5G Beam Management Using RF and Motion Sensor Fusion
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Solution Overview
Problem
In 5G/NR communication systems, finding the best beam for wireless communication is inefficient due to channel changes caused by UE movement, leading to latency and reduced reception/transmission performance.
Innovation Solution
Combining reference signal measurements with sensor information, such as orientation data from motion sensors, to efficiently identify the best beam for wireless communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beam management is performed using only RF measurements, then the system complexity is low, but the precision and reliability of beam selection deteriorate in non-line-of-sight conditions
Solution Approach 1:
The patent combines RF measurements from the communication system with measurements from external sensors (GPS, compass, accelerometer, gyroscope) to create a fused measurement system. This merging allows the system to achieve high beam selection precision by cross-validating RF data with independent sensor data, particularly in non-line-of-sight conditions where RF alone is insufficient.
Solution Approach 2:
The patent introduces sensor measurements as an intermediary layer between the RF environment and beam selection decisions. The sensor data (position, orientation, motion) acts as a mediator that helps interpret RF measurements and disambiguate between different beam candidates, improving precision without directly modifying the RF propagation physics.
2Reliability
If multiple sensors are integrated for measurement fusion, then the reliability of beam management improves, but the device complexity increases
Solution Approach 1:
The patent makes the measurement fusion system multi-functional by using the same sensor suite for multiple purposes: beam selection, beam refinement, mobility detection, and environment characterization. This universality allows a single integrated system to perform multiple beam management tasks, improving reliability across different scenarios without proportionally increasing complexity.
Solution Approach 2:
The patent implements feedback mechanisms where sensor measurements continuously inform beam selection and refinement decisions. The system uses accelerometer and gyroscope data to detect mobility states and adjust beam management strategies in real-time, creating a closed-loop system that maintains high reliability through continuous adaptation to changing conditions.
3Measurement precision
If sensor measurements are fused with RF measurements, then beam selection accuracy improves, but the processing complexity and time increase
Solution Approach 1:
The patent performs preliminary classification of mobility states using accelerometer and gyroscope data before executing complex beam selection algorithms. By pre-processing sensor data to identify mobility categories (stationary, pedestrian, vehicular), the system reduces the computational burden of subsequent RF-sensor fusion, maintaining high accuracy while managing processing complexity through staged processing.
Data Source
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AI summary
The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. A method for beam management by a user equipment (UE) in a wireless communication system includes determining reference signal measurements from signals received from one or more base stations. The method also includes obtaining, from a motion sensor, motion information of the UE. The method further includes generating beam management information for the beam management based on the reference signal measurements and the motion information.