Sensing System Beam Management for mmWave Mobility
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Solution Overview
Problem
Beam management in mmWave wireless communications is challenging due to the narrow beam angle and poor penetration and diffraction abilities, leading to frequent beam adjustments and resource consumption, especially with device mobility, which affects system throughput and capacity.
Innovation Solution
A sensing system is integrated with the wireless communication system to determine 3D positions and velocities of devices and obstacles in real-time, using machine learning to predict signal-related information and aid beam adjustment, reducing the need for frequent beam recovery and improving resource management efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beamforming is used to concentrate energy on the main lobe to direct radio beam towards target receiver, then receiving sensitivity is improved, but beam management becomes sensitive to device mobility and requires frequent adjustments
Solution Approach 1:
The system performs preliminary beam alignment using positioning information from sensors (GPS, compass, accelerometer) before actual data transmission begins. This preliminary positioning allows the beamforming parameters to be pre-configured based on predicted device locations, reducing the need for frequent beam adjustments during mobility.
Solution Approach 2:
The system continuously monitors device position through sensor feedback and uses this information to dynamically adjust beamforming parameters. The positioning system provides real-time feedback on device location and orientation, enabling the base station to track moving devices and maintain optimal beam alignment without frequent reconfiguration.
2Productivity
If narrow beam angle is used to concentrate radio energy, then transmission efficiency is improved, but penetration and diffraction abilities deteriorate
Solution Approach 1:
The system dynamically changes beamforming parameters including beam width, direction, and power distribution based on real-time positioning information. When obstacles are detected or signal quality degrades, the system adjusts parameters to improve penetration and diffraction while maintaining acceptable transmission efficiency.
Solution Approach 2:
The beamforming system transitions from static narrow beams to dynamic adaptive beams that can change width and direction in response to mobility and environmental conditions. This allows the system to maintain narrow beams for efficiency when conditions permit, while expanding beam width for better penetration when needed.
3Reliability
If frequent beam adjustments are made to track mobile devices, then connection stability is improved, but controlling and scheduling overhead increases
Solution Approach 1:
The system uses positioning information to predict future device locations and pre-adjusts beam directions before devices actually move to new positions. This predictive approach reduces the frequency of reactive beam adjustments and minimizes control overhead while maintaining connection stability.
Solution Approach 2:
The system creates virtual beam copies or alternative beam paths based on positioning information, allowing it to prepare backup beam configurations in advance. This reduces the need for frequent switching and reconfiguration when devices move, as pre-computed alternative beams are already available.
Data Source
AI summary
Methods and systems are described which use a sensing system in cooperation with a wireless communication system. Coordinate information (which may be from the sensing system, from an electronic device, or from a network-side device) and signal-related information (which may be from the wireless system) are associated with each other. The associated information may be used for wireless communication management, such as beam management operations, among others.