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 Designing a Real-time Swept Spectrum Analyser with USRP B210

2021 ◽  
Vol 5 (2) ◽  
pp. 329-339
Author(s):  
N. Bello ◽  
K.O. Ogbeide
Keyword(s):  
Cognitive Radio ◽  
Real Time ◽  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Wide Band ◽  
Energy Detection ◽  
Promising Technique ◽  
Basic Functions ◽  
High Flexibility ◽  
Very High

Cognitive radio has received considerable amount of attention as a promising technique to provide dynamic spectrum allocation. Spectrum sensing is one of the basic functions in the cognitive radio and is crucial to all other functions. Software- defined radios (SDRs) are considered due to its very high flexibility and have become a common platform for CR implementation replacing expensive spectrum analysers. The most popular among various SDR platforms is the universal software-defined radio peripheral (USRP). This paper presents a real-time swept spectrum sensing solution based on USRP B210. It also presents a detailed explanation of the concept of energy detection and the methodology for wide-band sensing. Finally, the performance of the proposed sensing solution is analysed through FFT graphs and spectrogram plot taken for 8 hours. The results showed that the proposed sensing solution was capable of achieving high resolution in the frequency domain of the wide band measured which implies that wide bands with heterogenous signals like the ISM band can be accurately resolved and analysed.

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.

Implementation of Multi-Hop Cognitive Radio Testbed using Raspberry Pi and USRP

2017 ◽  
Vol 9 (4) ◽  
pp. 37-48 ◽  
Author(s):  
Hyun Jae Park ◽  
Gyu-min Lee ◽  
Seung-Hun Shin ◽  
Byeong-hee Roh ◽  
Ji Myeong Oh
Keyword(s):  
Cognitive Radio ◽  
Wireless Communication ◽  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Software Radio ◽  
Energy Detection ◽  
Raspberry Pi ◽  
Public Attention ◽  
Test Environment ◽  
Cr System

The increased usage of wireless communication has created a wireless frequency shortage problem. Cognitive Radio (CR) has attracted public attention, as one of the solutions that can resolve this issue. In this paper, the authors built an actual CR system testbed using the SDR (Software Defined Radio) platform, USRP (Universal Software Radio Peripheral) board, the SDR development toolkit, GNU Radio, and Raspberry Pi3, which is a single board computer. They configured Secondary User (SU)s with Raspberry Pi3 for straightforward and portable test environment. The authors' testbed performs spectrum sensing based on energy detection and determines whether the channel is occupied or not. Experimental results not only show performance but also provide their testbed that works well in multi-hop environments.

Implementation and Performance Analysis of Cognitive Radio with Frequency Updating Algorithm on Software-defined Radio Platform

2020 ◽  
Vol 14 ◽  
Author(s):  
Jaskaran Singh Phull ◽  
Narwant Singh Grewal ◽  
Simar Preet Singh ◽  
Asha Rani
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Bit Error Rate ◽  
Error Rate ◽  
Gaussian Noise ◽  
Software Defined Radio ◽  
Transmission Rate ◽  
Primary User ◽  
Secondary User ◽  
Gnu Radio

Wireless communication is being used in all communication standards. However, with each passing day, the bandwidth scarcity has become a significant concern for the upcoming wireless technologies. In order to address this concern, various techniques based on artificial intelligence have been designed. The basic intelligent radio called cognitive radio, has been devised. It works on the basic principle of spectrum sensing and detecting the free frequency for transmission of the secondary user, who is an unlicensed user. This work proposes an efficient technique that has been developed to design cognitive radio based on SDR platform. The frequency updating algorithm has been added for the performance assessment of the proposed technique. The analysis posits that for every 10dB rise in Gaussian Noise, the bit error rate of secondary transmitter and spectrum sensor, cause an increment of 19.59% and 29.39% respectively. It has been found that spectrum sensor is more prone to noise and that the Gaussian noise degrades the performance of the system. Therefore, it is pertinent that the spectrum sensor should be programmed carefully. This analysis, shows that the best range of spectrum sensor under Gaussian noise is 0 to 0.1dB. and the bit error rate is within this specified range. Background: Used the GNU radio companion software on software defined radio platform. Objective: To design the primary user and secondary user using GNU radio and to design an algorithm to update the frequency. Methods: Designing both the transmitter and receiver in different laptops using GRC. Python code for updating algorithm is written at the back end. Results: Performance is increased in making the intelligent in bit error rate as well as the transmission rate. Conclusion: Various parameters measured for cognitive radio which makes it more efficient in spectrum sensing.

scholarly journals A Design of Anti-jamming Method Based on Spectrum Sensing and GNSS Software Defined Radio

2019 ◽  
Vol 94 ◽  
pp. 03004
Author(s):  
Kwi Woo Park ◽  
Min Joon Lee ◽  
Chansik Park
Keyword(s):  
Cognitive Radio ◽  
Real Time ◽  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Software Radio ◽  
Energy Detector ◽  
Center Frequency ◽  
Test Scenario ◽  
New Approach ◽  
Noise Ratio

This paper presents result of new approach for anti-jamming using a method based on cognitive radio. To detect and get center frequency and bandwidth of jamming, a spectrum sensing based on multi-channel energy detector is implemented on the SDR. The SDR and a universal software radio peripheral is used to support real-time channel reconfiguration. And detected center frequency and bandwidth is used to select LO frequency to avoid jamming and receive GNSS signal. Then the receiver is reconfigured by the selected LO frequency. To verify the feasibility of the proposed anti-jamming process, position, carrier to noise ratio of each channel are measured using a test scenario that is consist of GPS and Beidou with a CW jamming. As a results, by switching of LO frequency, GNSS signal that is not affected by jamming can be received with the same performance as non-jamming.

scholarly journals IMPROVEMENT OF ENERGY CONSUMPTION IN SPECTRUM SENSING COGNITIVE RADIO NETWORKS USING AN EFFICIENT TWO STAGE SENSING METHOD

2017 ◽  
Vol 57 (4) ◽  
pp. 235 ◽  
Author(s):  
Hikmat Najem Abdullah ◽  
Hadeel Sami Abed
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Fading Channels ◽  
Spectrum Sensing ◽  
Minimum Energy ◽  
Energy Detection ◽  
Primary User ◽  
Low Snr ◽  
Local Decision ◽  
Two Stages

Cognitive radio (CR) is a wireless technology developed to improve the usage in the spectrum frequency. Energy consumption is considered as a big problem in this technology, especially during a spectrum sensing. In this paper, we propose an algorithm to improve the energy consumption during the spectrum sensing. The theoretical analysis to calculate the amount of energy consumption, using the proposed method during sensing stage as well as the transmission stage during transmitting a local decision to the fusion center FC, are derived. The proposed algorithm is using energy detection technique to detect the presence or absence of the primary user (PU). The proposed algorithm consists of two stages: the coarse sensing stage and fine sensing stage. In the coarse sensing stage, all the channels in the band are sensed shortly and the channel that have maximum (or minimum) energy is identified to make a dense fine sensing for confirming the presence of the PU signal (or hole). The performance of the proposed algorithm is evaluated in two scenarios: non-cooperative, and cooperative in both the AWGN and Rayleigh fading channels. The simulation results show that the proposed method improves the energy consumption by about 40% at a low SNR values, when compared with the traditional methods based on a single sensing stage and more advanced method based on censoring and sequential censoring algorithms.

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.

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.

Sign in / Sign up

Export Citation Format

Share Document