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:
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.
Parth Pathak
Associate Professor CS@GMU
NSDI '24 |
mmComb: High-speed mmWave CommodityWiFi Backscatter Yoon Chae, Zhenzhe Lin, Kang Min Bae, Song Min Kim, and Parth Pathak |
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Sigmetrics '23 |
CoBF: Coordinated Beamforming in Dense mmWave Networks Ding Zhang, Panneer Selvam Santhalingam, Parth Pathak, and Zizhan Zheng |
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SenSys '22 |
M5: Facilitating Multi-user Volumetric Content Delivery with Multi-lobe Multicast over mmWave Ding Zhang, Puqi Zhou, Bo Han and Parth Pathak |
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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 |
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HotMobile '22 |
Networked Beamforming in Dense mmWave WLANs Ding Zhang, Panneer Selvam Santhalingam, Parth Pathak and Zizhan Zheng |
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Infocom '22 |
MILLIEAR: Millimeter-wave Acoustic Eavesdropping with Unconstrained Vocabulary Pengfei Hu, Yifan Ma, Panneer Selvam Santhalingam, Parth Pathak, and Xiuzhen Cheng |
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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 |
The project is funded by National Science Foundation (NSF) NeTS grant award (CNS-2045885).