Scalable Communication with Passive-Sensing Backscatter Tags

Abstract

Internet of things (IoT) devices have revolutionized massive sensor networks and data collection. Their scale, emphasis on low complexity, and need for low power consumption have piqued interest in ways to make these systems fully passive. Passive sensing has been widely adopted in near-field communication technology, such as wireless payments, and is also pervasive in far-field RFID systems; however, due to the extremely low power, susceptibility to noise, and power loss due to signal attenuation, these fully passive technologies have struggled to effectively break into higher frequency regimes such as 2.4 GHz. Recent developments made possible by large-area electronics (LAE) have facilitated the creation of a fully passive backscatter tag capable of operating in the 2.4 GHz regime. This thesis modeled this novel tag, evaluated On-Off Keying and Frequency-Shift Keying modulation schemes as well as their higher order variants employable on the tag, simulated its response to channel noise, and explored very simple multi-user access schemes (statically allocated and fully random frequency hopping as well as a simplified p-persistent slotted ALOHA) while providing a foundation for future work through the produced simulation software.