A Survey of mmWave Backscatter: Applications, Platforms, and Technologies

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2025-03-12 DOI:10.1145/3723004

Yimiao Sun, Yuan He, Yang Zou, Jiaming Gu, Xiaolei Yang, Jia Zhang, Ziheng Mao

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引用次数: 0

Abstract

As a key enabling technology of the Internet of Things (IoT) and 5G communication networks, millimeter wave (mmWave) backscatter has undergone noteworthy advancements and brought significant improvement to prevailing sensing and communication systems. Past few years have witnessed growing efforts in innovating mmWave backscatter transmitters ( e.g., tags and metasurfaces) and the corresponding techniques, which provide efficient information embedding and fine-grained signal manipulation for mmWave backscatter technologies. These efforts have greatly enabled a variety of appealing applications, such as long-range localization, roadside-to-vehicle communication, coverage optimization and large-scale identification. In this paper, we carry out a comprehensive survey to systematically summarize the works related to the topic of mmWave backscatter. Firstly, we introduce the scope of this survey and provide a taxonomy to distinguish two categories of mmWave backscatter research based on the operating principle of the backscatter transmitter: modulation-based and relay-based. Furthermore, existing works in each category are grouped and introduced in detail, with their common applications, platforms and technologies, respectively. Finally, we elaborate on potential directions and discuss related surveys in this area.

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毫米波反向散射研究：应用、平台和技术

作为物联网（IoT）和5G通信网络的关键使能技术，毫米波（mmWave）背散射技术取得了令人瞩目的进步，对现有的传感和通信系统带来了重大改进。过去几年，人们在毫米波反向散射发射机（如标签和元表面）及其相应技术的创新方面付出了越来越多的努力，这些技术为毫米波反向散射技术提供了有效的信息嵌入和细粒度信号处理。这些努力极大地实现了各种有吸引力的应用，如远程定位，路边到车辆通信，覆盖优化和大规模识别。在本文中，我们进行了全面的调查，系统地总结了与毫米波反向散射主题相关的工作。首先，我们介绍了本研究的范围，并根据后向散射发射机的工作原理对两类毫米波后向散射研究进行了分类：基于调制和基于中继。此外，对每个类别的现有作品进行了详细的分组和介绍，分别介绍了它们的常见应用、平台和技术。最后，阐述了该领域的发展方向，并对相关研究进行了讨论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.