A Computer Vision Aided Beamforming Scheme with EM Exposure Control in Outdoor LOS Scenarios

TL;DR

This paper introduces a computer vision-based beamforming scheme for outdoor mmWave communications that actively avoids electromagnetic exposure to humans by adjusting transmission beams, balancing safety and communication quality.

Contribution

It presents a novel exposure avoidance method using pose detection and finer beam management for electromagnetic safety in outdoor LOS scenarios.

Findings

Finer beam granularity improves exposure reduction.

Simulation results show maintained communication quality.

The method effectively avoids vulnerable human body parts.

Abstract

Without any radiation control measures, a large-scale mmWave antenna array at close range may lead to a large amount of electromagnetic exposure of human. In this paper, with the aid of pose detection in computer vision, a beamforming scheme using a novel exposure avoidance method is proposed in outdoor line of sight scenarios. Instead of reducing transmitted power, the proposed method can protect the vulnerable parts of human body from electromagnetic exposure during transmission by deviating the transmission beams from vulnerable parts. Besides, a finer beam management granularity is adopted to better balance the trade-off between exposure reduction and communication quality loss, because finer beams can provide more adjustability for finding the beam that reduces exposure without excessively reducing the link quality. The proposed exposure avoidance method is validated in simulations, and the results show that the finer beam management granularity can guarantee communication quality while reducing the electromagnetic exposure.