Prof. Pathak is awarded the National Science Foundation Early Career Research Award. The title of his project is CAREER: Unifying Millimeter-wave Networking and Sensing using Commodity Backscatter.
Abstract of his project:
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: (1) Robust backscatter communication techniques will be developed where mmID tags can exploit the existing mmWave networking protocol messages to modulate their data; (2) Densely deployed mmWave backscatters will be leveraged for proactive blockage mitigation and mobility resilience in WLANs; (3) A high-speed commodity mmWave backscatter will be devised through symbol translation techniques and self-interference mitigation; (4) 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.
More information here: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2045885&HistoricalAwards=false
List of all Career Awardees at CS@GMU: https://cs.gmu.edu/about/faculty-awards/