scholarly journals Adaptive threshold and optimal frame duration for multi-taper spectrum sensing in cognitive radio

ICT Express ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 31-36 ◽  
Author(s):  
Ahmed O. Abdul Salam ◽  
Ray E. Sheriff ◽  
Saleh R. Al-Araji ◽  
Kahtan Mezher ◽  
Qassim Nasir
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Adaptive Threshold ◽  
Frame Duration

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

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Muhammad Sajjad Khan ◽  
Muhammad Jibran ◽  
Insoo Koo ◽  
Su Min Kim ◽  
Junsu Kim
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Evidence Theory ◽  
Adaptive Threshold ◽  
Radio Networks ◽  
Maximal Ratio Combining ◽  
Fusion Center ◽  
Adaptive Approach

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.

scholarly journals An Effective Adaptive Threshold Based Compressive Spectrum Sensing in Cognitive Radio Networks

2021 ◽  
Vol 9 (1) ◽  
pp. 1220-1224
Author(s):  
S. Varalakshmi, K. Senthil Kumar, A. K. Gnanasekar, S. Sureshkrishna
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Sampling Rate ◽  
Adaptive Threshold ◽  
Radio Networks ◽  
Parametric Estimation ◽  
Noise Uncertainty ◽  
Low Snr ◽  
Wideband Spectrum Sensing

Spectrum sensing is playing a vital role in Cognitive Radio networks. Wideband spectrum sensing increases the speed of sensing but which in turn requires higher sampling rate and also increases the complexity of hardware and also power consumption. Compression based sensing reduces the sampling rate by using Sub-Nyquist sampling but the compression and the reconstruction problem exists. In compression based spectrum sensing, noise uncertainty is one of the major performance degradation factor. To reduce this degradation, compressive measurements based sensing with adaptive threshold is proposed. In this technique compressed signal is sensed without any reconstruction of the signal. When the nodes are mobile in the low SNR region, the noise uncertainty degrades the performance of spectrum sensing. To conquer this problem, noise variance is estimated using parametric estimation technique and the threshold is varied adaptively. In the low SNR region, this proposed technique reduces the effect of noise and improves the spectrum sensing performance.

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