Hierarchical Cooperative Spectrum Sensing Based on Double Thresholds Energy Detection

Liu, Shiqi; Hu, Bin‐Jie; Wang, Xian-Yi

doi:10.1109/lcomm.2012.050112.120765

Cited by 85 publications

(60 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To mitigate this problem of noise uncertainty, authors in [25,15,5] used the concept of double threshold (introduced above) in a cooperative sensing environment for CR network. The idea of hierarchical quantization has been exploited in [6] at the local CR level.…”

Section: Related Workmentioning

confidence: 99%

“…4 (a), (b), (c) and (d). The transformation of the fuzzy output (FD), to decision result is done by computing a new threshold called Fuzzy Threshold (λ f ) using newly proposed geometric mean method (15) The fuzzy output that is obtained after rule aggregation using center of area (COA) method [23] for a particular input, is transformed to the crisp binary decision values {H 0 =0, H 1 =1} by comparing the outputs with a fuzzy threshold. …”

Section: Problem Formulation On Fuzzy Decision Rulementioning

confidence: 99%

See 1 more Smart Citation

Improved Energy Detector for Spectrum Sensing Using Neuro-Fuzzy Double Threshold Technique

Dey¹,

Hossain²,

Balas³

et al. 2017

STUD INFORM CONTROL

View full text Add to dashboard Cite

This paper reports a modified and computationally efficient energy detection method for spectrum sensing in cognitive radio (CR) system utilising hybrid soft computing paradigms. The proposed soft computing method uses artificial neural network and fuzzy logic for learning and decision making as a solution to the problems when CR system is subjected to threshold uncertainty and uncertainties in noise variance. The proposed soft computing method should be referred thereafter as Neuro-Fuzzy double threshold (NFDT) technique. The developed technique utilizes the concept of double sensing credibility while formulating the fuzzy decision rule and artificial neural network to learn the threshold function. Through simulation results it is validated that proposed method leads to overall improved probability of detection compared to conventional and existing methods.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Problem Formulation On Fuzzy Decision Rulementioning

confidence: 99%

Improved Energy Detector for Spectrum Sensing Using Neuro-Fuzzy Double Threshold Technique

Dey¹,

Hossain²,

Balas³

et al. 2017

STUD INFORM CONTROL

View full text Add to dashboard Cite

show abstract

“…In [9], authors presented adaptive spectrum sensing scheme, where out of two stages only one of the detection stage runs at a time, presence of cyclostationary detector makes this scheme more complicated. However, to the best of available sources none of above techniques focused on spectrum sensing failure problem [10]. In [11] we presented new sensing techniques, known as double stage ED for sensing spectrum in CRN.…”

Section: Introductionmentioning

confidence: 99%

Novel Spectrum detector for IEEE 802.22 Wireless Regional Area Network

Bagwari¹,

Kanti²,

Tomar³

2015

IJSDA

View full text Add to dashboard Cite

show abstract

“…Double threshold based sensing mitigates noise uncertainty problem. But, when all measured values lie between two thresholds then it causes Spectrum sensing failure problem [15][16][17].…”

Section: Introductionmentioning

confidence: 99%