution Approach 2:
The system uses measurement information from sidelink channels as feedback to train and refine AI/ML models for beam blockage prediction. This feedback loop allows the models to continuously improve their accuracy based on actual network conditions, reducing the computational complexity required for initial predictions while maintaining high reliability.
3Measurement precision
If measurement information is shared via sidelink channels, then beam blockage prediction accuracy is improved, but channel interference and signal degradation may occur
Solution Approach 1:
The patent segments the communication system into different functional channels: sidelink channels for measurement information exchange and traditional uplink/downlink channels for actual data transmission. By separating these functions spatially and functionally, the system prevents interference between measurement signaling and data traffic, ensuring accurate blockage detection without degrading service quality.
Data Source
AI summary
This disclosure provides systems, methods, and devices for wireless communication that support sidelink assisted beam blockage prediction operations. In a first aspect, an apparatus includes at least one processor and a memory coupled to the at least one processor. The at least one processor is configured to obtain measurement information associated with at least one downlink serving cell; and transmit beam blockage prediction information to a second network node, wherein the beam blockage prediction information is based on the measurement information, and wherein the beam blockage prediction information is indicative of at least one predicted beam blockage associated with the at least one downlink serving cell. Other aspects and features are also claimed and described.