Performance of energy detector in the presence of noise uncertainty in cognitive radio networks

Energy detection (ED) is a popular spectrum sensing technique in cognitive radio to detect the primary user. But the detection performance of ED deteriorates in the presence of noise uncertainty and exhibits associated SNR wall phenomenon. In this paper, the generalized energy detector (GED) is investigated, where the squaring operation of amplitude of received samples in conventional energy detector (CED) is replaced by an arbitrary positive operation p. Our aim is to study the effect of noise uncertainty on the detection performance of GED. We consider different distributions of noise uncertainty. Initially, uniform distribution of noise uncertainty is considered and an expression of the SNR wall for the same is derived. It is shown that the SNR wall for uniformly distributed noise uncertainty is independent of p. The study of the detection performance of GED is further extended for log-normally distributed noise uncertainty, where the SNR wall is calculated numerically.

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“…In [11]- [13], the effect of uniform distribution of noise uncertainty is analysed on CED. The SNR wall expression is found for the same in [11].…”

Section: Introductionmentioning

confidence: 99%

SNR wall for generalized energy detection under noise uncertainty in cognitive radio

Kalamkar

Banerjee

Gupta

2013

2013 19th Asia-Pacific Conference on Communications (APCC)

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“…In the presence of noise uncertainty, c a � ρc n , where ρ is the noise uncertainty coefficient, and its value in dB is denoted by β � 10 log 10 ρ. Usually, β is uniformly distributed in the interval [−B, B] [10,17]. en, the PDF of β can be expressed as…”

Section: Performance Analysis Of the Logarithmic Detector Inmentioning

confidence: 99%

“…In nonpresence of noise uncertainty, the false alarm and detection probabilities can be calculated using (16) and (17). When the noise uncertainty does exist, the noise dispersion c is no longer a constant value.…”

Section: Performance Analysis Of the Logarithmic Detector Inmentioning

confidence: 99%

Nonparametric Blind Signal Detection Based on Logarithmic Moments in Very Impulsive Noise

Jin-jun

Wang

Er-yang

et al. 2018

Mobile Information Systems

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The detection problem in impulsive noise modeled by the symmetric alpha stable SαS distribution is studied. The traditional detectors based on the second or higher order moments fail in SαS noise, and the method based on the fractional lower order moments (FLOMs) performs poorly when the noise distribution has small values of characteristic exponent. In this paper, a detector based on the logarithmic moments is investigated. The analytical expressions of the false alarm and detection probabilities are derived in nonfading channels as well as Rayleigh fading channels. The effect of noise uncertainty on the performance is discussed. Simulation results show that the logarithmic detector performs better than the FLOM and Cauchy detectors in very impulsive noise. In addition, the logarithmic detector is a nonparametric method and avoids estimating the parameter of the noise distribution, which makes the logarithmic detector easier to implement than the FLOM detector.

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“…The performance of energy detection under Log Normal approximation of noise uncertainty is analyzed in [16]. The authors of [17] assume a uniform distribution for noise uncertainty and analyzed the performance of energy detection. A generalized energy detector is analyzed under noise uncertainty in [18] and observed that the traditional energy detector (TED) is best suited for spectrum sensing under noise uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sensing in Cognitive Radios Under Noise Uncertainty: Decision Making Using Game Theory

Muthumeenakshi¹,

Radha²

2017

International Journal on Smart Sensing and Intelligent Systems

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Abstract-Energy detection is best suited for the detection of licensed users when prior knowledge about them is unavailable. However, the presence of noise uncertainty refrains the use of energy detection for spectrum sensing. In this paper, we propose a refined energy detection (RED) which used dual threshold in the presence of noise uncertainty, and combine the concepts from game theory to achieve further performance improvements. The secondary user payoff is defined based on the primary user activity and the strategy adopted by the secondary user. The pure strategy Nash equilibrium and the best response for the mixed strategy Nash equilibrium are analyzed for all the possible strategies adopted by the secondary user. Simulations results show the effectiveness of the proposed algorithm in terms of greater secondary user payoff and robustness against noise uncertainty.

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Performance of energy detector in the presence of noise uncertainty in cognitive radio networks

Cited by 13 publications

References 18 publications

SNR wall for generalized energy detection under noise uncertainty in cognitive radio

SNR wall for generalized energy detection under noise uncertainty in cognitive radio

Nonparametric Blind Signal Detection Based on Logarithmic Moments in Very Impulsive Noise

Spectrum Sensing in Cognitive Radios Under Noise Uncertainty: Decision Making Using Game Theory

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