scholarly journals Spectrum Sensing using AMC and TFT

2019 ◽  
Vol 9 (2) ◽  
pp. 898-902
Keyword(s):  
Decision Making ◽  
Spectrum Sensing ◽  
Fading Channel ◽  
Matched Filter ◽  
Energy Detection ◽  
Primary User ◽  
Modulation Classification ◽  
Time Frequency ◽  
Automatic Modulation Classification ◽  
Channel Conditions

Spectrum Sensing (SS) is a foremost step to implement next generation Cognitive Radio (CR) systems. The primary goal of a SS technique is to examine whether the Primary User (PU) is in active state or not by analyzing the surrounding radio environment. Traditional methods such as energy detection and Matched Filter Detection (MFD) schemes along with decision making circuits are generally used in SS. However, these techniques are developed under cooperative scenarios and they are used to sense single PU (narrowband sensing). In non-cooperative scenarios and fading channel conditions, traditional techniques produce higher false alarm. If Secondary User (SU) is occupied in the channel then SS task is more difficult. In order to overcome these limitations, a narrowband and wideband SS algorithm using Automatic Modulation Classification (AMC) and Time-Frequency Transform (TFT) is developed in this paper. The performance analysis of proposed AMC and TFT based SS technique under various channel conditions which is also described in this paper.

scholarly journals Performance Analysis of Automatic Modulation Classification using Time Frequency Transforms under Non-Ideal Channel Conditions

2019 ◽  
Vol 8 (12) ◽  
pp. 1685-1691
Keyword(s):  
Performance Analysis ◽  
Fading Channels ◽  
Classification Accuracy ◽  
Modulation Classification ◽  
Time Frequency ◽  
Automatic Modulation Classification ◽  
Performance Metric ◽  
S Transform ◽  
Channel Conditions

Classification of different analog and digital modulation classes using Time-Frequency Transforms (TFTs) through MST and MFSWT under ideal channel conditions is presented in this paper. It also deals with performance analysis of proposed Modified S- Transform (MST) and Modified Frequency Slice Wavelet Transform (MFSWT) based Automatic Modulation Classification (AMC) methods under different channel conditions such as Gaussian and fading channels. The performance of the proposed TFT based AMC methods under AWGN (with SNR values varied from -10 dB to 20 dB) and fading channels is examined through simulation. Moreover, the performance of the proposed TFT based AMC is compared with that of the existing techniques in terms of performance metric namely classification accuracy which is also discussed in this paper.

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.

Energy Detection Spectrum Sensing with Discontinuous Primary User Signal

2009 ◽  
Author(s):  
F. Penna ◽  
C. Pastrone ◽  
M. A. Spirito ◽  
R. Garello
Keyword(s):  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User

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 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.

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.

Matched filter based spectrum sensing when primary user has multiple power levels

2015 ◽  
Vol 12 (2) ◽  
pp. 21-31 ◽  
Author(s):  
Xinzhi Zhang ◽  
Feifei Gao ◽  
Rong Chai ◽  
Tao Jiang
Keyword(s):  
Spectrum Sensing ◽  
Matched Filter ◽  
Primary User ◽  
Multiple Power
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