University of Oulu

A. Al-Tahmeesschi, M. Lopez-Benitez, J. Lehtomaki and K. Umebayashi, "Investigating the Estimation of Primary Occupancy Patterns under Imperfect Spectrum Sensing," 2017 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), San Francisco, CA, 2017, pp. 1-6. doi: 10.1109/WCNCW.2017.7919112

Investigating the estimation of primary occupancy patterns under imperfect spectrum sensing

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Author: Al-Tahmeesschi, Ahmed1; López-Benítez, Miguel1; Lehtomäki, Janne2;
Organizations: 1Dept. of Electrical Engineering and Electronics, University of Liverpool, United Kingdom
2Centre for Wireless Communications, University of Oulu, Finland
3Graduate School of Engineering, Tokyo University of Agriculture and Technology, Japan
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018090434564
Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2018-09-04
Description:

Abstract

Dynamic Spectrum Access (DSA)/Cognitive Radio (CR) systems access the channel in an opportunistic, noninterfering manner with the primary network. As a result, CR performance depends on the primary channel occupancy pattern. The occupancy pattern of primary network is affected by multiple factors including time, location and frequency band. This work focuses on the time domain of spectrum sharing. The objective of this work is to study how the primary user activity pattern in the time domain (i.e., statistical distribution of the durations of idle/busy periods) affects the ability of the CR system to obtain accurate statistical information based on spectrum sensing observations. In this research, we model the primary activity pattern as a Continuous-Time Semi-Markov Chain (CTSMC). Different distributions to imitate occupancy patterns of primary network are tested by means of simulation, first when having a perfect spectrum sensing, then in the presence of imperfect spectrum sensing. It is shown that every occupancy pattern (i.e., distribution) actually leads to different levels of accuracy in the estimated statistics. A new algorithm to palliate the degrading effects of spectrum sensing errors is proposed and evaluated. The new and considered algorithms can improve the prediction of primary network statistics, however with different levels of effectiveness depending on the primary activity pattern.

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ISBN: 978-1-5090-5908-9
ISBN Print: 978-1-5090-5909-6
Pages: 1 - 6
DOI: 10.1109/WCNCW.2017.7919112
OADOI: https://oadoi.org/10.1109/WCNCW.2017.7919112
Host publication: 2017 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)
Conference: IEEE Wireless Communications and Networking Conference Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
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