Camera-Based Beam Alignment for Millimeter Wave Networks
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Solution Overview
Problem
Next-generation wireless networks face challenges in quick link discovery and link adaptation due to increased susceptibility to interference from link obstructions and environmental conditions, particularly with high-frequency millimeter wave signals requiring directional beamforming, which complicates initial cell search and signal alignment.
Innovation Solution
The use of camera sensors to provide visual information for assigning scheduling and transmission parameters, predicting link obstructions, and managing backhaul links by modifying signal transmission angles to compensate for movement, thereby enhancing beam alignment and link quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If high-frequency millimeter wave signals are used to achieve suitable signal range, then signal transmission capability is improved, but susceptibility to link obstructions increases
Solution Approach 1:
The system performs visual discovery and spatial localization of user equipment before initiating millimeter wave link establishment. Camera sensors capture images to determine UE position and characteristics in advance, allowing the system to pre-select optimal beam directions and anticipate potential obstructions before the actual signal transmission begins, thereby reducing susceptibility to link obstructions.
Solution Approach 2:
Visual information from camera sensors serves as an intermediary between the millimeter wave communication system and the physical environment. This visual data provides spatial context about user equipment location, movement, and surrounding obstacles, enabling the system to adapt beamforming parameters and transmission strategies to avoid obstructions while maintaining high-frequency signal transmission capability.
2Power
If highly directional beamforming is implemented to improve spatial selectivity, then signal range is improved, but complexity of link discovery increases
Solution Approach 1:
The patent replaces the traditional mechanical/electronic beam sweeping process with visual information-based spatial localization. Instead of systematically scanning through all possible beam directions using complex electronic search procedures, the system uses camera sensors to directly determine user equipment position and orientation, substituting a simpler visual detection mechanism for the complex beamforming search process.
Solution Approach 2:
Visual discovery is performed as a preliminary action before beamforming link discovery. By capturing images and determining spatial characteristics of user equipment in advance, the system eliminates the need for exhaustive angular searching during link discovery, significantly reducing the complexity while maintaining the directional beamforming capability for signal transmission.
3Reliability
If joint search over angular directional space is performed to locate suitable antenna configuration, then link quality is improved, but time required for cell search increases
Solution Approach 1:
Visual information acts as an intermediary that directly provides spatial localization data about user equipment. This visual data includes position, orientation, and movement information that can be directly translated into optimal beamforming parameters, eliminating the need for time-consuming joint searches over angular directional spaces while ensuring high link quality through accurate spatial targeting.
Solution Approach 2:
The system creates a visual copy or representation of the physical environment and user equipment positions through camera imaging. This visual model serves as a substitute for performing actual angular searches through the entire directional space, allowing the system to quickly determine optimal transmission parameters by processing image data rather than exhaustively searching all possible beam angles.
Data Source
AI summary
Visual information from camera sensors can be used to assign scheduling and/or transmission parameters in a wireless network. For example, the visual information can be used to visually discover a user equipment (UE) prior to initiating link discovery. This may be accomplished by analyzing the visual information to identify an absolute or relative position of the UE. The positioned may then be used to select antenna configuration parameters for transmitting a discovery signal, e.g., direction of departure (DoD), angle of departure (AoD), precoder. As another example, the visual information is used to predict a link obstruction over a radio interface between a UE and an AP. In yet other examples, the visual information may be used for traffic engineering purposes, such as to predict a traffic density or pair UEs with APs.