In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

Milad Heydariaan

will defend his dissertation

Efficient and Scalable Localization with Ultra-Wideband Radios Through Concurrent Transmissions

Abstract

The technology to determine the location of a mobile device, also called localization technology, enables us to develop applications and systems that can optimize our work and lives in the physical world. Many IoT applications today rely on GPS for localization. However, GPS fails to provide the necessary location accuracy for indoor applications. Ultra-wideband (UWB) radios have facilitated accurate and precise (10 cm) indoor localization in the past few years. Wireless interference can severely impact the performance of localization and communication systems. Many localization and communication systems avoid or mitigate the destructive interference, which can lead to inefficient use of the wireless spectrum. A relatively new research approach to increase efficiency and scalability is to enable concurrent transmissions, i.e., create techniques that allow multiple transmitters to transmit their packets concurrently while enabling the receivers to successfully receive and decode those packets, and consequently reduce the total time required for packet exchanges. Time-of-arrival (ToA)-based localization and angle-of-arrival (AoA)-based localization are two common techniques for precise indoor localization with UWB radios. A UWB receiver node can measure the difference in ToA or AoA from multiple UWB transmitter nodes by analyzing the channel impulse response (CIR). Related work investigated the feasibility of UWB ToA-based concurrent localization, but existing solutions are not practical in real-world environments due to scalability and accuracy issues. To the best of our knowledge, there is no prior work on concurrent AoA estimation. In this dissertation, we focus on three main challenges: (1) Designing a reflection-resilient concurrent response detection algorithm by making use of the differences between the time deviation of concurrent peaks and multipath components (MPCs); (2) Relaxing transmitter processing time constraints by using a clock skew correction method to minimize inaccuracies caused by clock drift; and (3) Investigating the feasibility of concurrent AoA estimation with UWB radios and designing an efficient, scalable, and accurate indoor localization system using an angle-difference-of-arrival (ADoA) technique. Our research not only creates new algorithms and designs of localization systems but also evaluates their performance using real-world implementations on state-of-the-art hardware platforms and testbeds.

Date: Friday, April 10, 2020
Time: 3:00 - 5:00 PM
Place: Online Presentation - Google Meet
https://meet.google.com/mso-qqox-xrc 
Advisor: Dr. Omprakash Gnawali

Faculty, students, and the general public are invited.