Sensing-Assisted Beam Management for Faster 5G NR Beam Tracking
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Solution Overview
Problem
Current 5G NR beam management techniques face challenges in accelerating beam training and tracking, saving RS overhead, and maintaining link robustness due to the increase in candidate beams and narrower beam widths, which degrades spatial diversity and increases RS overhead.
Innovation Solution
The proposed solution involves using sensing information to assist beam management by defining virtual anchors and associating sensing information with beam measurement and reporting, enabling advanced notifications of predicted QoS changes and reducing RS overhead through efficient beam alignment and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beam width is narrowed to increase the number of candidate beams, then beam management precision is improved, but spatial diversity is degraded and RS overhead increases
Solution Approach 1:
The patent applies preliminary action by using sensing information (such as location, speed, and trajectory data) to predict future beam requirements before actual communication occurs. This allows the system to pre-configure beam directions and adjust beamwidth proactively, maintaining spatial diversity while achieving precise beam management without requiring excessive reference signals.
Solution Approach 2:
The patent dynamically changes beam parameters (beamwidth and direction) based on sensed environmental information and predicted QoS requirements. By adjusting these parameters adaptively rather than using fixed narrow beams, the system maintains both precision and spatial diversity, resolving the contradiction between the two objectives.
2Measurement precision
If beam width is narrowed to increase the number of candidate beams, then beam training accuracy is improved, but RS overhead increases
Solution Approach 1:
The system performs preliminary beam configuration using sensing data before actual beam training occurs. By predicting which beams will be needed based on sensed information, the system reduces the number of reference signals required during actual training, achieving high accuracy with lower overhead.
Solution Approach 2:
The system uses sensing information (location, speed, trajectory) to self-determine appropriate beam configurations without requiring extensive reference signal probing. This self-service approach allows the device to autonomously select promising beam directions based on environmental context, reducing RS overhead while maintaining training accuracy.
3Productivity
If beam training and tracking are accelerated, then communication speed is improved, but beam management complexity increases
Solution Approach 1:
The patent replaces traditional mechanical beam sweeping and probing methods with sensing-based prediction. Instead of systematically testing each beam direction with reference signals, the system uses sensing information to directly predict optimal beam configurations, dramatically accelerating beam training while reducing computational complexity through physics-based inference rather than exhaustive search.
Data Source
AI summary
Presented are systems, methods, apparatuses, or computer-readable media for performing sensing information assisted beam management. A wireless communication device may receive, from a wireless communication node, a first signaling that includes a transmission parameter setting. The wireless communication device may associate the transmission parameter setting and resource related information. The wireless communication device may communicate with the wireless communication node, a signal according to the resource related information.