This study demonstrates the feasibility of point cloud-based proactive link quality prediction for millimeter-wave (mmWave) communications. Previous studies have proposed machine learning-based methods to predict received signal strength for future time periods using time series of depth images to mitigate the line-of-sight (LOS) path blockage by pedestrians in mmWave communication. However, these image-based methods have limited applicability due to privacy concerns as camera images may contain sensitive information. This study proposes a point cloud-based method for mmWave link quality prediction and demonstrates its feasibility through experiments. Point clouds represent three-dimensional (3D) spaces as a set of points and are sparser and less likely to contain sensitive information than camera images. Additionally, point clouds provide 3D position and motion information, which is necessary for understanding the radio propagation environment involving pedestrians. This study designs the mmWave link quality prediction method and conducts realistic indoor experiments, where the link quality fluctuates significantly due to human blockage, using commercially available IEEE 802.11ad-based 60 GHz wireless LAN devices and Kinect v2 RGB-D camera and Velodyne VLP-16 light detection and ranging (LiDAR) for point cloud acquisition. The experimental results showed that our proposed method can predict future large attenuation of mmWave received signal strength and throughput induced by the LOS path blockage by pedestrians with comparable or superior accuracy to image-based prediction methods. Hence, our point cloud-based method can serve as a viable alternative to image-based methods.

翻译：本研究证明了基于点云的毫米波通信链路质量主动预测的可行性。先前的研究提出了基于机器学习的方法，利用深度图像的时间序列预测未来时段的接收信号强度，以减轻行人造成的视距路径遮挡对毫米波通信的影响。然而，这些基于图像的方法因相机图像可能包含敏感信息而存在隐私问题，导致其适用性有限。本研究提出了一种基于点云的毫米波链路质量预测方法，并通过实验验证了其可行性。点云将三维空间表示为点的集合，相较于相机图像更为稀疏且不易包含敏感信息。此外，点云提供了三维位置和运动信息，这对于理解涉及行人的无线电传播环境至关重要。本研究设计了毫米波链路质量预测方法，并使用基于IEEE 802.11ad标准的商用60 GHz无线局域网设备、Kinect v2 RGB-D相机及Velodyne VLP-16激光雷达进行点云采集，在室内真实场景下开展了实验，其中链路质量因人体遮挡而显著波动。实验结果表明，所提方法能够预测因行人视距遮挡导致的毫米波接收信号强度与吞吐量未来大幅衰减，其预测精度与基于图像的方法相当或更优。因此，本文提出的基于点云的方法可作为基于图像方法的可行替代方案。