Multi-Sensor Beam Control for Blockage-Aware mmWave Links
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Millimeter-wave and terahertz-wave wireless communication systems face challenges due to high propagation loss, diffraction, and penetration issues, leading to communication failures when obstacles block radio waves, and existing beamforming methods struggle to accurately adapt to changing environments.
Innovation Solution
A beam control method using a multi-sensor system, including a beam sweeping unit, divided region-specifying unit, information acquisition unit, and data transmitter, to identify target terminals and adjust beamforming based on sensor data from RGB-D cameras, LiDAR, and ultrasonic sensors, enabling precise beam control and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If beamforming concentrates all transmission power in the direction of the straight wave, then propagation loss is compensated, but communication failure occurs when obstacles block the radio wave path
Solution Approach 1:
The system performs preliminary actions by continuously monitoring the communication environment using sensors (camera, LiDAR, ultrasonic sensor) to detect obstacles before they block the radio wave path. When an obstacle is detected in advance, the system proactively switches to a relay base station or adjusts the beam direction, preventing communication failure before it occurs. This preliminary detection and preparation resolves the contradiction by maintaining reliability while still concentrating power in the LOS direction during normal operation.
2Loss of information
If continuous signal exchange is used to estimate distance and angle between base stations and terminals, then environment information is detected, but implementation becomes very difficult in future communication systems
Solution Approach 1:
The patent introduces sensors (camera, LiDAR, ultrasonic sensor) as intermediary devices that directly measure environmental information such as distance, angle, and obstacle locations. These sensors act as mediators between the communication system and the physical environment, providing accurate spatial information without requiring complex continuous signal exchange between base stations and terminals. This approach significantly reduces implementation complexity while maintaining accurate environment detection capability.
3Loss of energy
If beamforming concentrates power on the line of sight wave, then propagation loss is compensated, but the system cannot adapt when the straight wave path is blocked
Solution Approach 1:
The system implements continuous feedback by using sensors to monitor the communication environment in real-time. The sensor data (image information from camera, distance from LiDAR, obstacle detection from ultrasonic sensor) provides feedback about the current propagation conditions. Based on this feedback, the system dynamically adapts by switching to relay base stations or adjusting beam directions when obstacles are detected, while maintaining concentrated power transmission in the LOS direction when the path is clear. This feedback mechanism resolves the contradiction between power concentration and environmental adaptability.
Data Source
AI summary
A beam control method using a multi-sensor in a millimeter-wave and terahertz-wave wireless communication system comprises the steps of: diving a beamforming region and performing beam sweeping by a base station; specifying, through beam sweeping, a divided region in which the strength of a received signal is the strongest; obtaining image information through at least one sensor included in a wireless terminal or a base station located in the specified divided region; identifying a target terminal to be communicated, by using the obtained image information, and extracting location information of the identified target terminal; and transmitting data in a direction corresponding to the location information of the identified target terminal. Accordingly, it is possible to greatly increase the accuracy of beamforming in a wireless communication environment, and reduce power consumption, a radio resource overhead, and a delay time required for beamforming.