An adaptive threshold method for energy based spectrum sensing in Cognitive Radio Networks

Muralidharan, Ashish; Venkateswaran, Prajwal; Ajay, S. G.; Prakash, D. Arun; Arora, Mohandeep; Kirthiga, S

doi:10.1109/iccicct.2015.7475239

Cited by 27 publications

(27 citation statements)

References 4 publications

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“…The ED is a simple and straightforward technique, because it does not require any previous information about the signal characteristics, and hence it is straightforward and easy to implement. The ED 5–18 is based on computing the energy of the samples and comparing it with a threshold. If the energy is higher than this threshold, the PU signal is present; otherwise, it is absent.…”

Section: Related Workmentioning

confidence: 99%

Adaptive two‐stage spectrum sensing model using energy detection and wavelet denoising for cognitive radio systems

Fawzi

El‐Shafai

Abd‐Elnaby

et al. 2020

Int J Communication

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This paper presents an efficient adaptive two-stage spectrum sensing model for the cognitive radio (CR) systems. The proposed model combines two wellknown techniques: energy detection (ED) and wavelet denoising (WD). The ED technique is employed to identify the existence of the primary user (PU) signal in the case of high signal-to-noise ratio (SNR) by comparing the received signal with a threshold. In the case of low SNR, the ED technique alone cannot be adopted for decision making about the status of the PU due to the noise impact on the received signals. Hence, the stage of WD is exploited prior to the ED for reducing the noise effect and detecting the PU signal in the presence of noise. The detection performance of the proposed model is compared with those of the ED alone and the previous related two-stage spectrum sensing methods. Simulation results show that the proposed model improves the false alarm rate compared to the ED alone by 36% and 6%, respectively, at low SNRs of −15 and −20 dB. Also, the proposed model yields the smallest detection time compared to the previous two-stage spectrum sensing methods. The proposed model can be used to minimize the probability of false alarm, achieve a better probability of detection, and improve the sensing process in CR systems.

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Section: Related Workmentioning

confidence: 99%

Adaptive two‐stage spectrum sensing model using energy detection and wavelet denoising for cognitive radio systems

Fawzi

El‐Shafai

Abd‐Elnaby

et al. 2020

Int J Communication

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“…In [23], an energy detector, using an adaptive dual threshold, is proposed for solving the detection problem. In [24], the authors proposed an adaptive threshold detection algorithm based on an image binarization technique.…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sensing in Cognitive Radio Networks: Threshold Value Optimization and Analysis

Koçkaya

Develı

2020

Preprint

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Cognitive radio is a technology developed for the effective use of radio spectrum sources. The spectrum sensing function plays a key role in the performance of cognitive radio networks. In this study, we propose an online learning algorithm for the energy detection scheme, which aims to maximizing spectrum detection performance. Optimal threshold value, which is critical for the determination of the absence or the presence of a licensed user, was mathematically expressed in accordance with the balance between probability of detection and probability of false alarm. Performance of the proposed algorithm was tested on non-fading and different fading channels for low signal-to-noise ratio (SNR) regime with noise uncertainty. In conclusion of the simulation studies, improvement in spectrum detection performance according to optimal threshold value selection was observed.

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“…CR is a vital technology to improve spectrum utilization. A major challenge in CR is spectrum sensing that identifies the presence of the licensed/primary user (LU) in the network and whenever the LU is detected, secondary user (SU) needs to vacate the channel [5].…”

Section: Introductionmentioning

confidence: 99%

A Double Adaptive Approach to Tackle Malicious Users in Cognitive Radio Networks

Khan

Jibran

Koo

et al. 2019

Wireless Communications and Mobile Computing

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Cognitive radio (CR) is being considered as a vital technology to provide solution to spectrum scarcity in next generation network, by efficiently utilizing the vacant spectrum of the licensed users. Cooperative spectrum sensing in cognitive radio network has a promising performance compared to the individual sensing. However, the existence of the malicious users’ attack highly degrades the performance of the cognitive radio networks by sending falsified data also known as spectrum sensing data falsification (SSDF) to the fusion center. In this paper, we propose a double adaptive thresholding technique in order to differentiate legitimate users from doubtful and malicious users. Prior to the double adaptive approach, the maximal ratio combining (MRC) scheme is utilized to assign weight to each user such that the legitimate users experience higher weights than the malicious users. Double adaptive threshold is applied to give a fair chance to the doubtful users to ensure their credibility. A doubtful user that fails the double adaptive threshold test is declared as a malicious user. The results of the legitimate users are combined at the fusion center by utilizing Dempster-Shafer (DS) evidence theory. Effectiveness of the proposed scheme is proved through simulations by comparing with the existing schemes.

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An adaptive threshold method for energy based spectrum sensing in Cognitive Radio Networks

Cited by 27 publications

References 4 publications

Adaptive two‐stage spectrum sensing model using energy detection and wavelet denoising for cognitive radio systems

Adaptive two‐stage spectrum sensing model using energy detection and wavelet denoising for cognitive radio systems

Spectrum Sensing in Cognitive Radio Networks: Threshold Value Optimization and Analysis

A Double Adaptive Approach to Tackle Malicious Users in Cognitive Radio Networks

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