Energy detector based spectrum sensing by adaptive threshold for low SNR in CR networks

2015 ◽  
Author(s):  
Manobendu Sarker
Keyword(s):  
Spectrum Sensing ◽  
Adaptive Threshold ◽  
Energy Detector ◽  
Low Snr

An Adaptive Spectrum-Sensing Algorithm for Cognitive Radio Networks based on the Sample Covariance Matrix

2017 ◽  
Vol 67 (3) ◽  
pp. 325 ◽  
Author(s):  
Chhagan Charan ◽  
Rajoo Pandey
Keyword(s):  
Covariance Matrix ◽  
Spectrum Sensing ◽  
Primary User ◽  
Adaptive Threshold ◽  
Probability Of Detection ◽  
Superior Performance ◽  
Probability Of Error ◽  
Noise Uncertainty ◽  
Low Snr ◽  
Sample Covariance

<p>A novel adaptive threshold spectrum sensing technique based on the covariance matrix of received signal samples is proposed. The adaptive threshold in terms of signal to noise ratio (SNR) and spectrum utilisation ratio of primary user is derived. It considers both the probability of detection and the probability false alarm to minimise the overall decision error probability. The energy- based spectrum sensing scheme shows high vulnerability under noise uncertainty and low SNR. The existing covariance-based spectrum sensing technique overcomes the noise uncertainty problem but its performance deteriorates under low SNR. The proposed covariance-based scheme effectively addresses the low SNR problem. The superior performance of this scheme over the existing covariance-based detection method is confirmed by the simulation results in terms of probability of detection, probability of error, and requirement of samples for reliable detection of spectrum.</p>

scholarly journals Cooperative Spectrum Sensing Over Imperfect Reporting Channel using an Improved Energy Detector in Multiple Antenna Based Cognitive Radio

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2978-2981
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Energy Detector ◽  
Multiple Antenna ◽  
Low Snr ◽  
Improved Energy Detector ◽  
Energy Location ◽  
Reporting Channel

The presentation research of agreeable variety detecting with the help of a complicated energy finder is displayed in this paper. Subjective radios contain of severa reception apparatuses. each highbrow radio distinguishes essential customer sign with improved energy location, i.E., control 'p' of the adequacy of important examples. each CR takes its very very own selection and advances to the aggregate focus. The combination hobby melds all of the stop, and sincerely the final end of the nearness or nonattendance of the vital purchaser is executed. The articulations for the synthetic alert opportunity and the likelihood of left out region were determined, and the complete mistake price is determined. Streamlining of the all out amount of CR, strength discovery control 'p' and the quantity of reception apparatuses at every CR is completed with the help of diagram and articulations thru diminishing the all out blunder fee. With the assist of numerous reception apparatuses with low SNR amongst PU-CR joins, it is validated that we can accomplish a base blunder price

scholarly journals Comparison of Single User with Multi User Cooperative Spectrum Sensing for Energy Detector at Low SNR Wall

2021 ◽  
Vol 2070 (1) ◽  
pp. 012083
Author(s):  
Kavita Bani ◽  
Vaishali Kulkarni
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Roc Curve ◽  
Cooperative Spectrum Sensing ◽  
Probability Of Detection ◽  
Energy Detector ◽  
Low Snr ◽  
Single User ◽  
Increasing Demand ◽  
Region Of Convergence

Abstract With rapidly increasing demand in wireless communication, available licensed spectrum resources should be utilized efficiently and actively. Cognitive radio is a device which learns from surrounding environment and transmit its signal when license spectrum is unutilized. Spectrum sensing is the need for Cognitive radio. In this paper, Energy detector is implemented though MATLAB software for single and multiusers. Region of Convergence (ROC) curve is plotted for both normal ED and Cooperative spectrum sensing ED. Results show while increasing number of samples from 1k to 100k, probability of detection is also achieved 0.9 maximum. Increasing SNR from -20dB, -15dB to -10 dB, probability of detection is improved in ROC curve. Also cooperative spectrum sensing with OR rule gives good probability of detection 0.9 to 1.

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.

Two-Stage Spectrum Sensing for Cognitive Radio Using Eigenvalues Detection

2020 ◽  
Vol 12 (4) ◽  
pp. 18-36
Author(s):  
Faten Mashta ◽  
Wissam Altabban ◽  
Mohieddin Wainakh
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Primary User ◽  
Detection Performance ◽  
Probability Of Detection ◽  
Energy Detector ◽  
Detection Methods ◽  
Two Stage ◽  
Low Snr ◽  
Good Detection

Spectrum sensing in cognitive radio has difficult and complex requirements, requiring speed and good detection performance at low SNR ratios. As suggested in IEEE 802.22, the primary user signal needs to be detected at SNR = -21dB with a probability of detection exceeds 0.9. Conventional spectrum sensing methods such as the energy detector, which is characterized by simplicity with good detection performance at high SNR values, are ineffective at low SNR values, whereas eigenvalues detection methods have good detection performance at low SNR ratios, but they have high complexity. In this paper, the authors investigate the process of spectrum sensing in two stages: in the first stage (coarse sensing), the energy detector is adopted, while in the second stage (fine sensing), eigenvalues detection methods are used. This method improves performance in terms of probability of detection and computational complexity, as the authors compared the performance of two-stage sensing scheme with ones where only energy detection or eigenvalues detection is performed.

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