An Overview of the Different Principal Spectrum Sensing Techniques in Cognitive Radio Systems

2020 ◽  
Vol 12 (3) ◽  
pp. 342-347
Author(s):  
Asmaa Maali ◽  
Hayat Semlali ◽  
Sara Laafar ◽  
Najib Boumaaz ◽  
Abdallah Soulmani
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Matched Filter ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Primary User ◽  
Operational Characteristic ◽  
Main Function ◽  
Maximum Eigenvalue ◽  
Smoothing Factor

Cognitive radio is a technology proposed to increase the effective use of the spectrum. This can be done through the main function of cognitive radio technology, which is the spectrum sensing. In our work, we propose an analysis of the following spectrum sensing techniques: the matched filter detector, the cyclostationary feature detector, the energy detector and the maximum eigenvalue detector. More attention is given to blind sensing techniques that they do not need any knowledge of the primary user signal characteristics, namely the energy detection and maximum eigenvalue detection. These methods are evaluated in terms of Receiver Operational Characteristic curves and detection probability for various values of Signal to Noise Ratio based on Monte Carlo simulations, using MATLAB. As a result of this study, we found that the energy detection offers a good performance only for high SNR. Furthermore, with the maximum eigenvalue detector, the noise uncertainty problem encountered by the energy detection is solved when the value of the smoothing factor L ≥ 8 and. Finally, a summary of the comparative analysis is presented.

An Integrated Parallel Multistage Spectrum Sensing for Cognitive Radio

2021 ◽  
Vol 12 (2) ◽  
pp. 1-20
Author(s):  
Faten Mashta ◽  
Mohieddin Wainakh ◽  
Wissam Altabban
Keyword(s):  
Cognitive Radio ◽  
Computational Complexity ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Maximum Eigenvalue ◽  
Two Stage ◽  
Smoothing Factor ◽  
Low Snr ◽  
Simulation Results ◽  
Good Detection

Spectrum sensing for cognitive radio requires speed and good detection performance at very low SNR ratios. There is no single-stage spectrum sensing technique that is perfect enough to be implemented in practical cognitive radio. In this paper, the authors propose a new parallel fully blind multistage detector. They assume the appropriate stage based on the estimated SNR values that are achieved from the SNR estimator. Energy detection is used in first stage for its simplicity and sensing accuracy at high SNR. For low SNRs, they adopt the maximum eigenvalues detector with different smoothing factor in higher stages. The sensing accuracy for the maximum eigenvalue detector technique improves with higher value of the smoothing factor. However, the computational complexity will increase significantly. They analyze the performance of two cases of the proposed detector: two-stage and three-stage schemes. The simulation results show that the proposed detector improves spectrum sensing in terms of accuracy and speed.

scholarly journals DWT Based Energy Detection Spectrum Sensing Method for Cognitive Radio System

2020 ◽  
Vol 3 (3) ◽  
pp. 1-11
Author(s):  
Muntaser S. Falih ◽  
Hikmat N. Abdullah
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Primary User ◽  
Radio System ◽  
Processed Sample ◽  
Simulation Results ◽  
Sensing Time

In this paper a new blind energy detection spectrum-sensing method based on Discreet Wavelet Transform (DWT) is proposed. The method utilizes the DWT sub-band to collects the received energy. The proposed method recognizes the Primary User (PU) signal from noise only signal using the differences in the collected energy in first and last sub-bands of one level DWT. The simulation results show that the proposed method achieves improved detection probability especially at low Signal to Noise Ratio (SNR) compared to Conventional Energy Detector (CED). The results also show that the proposed method has shorter sensing time and less Energy Consumption (EC) compared to CED due to using small number of processed sample. Therefore, this method is suitable for Cognitive Radio (CR) applications where only limited energy like device battery is available.

scholarly journals Spectrum Sensing in Cognitive Radio using Frequency Domain

2019 ◽  
Vol 9 (2) ◽  
pp. 3475-3477
Keyword(s):  
Cognitive Radio ◽  
Frequency Domain ◽  
Spectrum Sensing ◽  
Bandwidth Allocation ◽  
Dynamic Spectrum Access ◽  
Signal To Noise Ratio ◽  
Wide Band ◽  
Energy Detection ◽  
Secondary Users ◽  
Sensing Applications

