Base Station Beam Management Using Sensor Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless communication systems, particularly in millimeter wave spectrum, face challenges in maintaining link quality due to environmental changes such as shadowing and blocking of beams, which affects mobile and static UEs, leading to dropped calls and lost data packets.
Innovation Solution
A method where base stations use sensor data like camera, radar, or lidar data to model the cell environment and combine it with beam management reporting history to determine optimal beams for communication with UEs, allowing for proactive beam switching and reduced reliance on UE reports, thereby improving link quality and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of moving object
If narrow directional beams are used in millimeter wave spectrum, then beam directionality and signal focus are improved, but beam reliability deteriorates due to environmental shadowing and blocking
Solution Approach 1:
The system performs preliminary actions by obtaining sensor data about the cell environment and proactively determining beam associations with UE locations before actual communication occurs. This allows the base station to predict and prepare for potential beam blocking scenarios, switching to alternative beams before link failure happens, thus maintaining reliability while using directional beams.
Solution Approach 2:
Sensor data acts as an intermediary between the physical environment and beam selection decisions. The sensor data provides information about objects that may block beams, allowing the system to indirectly assess beam reliability without direct trial-and-error testing, thus resolving the contradiction between directionality and reliability.
2Measurement precision
If beam management relies on UE reports, then beam selection accuracy is improved, but system complexity and processing overhead increase
Solution Approach 1:
The base station performs self-service by using its own sensor data to determine beam associations with UE locations, reducing reliance on UE reports. The system serves itself by independently assessing environmental conditions and making informed beam selection decisions, thereby reducing processing overhead while maintaining accuracy.
Solution Approach 2:
The system uses partial action by selectively using sensor data for beam association determination rather than relying solely on comprehensive UE reports. This partial approach to information gathering reduces processing complexity while maintaining sufficient beam selection accuracy for practical operation.
3Measurement precision
If sensor data is obtained and processed, then beam selection accuracy is improved, but base station power consumption and processing load increase
Solution Approach 1:
Sensor data is obtained and processed in advance to build beam location associations before they are needed for communication. This preliminary processing allows the base station to cache and reuse this information, reducing the need for continuous real-time sensor processing and thereby reducing ongoing power consumption while maintaining accurate beam selection.
Data Source
AI summary
The present disclosure involves determining base station (BS) beams for communicating between a UE and the BS. The BS may use sensor data or beam management reporting history to assist with determining one or more appropriate beams. The sensor data may include camera images, radar data, or lidar data, and be used to model the cell environment served by the BS. The BS may obtain reporting data from multiple UEs over time indicating the quality of beams received by the UEs at various locations in the cell environment and model the cell environment based on the reporting data. The BS may associate beams with possible UE locations within the cell environment and use the associations to determine beams for communicating with a UE after determining the UE's location.