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Analytical Modeling of White Space Utilization for a Dynamic Spectrum Access System

Published

Author(s)

Robert Hagwood, Anirudha Sahoo, Timothy Hall

Abstract

Dynamic Spectrum Access (DSA) promises to be a shared spectrum technology that can alleviate the artificial spectrum crunch created by the static allocation of spectrum. There have been many studies on DSA systems in the literature. However, most of them are analyzed using simulation studies rather than analytical modeling. Analytical models are useful in evaluating performance of such systems quickly and easily. In this paper, we present an analytical model of an opportunistic DSA system which is based on survival analysis. Using an alternating renewal process to represent primary user traffic of the DSA system and applying theory from survival analyis and stochastic process, we derive an expression to compute the white space utilization (WSU) of a DSA system for a general distribution of idle durations of primary traffic. Taking the exponential distribution as an example, we validate our analytical model by comparing the results of our analytical model to results obtained from two simulation experiments. One experiment uses idle durations generated from pseudorandom variates and the other uses data collected from a real LTE system whose idle duration distribution is approximately exponential. Our analytical WSU results match closely with those from the first experiment and match reasonably well with those obtained from the second experiment.
Conference Dates
April 15-18, 2019
Conference Location
Marrakech, MA
Conference Title
IEEE Wireless Communications and Networking Conference

Keywords

dynamic spectrum access, spectrum sharing, survival analysis

Citation

Hagwood, R. , Sahoo, A. and Hall, T. (2019), Analytical Modeling of White Space Utilization for a Dynamic Spectrum Access System, IEEE Wireless Communications and Networking Conference, Marrakech, MA, [online], https://doi.org/10.1109/WCNC.2019.8885681, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927089 (Accessed May 19, 2024)

Issues

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Created April 14, 2019, Updated October 12, 2021