Leveraging Backscatter for Ultra-Low-Power Wireless Sensing Networks
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Date
2022-01-01
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Department
Computer Science and Electrical Engineering
Program
Engineering, Computer
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Distribution Rights granted to UMBC by the author.
Access limited to the UMBC community. Item may possibly be obtained via Interlibrary Loan thorugh a local library, pending author/copyright holder's permission.
Abstract
The vision of the wireless sensing networks (WSNs) is to build the connection between the digital world and the physical world so that we can monitor, control and change everything surrounding us through ubiquitous sensing and interconnected network. One critical challenge toward this vision is to power multitudinous wireless sensors, allowing long-term network operations without charging or replacing batteries. The backscatter technology is a promising but challenging solution that performs wireless communication by reflecting ambient radio frequency (RF) signals. Since reflecting RF signals only consumes microwatt-level energy, a wireless sensor can replace the battery with an RF energy harvester to run WSNs applications with ultra-low power consumption. Therefore, researchers propose various backscatter technologies to build ultra-low-power WSNs. However, integrating the backscatter technology into the existing WSNs is fraught with challenges. First, the existing backscatter systems simply reflect the ambient RF signals and do not take advantage of the signals' advanced features (e.g., MIMO's low bit error rate and high throughput). As a result, the MIMO backscatter system has a higher bit error rate (BER) and lower throughput than the non-MIMO backscatter system. Second, since the existing backscatter systems leverage the bursty and intermittent ambient RF signals to transmit data, they may not have or only have unavailable ambient RF signals when they want to transmit data. Hence, they cannot provide ubiquitous communication for various applications. Third, the existing backscatter systems rely on specific wireless receivers and high-precision synchronization with ambient RF signals to transmit data, which both limit the widespread deployment and lower the reliability of ultra-low-power WSNs. This dissertations addresses these challenges by making the following contributions. First, we design and implement a versatile MIMO backscatter system, which leverages the diversity features of MIMO to dramatically decrease BER and increase throughput with negligible overhead. Our extensive evaluation shows that the BER is reduced by a factor of 862 compared to the most related MIMO backscatter. Second, we present the first LTE backscatter system that leverages the continuous LTE ambient traffic for ubiquitous, high throughput, and low latency backscatter communication. The results show that our LTE backscatter's performance is consistently orders of magnitude better than WiFi backscatter. Finally, we design a novel OFDM backscatter, which uses high-granularity sample-level modulation to avoid the need for specific wireless receivers and high-precision synchronization. The results show that our OFDM backscatter has three to four orders of magnitude lower BER when its throughput is similar to the latest OFDM backscatter system.