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LTE-based Pervasive Sensing Across Indoor and Outdoor

27 Jun
Thursday, 06/27/2024 9:30am to 11:25am
Zoom
PhD Thesis Defense
Speaker: Yuda Feng

Besides the communication function, wireless signals, such as WiFi, Bluetooth and UWB, are recently exploited for sensing purposes. However, designing a wireless sensing system that provides truly pervasive coverage at city or even national scale is still challenging. In this dissertation, we propose to involve the pervasive LTE signals into the ecosystem of wireless sensing, and enable various sensing applications on human, vehicles, and agriculture.   

In the first part of the dissertation, we exploit the unique advantages of downlink LTE sensing and resolve its unique challenges. Downlink LTE signals from the base station manifest unique features of pervasive coverage, extensive frequency and spatial diversity, and everlasting high-rate uniform frames, which facilitates LTE sensing. On the other hand, due to the long distance between LTE base stations and user devices, LTE signal interacts with diverse objects during the propagation process which causes severe interference in sensing. We design delicate signal processing schemes to combat severe interference. We demonstrate the advantages of LTE sensing using two typical applications, indoor respiration sensing and outdoor traffic monitoring. The proposed system achieves highly accurate respiration sensing with the blind spot and orientation-sensitive issues greatly mitigated. And the error of car speed estimation is lower than 2 mph, as good as commercial devices on the market.  

In the second part, we further extend the applicability of LTE sensing to agriculture. Soil moisture sensing is a basic function in modern precision irrigation. Multiple wireless soil moisture sensing solutions such as WiFi and RFID have been proposed, which, however, can hardly support large scale deployment in farmfield environments. LTE signal provides a unique opportunity for soil moisture sensing as the ubiquitously deployed base stations. We for the first time propose low-cost and low-power LTE based soil moisture sensing. Our low-cost sensing system ($55) achieves a high accuracy (3.15%) comparable to high-end soil sensors ($850), wide coverage (2.4 km from the base station) and low power consumption (lasting 16 months using batteries).

In the last part of the dissertation, we propose to combat the inherent limitations of downlink LTE sensing, i.e., the low signal quality in comparison to other wireless technologies (10 dB lower than WiFi) and significant variations across different areas. To boost LTE sensing potential, we found the key insight in the unique asymmetric downlink and uplink transmissions. Accordingly, we propose to leverage the complementary features of LTE uplink and downlink signals on signal power, bandwidth and sensing rate. We propose noise-resistant combination algorithms and develop robust LTE sensing.

Advisors: Jie Xiong and Deepak Ganesan

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