arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2011.08465eess.SPcs.CVcs.LG
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利用大型智能表面评估无线传感潜力

Assessing Wireless Sensing Potential with Large Intelligent Surfaces

Aalborg University(奥尔堡大学);Norwegian University of Science and Technology(挪威科技大学)

Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski

摘要:

感知能力是未来6G无线网络最突出的新特性之一。本文讨论了大型智能表面(LIS)在示例性工业4.0场景中的传感潜力。除了LIS在通信方面受到的关注外,它还可以提供传播环境的高分辨率渲染。这是因为,在室内环境中,它可以放置在感测现象附近,而高分辨率是由部署在大面积上的密集间隔的微小天线提供的。通过将LIS视为依赖于接收信号功率的环境的无线电图像,我们开发了通过利用图像处理和机器学习的工具来感测环境的技术。一旦获得全息图像,就可以使用去噪自动编码器(DAE)网络来构建超分辨率图像,从而获得传统传感系统中不可用的传感优势。此外,我们推导出一个基于广义似然比(GLRT)的统计测试,作为机器学习解决方案的基准。我们测试这些方法的情况下,我们需要检测工业机器人是否偏离预定义的路线。结果表明,基于LIS的传感器具有较高的精度,在室内工业环境中具有很大的应用潜力。

英文摘要:

Sensing capability is one of the most highlighted new feature of future 6G wireless networks. This paper addresses the sensing potential of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the attention received by LIS in terms of communication aspects, it can offer a high-resolution rendering of the propagation environment. This is because, in an indoor setting, it can be placed in proximity to the sensed phenomena, while the high resolution is offered by densely spaced tiny antennas deployed over a large area. By treating an LIS as a radio image of the environment relying on the received signal power, we develop techniques to sense the environment, by leveraging the tools of image processing and machine learning. Once a holographic image is obtained, a Denoising Autoencoder (DAE) network can be used for constructing a super-resolution image leading to sensing advantages not available in traditional sensing systems. Also, we derive a statistical test based on the Generalized Likelihood Ratio (GLRT) as a benchmark for the machine learning solution. We test these methods for a scenario where we need to detect whether an industrial robot deviates from a predefined route. The results show that the LIS-based sensing offers high precision and has a high application potential in indoor industrial environments.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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