Noise Uncertainty Study of the Low SNR Energy Detector in Cognitive Radio

2010 ◽  
pp. 248-255
Author(s):  
Guoqing Ji ◽  
Hongbo Zhu
Keyword(s):  
Cognitive Radio ◽  
Energy Detector ◽  
Noise Uncertainty ◽  
Low Snr

scholarly journals Simulation and Analysis of the OFDM Transceiver Based Commutation System

2020 ◽  
Vol 26 (12) ◽  
pp. 131-140
Author(s):  
Areej Munadel ◽  
Ekhlas Kadhum Hamza
Keyword(s):  
Cognitive Radio ◽  
Signal To Noise Ratio ◽  
Radio Spectrum ◽  
Cyclic Prefix ◽  
Probability Of Detection ◽  
Energy Detector ◽  
Signal To Noise ◽  
Wireless Applications ◽  
Low Snr

As a result of the increase in wireless applications, this led to a spectrum problem, which was often a significant restriction. However, a wide bandwidth (more than two-thirds of the available) remains wasted due to inappropriate usage. As a consequence, the quality of the service of the system was impacted. This problem was resolved by using cognitive radio that provides opportunistic sharing or utilization of the spectrum. This paper analyzes the performance of the cognitive radio spectrum sensing algorithm for the energy detector, which implemented by using a MATLAB Mfile version (2018b). The signal to noise ratio SNR vs. Pd probability of detection for OFDM and SNR vs. BER with CP cyclic prefix with energy detector is calculated and analyzed. In this paper, the proposed work produces more accurate results compared to the existing techniques at low SNR values.

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 Performance Analysis of Spectrum Sensing in Cognitive Radio under Low SNR and Noise Floor

2019 ◽  
Vol 9 (2) ◽  
pp. 2655-2661
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Kernel Function ◽  
Feature Space ◽  
Energy Detection ◽  
Spectrum Efficiency ◽  
Dynamic Threshold ◽  
Noise Uncertainty ◽  
Low Snr ◽  
Space Data

Cognitive radio (CR) is a new technology that is proposed to improve spectrum efficiency by allowing unlicensed secondary users to access the licensed frequency bands without interfering with the licensed primary users. As there are several methods available for spectrum sensing, the energy detection (ED) is more popular due to its simple implementation. However, ED is more vulnerable to the noise uncertainty so for that reason, we present a robust detector using signal to noise ratio (SNR) with dynamic threshold energy detection technique is combined with the kernel principal component analysis (KPCA) in Cognitive Radio Networks (CRN). The primary purpose of kernel function is to ensure that its dependency relies on inner-product of data without the feature space data requirement. In this paper, with the aid of kernel function the spectrum sensing with the leading eigenvector approach is modified to a feature space of higher dimensionality.By introducing of efficient detection system with dynamic threshold facility helps the better detection levels even low SNR values with quite a lot of noise uncertainty levels. The simulation results of the proposed system reveal that KPCA outperforms with that of traditional PCA in terms of false alarm rate, detector performance when tested under various uncertainties for orthogonal frequency division multiplexing signal.

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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