Abstract
Adaptive spectrum sharing between different systems and operators is being deployed in order to make use of the wireless spectrum more efficiently. However, when the spectrum is shared, it can create situations in which an operator is unable to determine the identity of an interferer transmitting an unknown signal. This is the situation in which the POWDER testbed found itself in, starting in late 2021. This thesis provides general-purpose tools for operators to locate an unknown signal source in real-world outdoor environments. We used cross-correlation between the signals measured at multiple time-synchronized base stations to estimate the time difference of arrival (TDoA) between each pair. Then, we used a TDoA localization algorithm to locate each unknown transmitted signal source. In particular, for POWDER, we applied these methods to estimate the source locations of multiple unknown interference signals detected in the citizens broadband radio service (CBRS) band with multiple static base stations as the receivers. The localization results are displayed in grid maps that indicate the most likely signal source coordinates of the unknown signals. Our tools are open source and available for other researchers to locate interferers near their deployed network.
Committee Chair
Neal Patwari
Committee Members
Joseph O'Sullivan, Raj Jain
Degree
Master of Science (MS)
Author's Department
Electrical & Systems Engineering
Document Type
Thesis
Date of Award
Spring 5-2022
Language
English (en)
DOI
https://doi.org/10.7936/7n7k-4b40
Recommended Citation
Kuo, Chia Ying, "Locating Unknown Interference Sources with Time Difference of Arrival Estimates" (2022). McKelvey School of Engineering Theses & Dissertations. 711.
The definitive version is available at https://doi.org/10.7936/7n7k-4b40