Research Article
Spectrum Analysis Using Semantic Models for Context
@INPROCEEDINGS{10.1007/978-3-030-25748-4_10, author={Vaishali Nagpure and Stephanie Vaccaro and Cynthia Hood}, title={Spectrum Analysis Using Semantic Models for Context}, proceedings={Cognitive Radio-Oriented Wireless Networks. 14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11--12, 2019, Proceedings}, proceedings_a={CROWNCOM}, year={2019}, month={8}, keywords={Spectrum occupancy Spectrum measurements Semantic modeling Land Mobile Radio}, doi={10.1007/978-3-030-25748-4_10} }- Vaishali Nagpure
Stephanie Vaccaro
Cynthia Hood
Year: 2019
Spectrum Analysis Using Semantic Models for Context
CROWNCOM
Springer
DOI: 10.1007/978-3-030-25748-4_10
Abstract
With the ever-increasing demand for spectrum to support wireless innovation, it is critical to understand the fine-grained characteristics of spectrum use in frequency, space and time to facilitate greater spectrum sharing. Contextual information is needed to analyze how the spectrum is being utilized and understand the drivers for spectrum use dynamics. Since human activity often drives spectrum use, understanding this activity can provide significant insight. Analysis of wideband spectrum is extremely time consuming as each band has unique characteristics, domain knowledge and usage drivers. Toward automated analysis, this paper proposes an approach to incorporate contextual information into the analysis utilizing semantic models to capture domain and human activity knowledge. This approach is illustrated through analysis of spectrum measurements of four frequencies licensed to the Chicago White Sox.