dc.contributor.author |
Onumanyi, Adeiza J
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dc.contributor.author |
Abu-Mahfouz, Adnan MI
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dc.contributor.author |
Hancke, GP
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dc.date.accessioned |
2018-10-01T10:14:01Z |
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dc.date.available |
2018-10-01T10:14:01Z |
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dc.date.issued |
2018-08 |
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dc.identifier.citation |
Onumanyi, A.J., Abu-Mahfouz, A.M.I. and Hancke, G.P. 2018. A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio. Physical Communication, vol. 29(8): 1-11 |
en_US |
dc.identifier.govdoc |
https://www.sciencedirect.com/science/article/pii/S1874490718300405 |
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dc.identifier.issn |
1874-4907 |
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dc.identifier.uri |
https://doi.org/10.1016/j.phycom.2018.04.008
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dc.identifier.uri |
http://hdl.handle.net/10204/10432
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|
dc.description |
Copyright: 2018 Elsevier. Due to copyright restrictions, the attached pdf contains a preprint version of the published article. The published version can be obtained from the publisher's website, at https://www.sciencedirect.com/science/article/pii/S1874490718300405 |
en_US |
dc.description.abstract |
In this paper, we compare local and global adaptive threshold estimation techniques for energy detection in Cognitive Radio (CR). By this comparison we provide a sum-up synopsis on the effective performance range and the operating conditions under which both classes best apply in CR. Representative methods from both classes were implemented and trained using synthesized signals to fine tune each algorithm’s parameter values. Further tests were conducted using real-life signals acquired via a spectrum survey exercise and results were analysed using the probability of detection and the probability of false alarm computed for each algorithm. It is observed that while local based methods may be adept at maintaining a low constant probability of false alarm, they however suffer a grossly low probability of detection over a wide variety of CR spectra. Consequently, we concluded that global adaptive threshold estimation techniques are more suitable for signal detection in CR than their local adaptive thresholding counterparts. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.relation.ispartofseries |
Worklist;21400 |
|
dc.subject |
Cognitive radio |
en_US |
dc.subject |
Comparative analysis |
en_US |
dc.subject |
Energy detector |
en_US |
dc.subject |
Global |
en_US |
dc.subject |
Local |
en_US |
dc.subject |
Threshold |
en_US |
dc.title |
A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio |
en_US |
dc.type |
Article |
en_US |
dc.identifier.apacitation |
Onumanyi, A., Abu-Mahfouz, A. M., & Hancke, G. (2018). A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio. http://hdl.handle.net/10204/10432 |
en_ZA |
dc.identifier.chicagocitation |
Onumanyi, AJ, Adnan MI Abu-Mahfouz, and GP Hancke "A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio." (2018) http://hdl.handle.net/10204/10432 |
en_ZA |
dc.identifier.vancouvercitation |
Onumanyi A, Abu-Mahfouz AM, Hancke G. A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio. 2018; http://hdl.handle.net/10204/10432. |
en_ZA |
dc.identifier.ris |
TY - Article
AU - Onumanyi, AJ
AU - Abu-Mahfouz, Adnan MI
AU - Hancke, GP
AB - In this paper, we compare local and global adaptive threshold estimation techniques for energy detection in Cognitive Radio (CR). By this comparison we provide a sum-up synopsis on the effective performance range and the operating conditions under which both classes best apply in CR. Representative methods from both classes were implemented and trained using synthesized signals to fine tune each algorithm’s parameter values. Further tests were conducted using real-life signals acquired via a spectrum survey exercise and results were analysed using the probability of detection and the probability of false alarm computed for each algorithm. It is observed that while local based methods may be adept at maintaining a low constant probability of false alarm, they however suffer a grossly low probability of detection over a wide variety of CR spectra. Consequently, we concluded that global adaptive threshold estimation techniques are more suitable for signal detection in CR than their local adaptive thresholding counterparts.
DA - 2018-08
DB - ResearchSpace
DP - CSIR
KW - Cognitive radio
KW - Comparative analysis
KW - Energy detector
KW - Global
KW - Local
KW - Threshold
LK - https://researchspace.csir.co.za
PY - 2018
SM - 1874-4907
T1 - A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio
TI - A comparative analysis of local and global adaptive threshold estimation techniques for energy detection in cognitive radio
UR - http://hdl.handle.net/10204/10432
ER - |
en_ZA |