CAREER: Unifying Millimeter-wave Networking and Sensing using Commodity Backscatter

Internet-of-Things (IoT) devices are being integrated into virtually every aspect of our daily lives with applications in logistics, supply chain, healthcare, smart cities, human-computer interaction, tracking, sensing, etc. However, providing high-speed wireless connectivity to these IoT devices remains a challenging open problem. While very high-speed wireless networks such as the next generation 802.11ad/ay WiFi and 5G cellular networks are being deployed using the high-frequency millimeter-wave (mmWave) spectrum, today’s IoT devices (such as Bluetooth and RFIDs) still primarily operate at lower frequencies (sub-6 GHz) due to their low power requirements. The aim of this project is to develop methods and tools for commodity mmWave backscattering and enable IoT devices to operate at mmWave frequencies. The proposed mmWave backscattering will enable high-speed, low-power, and low-cost mmWave wireless connectivity to millions of IoT devices.

The project will investigate commodity mmWave backscatter (called mmIDs) and realize a unified mmWave networking and sensing framework where (i) the mmID devices can be integrated into today’s mmWave networks for their seamless high-speed connectivity and (ii) robustness of the mmWave networks can be improved through the presence of densely deployed mmID IoT devices. The project includes four research thrusts:

  • Robust backscatter communication techniques will be developed where mmID tags can exploit the existing mmWave networking protocol messages to modulate their data;
  • Densely deployed mmWave backscatters will be leveraged for proactive blockage mitigation and mobility resilience in WLANs;
  • A high-speed commodity mmWave backscatter will be devised through symbol translation techniques and self-interference mitigation;
  • The commodity mmWave backscatter will be exploited to enable high-accuracy and low-cost sensing with applications in accessibility.

The proposed techniques and protocols for mmWave backscattering will be designed, implemented, and evaluated for emerging commodity mmWave networks such as 802.11ad/ay WLANs and 5G NR. The project presents integrated research and education plan with outreach activities involving high school students from underrepresented minority groups and undergraduate students with disabilities.

Students

Yoon Chae
Ph.D. candidate

Zhenzhe Lin
Ph.D. student

Mingyo Jeong
Ph.D. student

Faculty

Parth Pathak
Associate Professor CS@GMU

Publications
NSDI '24
mmComb: High-speed mmWave CommodityWiFi Backscatter
Yoon Chae, Zhenzhe Lin, Kang Min Bae, Song Min Kim, and Parth Pathak
USENIX Symposium on Networked Systems Design and Implementation (NSDI) 2024
Sigmetrics '23
CoBF: Coordinated Beamforming in Dense mmWave Networks
Ding Zhang, Panneer Selvam Santhalingam, Parth Pathak, and Zizhan Zheng
ACM Conference on Measurement and Modeling of Computer Systems (Sigmetrics) 2023
SenSys '22
M5: Facilitating Multi-user Volumetric Content Delivery with Multi-lobe Multicast over mmWave
Ding Zhang, Puqi Zhou, Bo Han and Parth Pathak
ACM Conference on Embedded Networked Sensor Systems (SenSys) 2022
MobiSys '22
Best Paper Award
OmniScatter: Extreme Sensitivity mmWave Backscattering using Commodity FMCW Radar
Kang Min Bae, Namjo Ahn, Yoon Chae, Parth Pathak, Sung-Min Sohn and Song Min Kim
ACM Conference on Mobile Systems, Applications and Services (MobiSys) 2022
HotMobile '22
Networked Beamforming in Dense mmWave WLANs
Ding Zhang, Panneer Selvam Santhalingam, Parth Pathak and Zizhan Zheng
ACM Workshop on Mobile Computing Systems and Applications (HotMobile) 2022
Infocom '22
MILLIEAR: Millimeter-wave Acoustic Eavesdropping with Unconstrained Vocabulary
Pengfei Hu, Yifan Ma, Panneer Selvam Santhalingam, Parth Pathak, and Xiuzhen Cheng
IEEE International Conference on Computer Communications (Infocom) 2022
WinTech '20
On the Feasibility of Millimeter-wave Backscatter using Commodity 802.11ad 60 GHz Radios
Yoon Chae, Kang Min Bae, Parth Pathak, and Song Min Kim
ACM Workshop on Wireless Network Testbeds, Experimental evaluation & Characterization (WinTech @MobiCom) 2020.
Project Support

The project is funded by National Science Foundation (NSF) NeTS grant award (CNS-2045885).