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SEMANTIC ONTOLOGIES FOR THE PUBLICATION OF SPECTRUM MEASUREMENT PROVENANCE
Title
SEMANTIC ONTOLOGIES FOR THE PUBLICATION OF SPECTRUM MEASUREMENT PROVENANCE
Creator
Faurie, Eric A.
Date
2016, 2016-05
Description
Measurement-based spectrum research isn’t new, but there is a renewed interest in understanding how the spectrum is being utilized. With the...
Show moreMeasurement-based spectrum research isn’t new, but there is a renewed interest in understanding how the spectrum is being utilized. With the modern prevalence of connected devices and our increasing reliance on wireless technologies, there is increasing demand for additional spectrum. The question of how to meet this demand largely depends on how the spectrum is being used today and thus a need for advanced measurement-based research has emerged. Spectrum measurement and analysis is complicated; the data is multi-dimensional and dynamic in time, space, and frequency. Signal behavior is governed by complex mathematics and its use is regulated by government agencies across the world. Data collection relies on a complex system of expensive hardware where the physical attributes of antennas, analyzers, and deployment locations all impact the data that’s collected. These variables and concerns must all be considered while deploying a Spectrum measurement system. This paper presents the Semantic Spectrum Ontology (SSO), a model which aids researchers in designing and deploying Spectrum Measurement systems and publishing their data as community resources. The SSO exists within the paradigm of the Semantic Web and links into the wider Semantic graph by extending the W3C’s Semantic Sensor Network Ontology (SSN). The Semantic Spectrum Ontology also presents two new Semantic Constructs. The Scientific Provenance Model allows researchers to publish in-depth metadata concerning the measurements and the conditions under which they were collected, and the Scientific Property Model creates a framework for encoding knowledge from various sources including domain experts and machine learning statistics. These two models were constructed specifically for the SSO but were generalized to allow for their application within any ontology representing any scientific field.
M.S. in Computer Science, May 2016
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A Reasoning System Architecture for Spectrum Decision-making
Title
A Reasoning System Architecture for Spectrum Decision-making
Creator
Das, Udayan D.
Date
2021
Description
Spectrum is a public resource; yet understanding how spectrum is allocated and used is a daunting task. Usable spectrum is already fully...
Show moreSpectrum is a public resource; yet understanding how spectrum is allocated and used is a daunting task. Usable spectrum is already fully allocated, but the demand for spectrum continues to grow and there are opportunities for utilizing spectrum in more efficient ways. Understanding how spectrum is allocated and its utilization in time and space is necessary to take advantage of these emerging opportunities. A combination of fragmented information from varied information sources, a complex regulatory environment, variability of regulations and physics by band, real-time spectrum usage dynamics, and a status quo with knowledge concentration among a few, makes understanding spectrum a considerable challenge for all stakeholders including researchers, students, policymakers, and new telecom operators. After considerable study of spectrum, its allocation, regulation, and usage, we have developed a system architecture that is a significant step towards easing the burden of understanding spectrum information. Our system architecture connects information from disparate sources and leads to a richer understanding of spectrum usage, how it is governed, and its potential for future use. Classes of information are modeled as knowledge graphs, and the interplay of knowledge graphs produces a richer set of insight and can lead to more informed decision-making. Further, we show mechanisms for connecting spectrum information with real-time observations to get a comprehensive view of spectrum usage dynamics. While focused on the United States, this work should be applicable to other spectrum contexts worldwide. This work, of considerable technical value, also has democratic value in making complex information accessible and allowing the public to determine whether spectrum, a natural resource, is being used for the public good.
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