Statistical spectrum occupancy prediction for dynamic spectrum access: a classification

Eltom, H, Sithamparanathan, K, Evans, R, Liang, Y and Ristic, B 2018, 'Statistical spectrum occupancy prediction for dynamic spectrum access: a classification', Eurasip Journal on Wireless Communications and Networking, vol. 2018, no. 1, pp. 1-17.


Document type: Journal Article
Collection: Journal Articles

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Title Statistical spectrum occupancy prediction for dynamic spectrum access: a classification
Author(s) Eltom, H
Sithamparanathan, K
Evans, R
Liang, Y
Ristic, B
Year 2018
Journal name Eurasip Journal on Wireless Communications and Networking
Volume number 2018
Issue number 1
Start page 1
End page 17
Total pages 17
Publisher Springer
Abstract Spectrum scarcity due to inefficient utilisation has ignited a plethora of dynamic spectrum access solutions to accommodate the expanding demand for future wireless networks. Dynamic spectrum access systems allow secondary users to utilise spectrum bands owned by primary users if the resulting interference is kept below a pre-designated threshold. Primary and secondary user spectrum occupancy patterns determine if minimum interference and seamless communications can be guaranteed. Thus, spectrum occupancy prediction is a key component of an optimised dynamic spectrum access system. Spectrum occupancy prediction recently received significant attention in the wireless communications literature. Nevertheless, a single consolidated literature source on statistical spectrum occupancy prediction is not yet available in the open literature. Our main contribution in this paper is to provide a statistical prediction classification framework to categorise and assess current spectrum occupancy models. An overview of statistical sequential prediction is presented first. This statistical background is used to analyse current techniques for spectrum occupancy prediction. This review also extends spectrum occupancy prediction to include cooperative prediction. Finally, theoretical and implementation challenges are discussed.
Subject Signal Processing
Keyword(s) Bayesian prediction
Cognitive radio
Cooperative prediction
Dynamic spectrum access
Markov models
Mixture models
Sequential prediction
Spectrum occupancy
Spectrum prediction
Universal prediction
DOI - identifier 10.1186/s13638-017-1019-8
Copyright notice © 2018, The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
ISSN 1687-1472
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