dc.contributor.author |
Barnes, Simon Daniel
|
|
dc.contributor.author |
Maharaj, Bodhaswar Tikanath Jugpershad
|
|
dc.date.accessioned |
2013-10-31T07:35:31Z |
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dc.date.available |
2013-10-31T07:35:31Z |
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dc.date.issued |
2014-04 |
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dc.description.abstract |
The interdependency, in a cognitive radio (CR) network, of spectrum sensing, occupancy modelling, channel switching and secondary
user (SU) performance, is investigated. Achievable SU data throughput and primary user (PU) disruption rate have been
examined for both theoretical test data as well as data obtained from real-world spectrum measurements done in Pretoria, South
Africa. A channel switching simulator was developed to investigate SU performance, where a hidden Markov model (HMM) was
employed to model and predict PU behaviour, from which proactive channel allocations could be made. Results show that CR
performance may be improved if PU behaviour is accurately modelled, since accurate prediction allows the SU to make proactive
channel switching decisions. It is further shown that a trade-off may exist between achievable SU throughput and average PU
disruption rate. When using the prediction model, significant performance improvements, particularly under heavy traffic density
conditions, of up to double the SU throughput and half the PU disruption rate were observed. Results obtained from a measurement
campaign were comparable with those obtained from theoretical occupancy data, with an average similarity score of 95% for
prediction accuracy, 90% for SU throughput and 70% for PU disruption rate. |
en |
dc.description.librarian |
hb2013 |
en |
dc.description.librarian |
ai2014 |
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dc.description.sponsorship |
Sentech Chair in Broadband Wireless Multimedia Communication (BWMC), the National Research Foundation (NRF) and the Independent Communications Authority of South Africa (ICASA). |
en |
dc.description.uri |
http://www.elsevier.com/locate/aeue |
en |
dc.identifier.citation |
Barnes, SD & Maharaj, BT 2014, 'Prediction based channel allocation performance for cognitive radio', AEÜ - International Journal of Electronics and Communications, vol. 68, no. 4, pp. 336-345. |
en |
dc.identifier.issn |
1434-8411 (print) |
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dc.identifier.issn |
1618-0399 (online) |
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dc.identifier.other |
10.1016/j.aeue.2013.09.009 |
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dc.identifier.uri |
http://hdl.handle.net/2263/32234 |
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dc.language.iso |
en |
en |
dc.publisher |
Elsevier |
en |
dc.rights |
© 2013 Published by Elsevier GmbH.Notice : this is the author’s version of a work that was accepted for publication in AEÜ - International Journal of Electronics and Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in AEÜ - International Journal of Electronics and Communications, vol. 68, no. 4, pp. 336-345, 2014, doi : 10.1016/j.aeue.2013.09.009 |
en |
dc.subject |
Channel switching |
en |
dc.subject |
Occupancy modelling |
en |
dc.subject |
Secondary user performance |
en |
dc.subject |
Spectrum measurements |
en |
dc.subject.lcsh |
Cognitive radio networks -- South Africa |
en |
dc.subject.lcsh |
Telecommunication systems -- South Africa |
en |
dc.title |
Prediction based channel allocation performance for cognitive radio |
en |
dc.type |
Postprint Article |
en |