Data fusion-aided cognitive radio network over generalised fading channels

In this Letter, the authors study analytical performance of various soft data fusion (SDF) schemes over generalised fading channels in a cognitive radio network. Two generalised fading models, namely, $\kappa -\mu $κ−μ and $\eta -\mu $η−μ are considered individually in the sensing channels and vario...

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Published inElectronics letters Vol. 55; no. 5; pp. 285 - 287
Main Author Nallagonda, Srinivas
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 07.03.2019
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Abstract In this Letter, the authors study analytical performance of various soft data fusion (SDF) schemes over generalised fading channels in a cognitive radio network. Two generalised fading models, namely, $\kappa -\mu $κ−μ and $\eta -\mu $η−μ are considered individually in the sensing channels and various SDF techniques are implemented at the fusion centre. Novel analytical frameworks for cooperative detection probability are developed subject to SDF and generalised fading and validated through computer simulations. Optimal values of the detection thresholds are determined where an average error rate is minimum.
AbstractList In this Letter, the authors study analytical performance of various soft data fusion (SDF) schemes over generalised fading channels in a cognitive radio network. Two generalised fading models, namely, κ−μ and η−μ are considered individually in the sensing channels and various SDF techniques are implemented at the fusion centre. Novel analytical frameworks for cooperative detection probability are developed subject to SDF and generalised fading and validated through computer simulations. Optimal values of the detection thresholds are determined where an average error rate is minimum.
In this Letter, the authors study analytical performance of various soft data fusion (SDF) schemes over generalised fading channels in a cognitive radio network. Two generalised fading models, namely, $\kappa -\mu $κ−μ and $\eta -\mu $η−μ are considered individually in the sensing channels and various SDF techniques are implemented at the fusion centre. Novel analytical frameworks for cooperative detection probability are developed subject to SDF and generalised fading and validated through computer simulations. Optimal values of the detection thresholds are determined where an average error rate is minimum.
In this Letter, the authors study analytical performance of various soft data fusion (SDF) schemes over generalised fading channels in a cognitive radio network. Two generalised fading models, namely, and are considered individually in the sensing channels and various SDF techniques are implemented at the fusion centre. Novel analytical frameworks for cooperative detection probability are developed subject to SDF and generalised fading and validated through computer simulations. Optimal values of the detection thresholds are determined where an average error rate is minimum.
Author Nallagonda, Srinivas
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Cites_doi 10.1109/TSP.2011.2170978
10.1002/sat.1200
10.1109/TAES.2017.2732798
10.1109/MAP.2007.370983
10.1109/TVT.2012.2228680
10.1109/98.788210
10.1049/iet-com.2014.0199
10.1109/TCOMM.2006.887483
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Keywords signal detection
fading channels
cognitive radio
sensing channels
cooperative detection probability
sensor fusion
SDF techniques
data fusion-aided cognitive radio network
soft data fusion schemes
generalised fading models
cooperative communication
generalised fading channels
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StartPage 285
SubjectTerms cognitive radio
cooperative communication
cooperative detection probability
data fusion‐aided cognitive radio network
fading channels
generalised fading channels
generalised fading models
SDF techniques
sensing channels
sensor fusion
signal detection
soft data fusion schemes
Wireless communications
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Title Data fusion-aided cognitive radio network over generalised fading channels
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