The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.
WiFi Sensing with Channel State Information: A Survey
Abstract
With the high demand for wireless data traffic, WiFi networks have experienced very rapid growth, because they provide high throughput and are easy to deploy. Recently, Channel State Information (CSI) measured by WiFi networks is widely used for different sensing purposes. To get a better understanding of existing WiFi sensing technologies and future WiFi sensing trends, this survey gives a comprehensive review of the signal processing techniques, algorithms, applications, and performance results of WiFi sensing with CSI. Different WiFi sensing algorithms and signal processing techniques have their own advantages and limitations and are suitable for different WiFi sensing applications. The survey groups CSI-based WiFi sensing applications into three categories, detection, recognition, and estimation, depending on whether the outputs are binary/multi-class classifications or numerical values. With the development and deployment of new WiFi technologies, there will be more WiFi sensing opportunities wherein the targets may go beyond from humans to environments, animals, and objects. The survey highlights three challenges for WiFi sensing: robustness and generalization, privacy and security, and coexistence of WiFi sensing and networking. Finally, the survey presents three future WiFi sensing trends, i.e., integrating cross-layer network information, multi-device cooperation, and fusion of different sensors, for enhancing existing WiFi sensing capabilities and enabling new WiFi sensing opportunities.
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Cites
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From RSSI to CSI: Indoor localization via channel response
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SpotFi: Decimeter Level Localization Using WiFi
Kotaru, M., Joshi, K., Bharadia, D., & Katti, S. (2015) · Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication · doi:10.1145/2785956.2787487 · Cited by 1,169
Understanding and Modeling of WiFi Signal Based Human Activity Recognition
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Cited by
Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond
Liu, F., Cui, Y., Masouros, C., Xu, J., Han, T. X., Eldar, Y. C., & Buzzi, S. (2022) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2022.3156632 · Cited by 3,857
A Survey on Human Behavior Recognition Using Channel State Information
Wang, Z., Jiang, K., Hou, Y., Dou, W., Zhang, C., Huang, Z., & Guo, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2949123 · Cited by 149
Wi-CaL: WiFi Sensing and Machine Learning Based Device-Free Crowd Counting and Localization
Choi, H., Fujimoto, M., Matsui, T., Misaki, S., & Yasumoto, K. (2022) · IEEE Access · doi:10.1109/access.2022.3155812 · Cited by 100
Metadata
- Authors
- Ma, Y., Zhou, G., & Wang, S.
- Venue
- ACM Computing Surveys
- Published
- 2019-06-18
- Volume
- 52
- Issue
- 3
- Pages
- 1-36
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2952065976
- Cited by
- 869
- References
- 135
- FWCI
- 25.47
- Type
- journal article
- Language
- en
- Open access
- closed
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