In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
will defend his dissertation
Heterogeneous Wireless and Visible Light Communication for the Internet of Things
Connecting sensor, control, and edge devices to the Internet in a reliable and robust way is critical to the success of many big data and IoT applications. Wireless technology enables such connectivity but has come under increasing challenge due to the proliferation of devices and increase in data requirements. Devices with wireless connectivity compete with each other in the limited spectrum resources, causing spectrum crunch and interference, which signicantly hampers the IoT vision. In this thesis, we study how serious the problem of interference is in wireless networks for IoT, and then we propose two solutions to solve this problem. Our goal is to connect IoT devices to the Internet with reliability, robustness, and adaptiveness using edge computing algorithms and methodologies in a practical manner. One solution is to leverage the wireless interference across various IoT devices. We transformed the interference into a covert communication channel between these devices and evaluated its feasibility in practical environments. The covert communication channel was established based on the spectrum shared by various wireless devices that were using different wireless technology, such as WiFi, Zigbee or Bluetooth. In this work, we have achieved one-way communication from WiFi devices to Zigbee devices. We have demonstrated the feasibility to send control signals utilizing the interference without any gateway. This validated that interference utilization can be a practical solution to solve spectrum crunch problem. Another solution is to avoid interference by exploring new spectrum resources that can provide wireless connectivity. We adopt visible light as the communication medium since it is ubiquitous and free from wireless interference. Existing embedded LED-to-LED communication has been rising as a promising technique for IoT connectivity. However, low cost embedded visible light communication (VLC) has been largely restricted by its reliability, robustness, and speed. In this work, we propose adaptive ambient light cancellation to improve the robustness of embedded VLC, we also present I/O offloading, concurrent communication and full-duplexing techniques to improve the reliability and speed. We designed, implemented and open sourced an embedded VLC platform which delivered 100kbps data rate with more than 95% reliability under a communication range of 6 meters. This work has improved state-of-the-art by at least 6-7x.
Date: Monday, February 26, 2018
Time: 11:00 AM
Place: PGH 550
Advisor: Dr. Omprakash Gnawali
Faculty, students, and the general public are invited.