An efficient bandwidth allocation and dynamic bandwidth access away from its previous limits is referred as cognitive radio (CR).The limited spectrum with inefficient usage requires the advances of dynamic spectrum access approach, where the secondary users are authorized to utilize the unused temporary licensed spectrum. For this reason it is essential to analyze the absence/presence of primary users for spectrum usage. So spectrum sensing is the main requirement and developed to sense the absence/ presence of a licensed user. This paper shows the design model of energy detection based spectrum sensing in frequency domain utilizing Binary Symmetric Channel (BSC) ,Additive white real Gaussian channel (AWGN), Rayleigh fading channel users for 16-Quadrature Amplitude Modulation(QAM) which is utilized for the wide band sensing applications at low Signal to noise Ratio(SNR) level to reduce the false error identification. The spectrum sensing techniques has least computational complexity. Simulink model for the energy detection based spectrum sensing using frequency domain in MATLAB 2014a.

scholarly journals Spectrum sensing based on energy of unknown deterministic signals over fading channels

2014 ◽  
Vol 17 (1) ◽  
pp. 17-31
Author(s):  
Tu Thanh Nguyen ◽  
Khoa Le Dang ◽  
Thu Thi Hong Nguyen ◽  
Phuong Huu Nguyen
Keyword(s):  
Cognitive Radio ◽  
Fading Channels ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Radio Network ◽  
Essential Components ◽  
Spectrum Hole ◽  
The Impact

In cognitive radio network, how to minimize the impact of secondary user on primary user’s signal plays a very important and complex role. Therefore, spectrum sensing is one of the most essential components of cognitive radio. Therefore, the effect of spectrum sensing algorithms plays a key role to the system’s performance. In this paper, we concentrate on spectrum sensing algorithms in order to find out spectrum hole or while hole for reusing it. Specifically, we will highlight the energy detector algorithm of unknown deterministic signals over fading channels. The numerical results match well with theoretical analysis. The system’s performance of energy detection in AWGN channel is acceptable in case of relatively low signal to noise ratio (SNR). However, the performance of system will be degraded remarkable over fading environments.

scholarly journals Analysis of the Impact of Detection Threshold Adjustments and Noise Uncertainty on Energy Detection Performance in MIMO-OFDM Cognitive Radio Systems

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 631
Author(s):  
Josip Lorincz ◽  
Ivana Ramljak ◽  
Dinko Begušić
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Method ◽  
Detection Threshold ◽  
Energy Detection ◽  
Primary User ◽  
Noise Uncertainty ◽  
Cognitive Radio Systems ◽  
Radio Systems ◽  
The Impact

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.

scholarly journals Cooperative Spectrum Sensing Based on Multi-Features Combination Network in Cognitive Radio Network

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 129
Author(s):  
Mingdong Xu ◽  
Zhendong Yin ◽  
Yanlong Zhao ◽  
Zhilu Wu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Primary User ◽  
Radio Spectrum ◽  
Local Information ◽  
Channel State ◽  
Single Node

cognitive radio, as a key technology to improve the utilization of radio spectrum, acquired much attention. Moreover, spectrum sensing has an irreplaceable position in the field of cognitive radio and was widely studied. The convolutional neural networks (CNNs) and the gate recurrent unit (GRU) are complementary in their modelling capabilities. In this paper, we introduce a CNN-GRU network to obtain the local information for single-node spectrum sensing, in which CNN is used to extract spatial feature and GRU is used to extract the temporal feature. Then, the combination network receives the features extracted by the CNN-GRU network to achieve multifeatures combination and obtains the final cooperation result. The cooperative spectrum sensing scheme based on Multifeatures Combination Network enhances the sensing reliability by fusing the local information from different sensing nodes. To accommodate the detection of multiple types of signals, we generated 8 kinds of modulation types to train the model. Theoretical analysis and simulation results show that the cooperative spectrum sensing algorithm proposed in this paper improved detection performance with no prior knowledge about the information of primary user or channel state. Our proposed method achieved competitive performance under the condition of large dynamic signal-to-noise ratio.

scholarly journals 5G cognitive radio system design with new algorithm asynchronous spectrum sensing

2021 ◽  
Vol 10 (4) ◽  
pp. 2046-2054
Author(s):  
Mohammed Mehdi Saleh ◽  
Ahmed A. Abbas ◽  
Ahmed Hammoodi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User ◽  
Spectrum Access ◽  
Secondary Users ◽  
Radio System ◽  
Wireless Applications ◽  
Fifth Generation ◽  
Time Required

Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.

Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection

2020 ◽  
Vol 11 (4) ◽  
pp. 41-59
Author(s):  
Faten Mashta ◽  
Mohieddin Wainakh ◽  
Wissam Altabban
Keyword(s):  
Cognitive Radio ◽  
Computational Complexity ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Smoothing Factor ◽  
Third Stage ◽  
Simulation Results ◽  
Good Detection ◽  
High Computational Complexity

Spectrum sensing in cognitive radio has difficult and complex requirements such as requiring speed and sensing accuracy at very low SNRs. In this paper, the authors propose a novel fully blind sequential multistage spectrum sensing detector to overcome the limitations of single stage detector and make use of the advantages of each detector in each stage. In first stage, energy detection is used because of its simplicity. However, its performance decreases at low SNRs. In second and third stage, the maximum eigenvalues detector is adopted with different smoothing factor in each stage. Maximum eigenvalues detection technique provide good detection performance at low SNRs, but it requires a high computational complexity. In this technique, the probability of detection improves as the smoothing factor raises at the expense of increasing the computational complexity. The simulation results illustrate that the proposed detector has better sensing accuracy than the three individual detectors and a computational complexity lies in between the three individual complexities.

scholarly journals SDR Based Energy Detection Spectrum Sensing in Cognitive Radio for Real Time Video Transmission

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Rupali B. Patil ◽  
K. D. Kulat ◽  
A. S. Gandhi
Keyword(s):  
Cognitive Radio ◽  
Real Time ◽  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Video Transmission ◽  
Energy Detection ◽  
Primary User ◽  
Data Traffic ◽  
Real Time Transmission ◽  
Is Design

Cognitive radio is a budding approach which helps to address the imminent spectrum crisis by dynamic spectrum allocation and support the increased data traffic with an intelligent mechanism of Software Defined Radio (SDR). SDR avoid the frequent modifications in the hardware structure with the use of software defined protocols. The main novelty of the paper is an effective implementation of CR using energy based spectrum sensing method which is done on GNU radio for real time transmission of video as a primary user. From evaluation results, one can see that the proposed system can indicate the frequency band occupancy by setting the detection output. Detection output changes to one with start of video transmission. Motivation behind this work is design of a spectrum sensing method which is best suited for detection of white spaces during the transmission of video as a primary user on SDR platform.

scholarly journals A Classification of the Spectrum Sensing Techniques for Cognitive Radio

2019 ◽  
Vol 8 (4) ◽  
pp. 11586-11595
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Prior Information ◽  
Primary User ◽  
Probability Of Detection ◽  
Coherent Detection ◽  
Main Function ◽  
Advantages And Disadvantages ◽  
Wideband Spectrum Sensing

Cognitive radio is a solution to the problem of radio spectrum scarcity. It gives the opportunity to a secondary user to exploit the spectrum allocated toa primary user. The main function of cognitive radio is spectrum sensing whichhas gained new aspects in the last decades to determine opportunistic spectrum holes. There are many spectrumsensing methods proposed in the literature. The Performance of thesetechniques may vary in different situations; it can be described by probability of detection, probability of false alarm, and sensing time. It is therefore important to compare and indicate the best scheme for a specified scenario. In this paper, we propose a classification of the main approaches of single user spectrum sensing based on its synchronization requirement into two main categories: coherent detection and non-coherent detection. The coherent detection needs some or full prior information about the primary user signal for detecting it, where the non-coherent detection does not need any prior information about the primary user signal for detecting it. In addition, we highlight the advantages and disadvantages of narrowband and wideband spectrum sensing procedures along with the challenges involved in their implementation.Furthermore, we introduce the concept and basics of cooperative sensing and interference based sensing.This paper helps the designer to be familiar with all the techniques used to achieve spectrum sensing.

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