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

2025-03-12

ACM Computing Surveys

AI Summary

Addressing the fragmentation and lack of a unified taxonomy in millimeter-wave (mmWave) backscatter research, this paper proposes the first binary classification framework based on transmitter operating principles—namely, *modulation-based* versus *relay-based* architectures. We systematically survey application paradigms—including long-range localization, vehicle-infrastructure cooperation, coverage enhancement, and massive tag identification—as well as hardware platforms (e.g., metasurface tags and reconfigurable intelligent surfaces, RIS) and core techniques (e.g., backscatter modulation, channel estimation, and signal detection). The study identifies cross-platform common challenges and fundamental performance bottlenecks. It further pinpoints RIS integration and integrated sensing and communication (ISAC) as critical evolutionary directions. This work provides a systematic reference for IoT–5G/6G convergence and supports the development of low-power, high-accuracy, wide-coverage wireless communication paradigms.

Technology Category

• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Search and Optimization: Metareasoning and Metaheuristics
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Web Mining and Content Analysis: Normalization, clustering, classification, and summarization of Web text

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.

Problem

• Surveying advancements in mmWave backscatter for IoT and 5G
• Classifying modulation-based and relay-based mmWave backscatter research
• Exploring applications like localization and vehicle communication

Innovation

• mmWave backscatter enables IoT and 5G networks
• Modulation-based and relay-based mmWave backscatter techniques
• Applications include localization and large-scale identification