Washington University in St. Louis
Locating Unknown Interference Sources with Time Difference of Arrival Estimates
Abstract
dc:description.abstract<p>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.</p>
Degree
thesis:*- Name thesis:degree_name
- Master of Science (MS)
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Electrical & Systems Engineering
- Year dc:date.available
- 2022
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Kuo, Chia Ying
- Contributors dc:contributor
-
- Neal Patwari
- Joseph O'Sullivan, Raj Jain
Subjects
dc:subject × 6Rights
dc:rights- Statement dc:rights
-
- I have not registered my thesis with the U.S. Copyright Office, but intend to later.
- Language dc:language
- English (en)
Identifiers
dc:identifier.*- OAI identifier oai:identifier
- oai:openscholarship.wustl.edu:eng_etds-1758