论文标题
基于计算机的基于计算机视觉的波束形成方案，用于LOS场景中的毫米波通信
A Computer Vision Based Beamforming Scheme for Millimeter Wave Communication in LOS Scenarios
论文作者
论文摘要
提出了一种用于毫米波通信的新型位置感知的波束形成方案，以进行视线（LOS）和低移动性场景，其中引入了计算机视觉，以从与MMWave天线阵列共处捕获的相机（S）捕获的图像或视频中得出所需的位置或空间角度信息。构建了无线覆盖模型，以研究卷积神经网络（CNN）实现图像处理的定位精度的覆盖范围性能和影响。此外，视频可能是故意模糊的，甚至可以直接应用低分辨率的视频，以保护用户的隐私，以可接受的定位精度，降低计算复杂性和较低的相机成本。模拟证明了光束形成方案是可行的，并且我们采用的主流CNN在光束方向性精度的两个方面都足够，并且每秒帧的处理速度。
A novel location-aware beamforming scheme for millimeter wave communication is proposed for line of sight (LOS) and low mobility scenarios, in which computer vision is introduced to derive the required position or spatial angular information from the image or video captured by camera(s) co-located with mmWave antenna array at base stations. A wireless coverage model is built to investigate the coverage performance and influence of positioning accuracy achieved by convolutional neural network (CNN) for image processing. In addition, videos could be intentionally blurred, or even low-resolution videos could be directly applied, to protect users' privacy with acceptable positioning precision, lower computation complexity and lower camera cost. It is proved by simulations that the beamforming scheme is practicable and the mainstream CNN we employed is sufficient in both aspects of beam directivity accuracy and processing speed in frame per second.
