Maximum Eigenvalue detection for spectrum sensing under correlated noise

Sharma, Shree Krishna; Chatzinotas, Symeon; Ottersten, Björn

doi:10.1109/icassp.2014.6855011

Cited by 19 publications

(8 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MED [12], minimum eigenvalue (ME) [13], two stage spectrum sensing detection (ED and CMME) [14], energy and eigenvalue based detections combined as fully blind and self adaptive [15]. The implementation of this dual stage detection scheme has been carried out using GNU radio and USRP.…”

Section: Network Protocols and Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

A Review on the Evolution of Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio

Patil¹,

Lande²,

Naikwadi³

2016

NPA

View full text Add to dashboard Cite

Spectrum scarcity has been encountered as a leading problem when launching new wireless services. To overcome this problem, cognitive radio is an optimistic solution. Spectrum sensing is a prominent task of cognitive radio. Over the past decade, numerous spectrum sensing algorithms have been proposed. In this paper, we present a comprehensive survey of evolutionary achievements of eigenvalue based spectrum sensing algorithms. The correlation between signal samples due to oversampling, multipath or multiple receivers gets reflected on the eigenvalues of the covariance matrix. It has been observed that different combinations of eigenvalues are used as test statistics and the distribution of eigenvalues and derivation of probability of detection is based on RMT (Random Matrix Theory). The main advantage offered by these algorithms is their robustness to noise uncertainty which severely affect www.macrothink.org/npa 58 Network Protocols and Algorithms ISSN 1943-3581 2016 other methods. Furthermore, they do not require accurate synchronization. These detections can be used for different signal detection applications without any prior information of signal or noise. To evaluate the performance of eigenvalue based spectrum sensing techniques under fading channels, we have simulated maximum to minimum eigenvalue based Detection (MME) and maximum eigenvalue based detection (MED) for Rician fading channel. Simulation results shows that MME is much better than MED.

show abstract

Section: Network Protocols and Algorithmsmentioning

confidence: 99%

“…It is observed that the threshold calculated for uncorrelated scenario when applied to correlated scenarios, the fa P value gets deviated from the targeted fa P value. To address this problem, threshold function is derived for correlated noise [12].…”

Section: Maximum Eigenvalue Based Detection For Correlated Noisementioning

confidence: 99%

A Review on the Evolution of Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio

Patil¹,

Lande²,

Naikwadi³

2016

NPA

View full text Add to dashboard Cite

show abstract

“…By using different eigenvalue properties of R Y (N ) such as Maximum Eigenvalue (ME) [17], Signal Condition Number (SCN) [4,15], Scaled Largest Eigenvalue (SLE) [14], etc., the presence or absence of the PU signal can be decided. 2.…”

Section: System and Signal Modelmentioning

confidence: 99%

Cooperative Spectrum Sensing for Heterogeneous Sensor Networks Using Multiple Decision Statistics

Sharma

Chatzinotas

Ottersten

2015

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Self Cite

View full text Add to dashboard Cite

Abstract. The detection of active Primary Users (PUs) in practical wireless channels with a single Cognitive Radio (CR) sensor is challenging due to several issues such as the hidden node problem, path loss, shadowing, multipath fading, and receiver noise/interference uncertainty. In this context, Cooperative Spectrum Sensing (CSS) is considered a promising technique in order to enhance the overall sensing efficiency. Existing CSS methods mostly focus on homogeneous cooperating nodes considering identical node capabilities, equal number of antennas, equal sampling rate and identical Signal to Noise Ratio (SNR). However, in practice, nodes with different capabilities can be deployed at different stages and are very much likely to be heterogeneous in terms of the aforementioned features. In this context, we propose a novel decision statistics-based centralized CSS technique using the joint Probability Distribution Function (PDF) of the multiple decision statistics resulting from different processing capabilities at the sensor nodes and compare its performance with various existing cooperative schemes. Further, we provide a design guideline for the network operators to facilitate decision making while upgrading a sensor network.

show abstract

“…Noise/Channel Correlation Although recent works [36], [140] have proposed new sensing bounds for SCN and ME based sensing under noise correlated scenarios, analyzing the effect of noise correlation on the performance of other detectors as well as investigation of new sensing bounds which provide improved detection performance under correlated scenarios is still an open research challenge. Future research should focus on investigating suitable approaches while considering these imperfections into account.…”

Section: Quantization Errorsmentioning

confidence: 99%

“…To address the aforementioned issue, new sensing thresholds for SCN and ME based techniques have been proposed in [139], [140] using recent results from RMT in order to achieve the improved sensing in correlated noise scenarios. The analysis has been carried out by considering a one-sided exponential correlation model to include noise correlation across the receive dimensions and the similar analysis is applicable for temporally correlated case assuming the exponential correlation model still holds.…”

Section: Noise/channel Correlationmentioning

confidence: 99%

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Sharma

Bogale

Chatzinotas

et al. 2015

IEEE Commun. Surv. Tutorials

Self Cite

199

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

Maximum Eigenvalue detection for spectrum sensing under correlated noise

Cited by 19 publications

References 38 publications

A Review on the Evolution of Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio

A Review on the Evolution of Eigenvalue Based Spectrum Sensing Algorithms for Cognitive Radio

Cooperative Spectrum Sensing for Heterogeneous Sensor Networks Using Multiple Decision Statistics

Cognitive Radio Techniques Under Practical Imperfections: A Survey

Contact Info

Product

Resources

About