Fuzzy Logic Based Spectrum Sensing for Cognitive Radio Networks

Ejaz, Waleed; Hasan, Najam Ul; Aslam, Saleem; Kim, Hyung Seok

doi:10.1109/ngmast.2011.41

Cited by 29 publications

(31 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Most of the existing SS and SNR estimation techniques assume the presence of an uncorrelated channel and the noise [56], [98], [138]. However, in practical scenarios, the channel may be correlated due to insufficient scattering in the propagation environment [88] and mutual coupling between antennas [89].…”

Section: Noise/channel Correlationmentioning

confidence: 99%

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Sharma

Bogale

Chatzinotas

et al. 2015

IEEE Commun. Surv. Tutorials

200

111

View full text Add to dashboard Cite

Abstract-Cognitive Radio (CR) has been considered as a potential candidate for addressing the spectrum scarcity problem of future wireless networks. Since its conception, several researchers, academic institutions, industries, regulatory and standardization bodies have put their significant efforts towards the realization of CR technology. However, as this technology adapts its transmission based on the surrounding radio environment, several practical issues may need to be considered. In practice, several imperfections such as noise uncertainty, channel/interference uncertainty, transceiver hardware imperfections, signal uncertainty, synchronization issues, etc. may severely deteriorate the performance of a CR system. To this end, the investigation of realistic solutions towards combating various practical imperfections is very important for successful implementation of the cognitive technology. In this direction, first, this survey paper provides an overview of the enabling techniques for CR communications. Subsequently, it discusses the main imperfections that may occur in the most widely used CR paradigms and then reviews the existing approaches towards addressing these imperfections. Finally, it provides some interesting open research issues.

show abstract

Section: Noise/channel Correlationmentioning

confidence: 99%

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Sharma

Bogale

Chatzinotas

et al. 2015

IEEE Commun. Surv. Tutorials

200

111

View full text Add to dashboard Cite

show abstract

“…Alternatively different from the above approaches researchers have tried to solve this limitation of energy detector by adopting soft decision method using Fuzzy logic [18,27,19,20,9] as there is great deal of ambiguity, uncertainty or fuzziness in the 'confused region' as shown in Figure 1 for a cooperative sensing scenario. The disadvantages cooperative based sensing are the increased hardware overhead as well as sensing latency.…”

Section: Related Workmentioning

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

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

“…This approach provides good sensing performance and high flexibility for decision combining at the fusion center. In [13], the author proposed a spectrum sensing scheme with fuzzy logic that is applied in the local node. In this scheme, the author performs three different spectrum sensing techniques simultaneously in the local node.…”

Section: Related Workmentioning

confidence: 99%