IoT Networking via Cross-technology Communication

Abstract

The prevalence of Internet of Things (IoT) brings various heterogeneous wireless techniques, such as Wi-Fi, LTE, ZigBee,Bluetooth, and LoRa. Due to the scarcity of spectrum resources, these wireless technologies commonly share the unlicensed industrial, scientific and medical (ISM) radio band. The coexistence scenario motivates the studies of IoT networking among heterogeneous wireless devices, which breaks the boundary between wireless protocols and paves way for a lot of novel applications (e.g., cross-technology data dissemination, data collection, location services, etc.). This dissertation focuses on the key enabler of IoT networking among heterogeneity - cross-technology communication (CTC) which allows heterogeneous wireless devices to directly exchange data without modifying their hardware. To address the critical roadblock of CTC - incompatibility in their physical (PHY) layers, we propose two approaches, demonstrating the feasibility of CTC both from high-speed to low-speed radios and from low-speed to high-speed ones. First, we present LTE2B which enables CTC from high-speed radios (e.g., LTE) to low-speed radios (e.g., ZigBee and Bluetooth). The key technical contribution is a time-domain signal emulation (TDE) approach which allows a LTE transmitter to produce emulated ZigBee or Bluetooth signal by approximating their time-domain waveform. In addition, it addresses other practical constraints (e.g., turbo coding constraint) to achieve transparent CTC with full compatibility with LTE standards. Our experiment result shows that LTE smartphones can directly disseminate messages to ZigBee devices within a 400-meter range. Second, we introduce XFi which shows the feasibility of CTC in the reverse direction, i.e., from low-speed radios (e.g., ZigBee and LoRa) to high-speed Wi-Fi. To address the fundamental limitation of bandwidth disparity, XFi adopts signal hitchhiking - low-speed IoT packets from ZigBee and LoRa devices can hitchhike on the high-speed Wi-Fi traffic and be captured by Wi-Fi radios. The unique discovery is that Wi-Fi devices can obtain the hitchhiking IoT data from the errors in decoded Wi-Fi payloads that are available in the software. The key insight enables CTC with zero modification to Wi-Fi hardware. Our evaluation demonstrates that Wi-Fi can collect data from 8 IoT devices in parallel with an overall throughput of 1.8 Mbps. Finally, we adopt CTC technique in a commercial Bluetooth location service to study and address the challenges of applying cross-technology design in real-world scenarios. We propose WiBeacon which repurposes ubiquitously deployed WiFi access points (AP) into virtual BLE beacons via only moderate software upgrades. This offers fast deployment of BLE LBS with zero additional hardware costs and low maintenance burdens. WiBeacon is carefully integrated with native WiFi services, retaining transparency to WiFi clients. We implement WiBeacon on commodity WiFi APs (with various chipsets such as Qualcomm, Broadcom, and MediaTek) and extensively evaluate it across various scenarios, including a real commercial application for courier check-ins. During the two-week pilot study, WiBeacon provides reliable services, i.e., as robust as conventional BLE beacons, for 697 users with 150 types of smartphones.