Sensor-Assisted Beamforming for Precise mmWave User Tracking
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Solution Overview
Problem
Existing wireless communication systems face challenges such as signal attenuation, especially in mmWave communication, leading to increased complexity and latency, and issues with Quality of Experience (QoE) due to coarse positioning methods and infrastructure costs.
Innovation Solution
An edge device with integrated sensors for precise tracking and beamforming, enabling centimeter-level accuracy in locating users, dynamically adjusting beam direction and shape to maintain high-performance and reliable communication without increasing signaling load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mmWave beamforming is used to enhance capacity and reduce latency, then communication performance is improved, but signal attenuation due to atmospheric conditions and obstructions worsens
Solution Approach 1:
The system performs preliminary positioning of the UE using coarse positioning methods to obtain initial location information before beamforming. This preliminary action allows the base station to pre-align beams toward the expected UE location, reducing the time and signaling required for beam acquisition and maintaining reliable connection despite signal attenuation challenges
Solution Approach 2:
The patent replaces traditional mechanical beam steering or wide-beam scanning mechanisms with a sensor-assisted beamforming system. Sensors (cameras, LIDAR, radar) detect UE position and motion, and this information directly controls phase shifters to electronically steer beams, eliminating the need for mechanical movement or exhaustive beam searching
2Measurement precision
If conventional positioning methods are used to determine UE location, then positioning information is obtained, but positioning accuracy is coarse (3-10 meters error) and signaling load increases
Solution Approach 1:
The system merges multiple positioning technologies (coarse positioning from network, sensor-based detection from base station, and potentially UE-side sensors) into a unified positioning framework. This combination achieves high accuracy (centimeter-level) by fusing data sources, reducing reliance on any single method and minimizing the signaling overhead required for position exchange
Solution Approach 2:
The base station acts as an intermediary that receives coarse positioning information, enhances it using its own sensors (cameras, LIDAR, radar) to track UE, and provides the refined position information to the beamforming system. This intermediary role eliminates the need for frequent high-accuracy positioning signaling between UE and network, as the base station independently refines position using local sensor data
3Reliability
If wide beam access is used to ensure coverage near repeater devices, then connectivity is maintained in proximity, but performance degrades as UE moves to greater distances due to signal attenuation
Solution Approach 1:
The system dynamically adjusts beam characteristics (direction, width, power) based on real-time UE position and distance. Near the repeater, wide beams ensure coverage; as UE moves farther, the system switches to narrow, high-gain beams focused on the distant UE. This dynamic adaptation maintains both connectivity and high performance across varying distances, overcoming the limitation of fixed wide-beam approaches
Solution Approach 2:
Different beam qualities are applied to different spatial regions: wide, lower-gain beams are used for near-field coverage around the repeater, while narrow, high-gain beams are directed toward distant UEs. This local quality differentiation ensures optimal performance for each spatial zone, addressing the distance-dependent performance degradation
Data Source
AI summary
An edge device includes an antenna array and a sensor that senses a surrounding area of the edge device. The edge device further includes control circuitry that detects a user in the surrounding area of the edge device, tracks the detected first user in the surrounding area of the edge device, and controls the first antenna array to direct, concurrently with the sensing of the surrounding area, a first beam of radio-frequency (RF) signal in a second frequency band in a first direction of the tracked first user, where the first frequency band is different from the second frequency band.