scholarly journals Analysis of radio frequency spectrum usage using cognitive radio

2020 ◽  
Vol 1 ◽  
pp. 1-8
Author(s):  
Munirah Shuaibu-Sadiq ◽  
F. I. Anyasi
Keyword(s):  
Cognitive Radio ◽  
Radio Frequency ◽  
Software Defined Radio ◽  
Probability Of Detection ◽  
Noise Power ◽  
Benin City ◽  
Probability Of False Alarm ◽  
Simulink Model ◽  
Radio Frequency Spectrum ◽  
Working Together

This paper presents the analysis of radio frequency (RF) spectrum usage using cognitive radio. The aim was to determine the unused spectrum frequency bands for efficiently utilization. A program was written to reuse a range of vacant frequency with different model element working together to produce a spectrum sensing in MATLAB/Simulink environment. The developed Simulink model was interfaced with a register transfer level - software defined radio, which measures the estimated noise power of the received signal over a given time and bandwidth. The threshold estimation performed generates a 1\0 output for decision and prediction. It was observed that some spectrum, identified as vacant frequency, were underutilized in FM station in Benin City. The result showed that when cognitive radio displays “1” output, which is decision H1, the channel is occupied and cannot be used by the cognitive radio for communication. Conversely, when “0” output (decision H0) is displayed, the channel is unoccupied. There is a gradual decrease in the probability of detection (Pd), when the probability of false alarm (Pfa) is increased from 1% to 5%. In the presence of higher Pfa, the Pd of the receiver maintains a high stability. Hence, the analysis finds the spectrum hole and identifies how it can be reused

scholarly journals IN SEARCH OF SUSTAINABLE BUSINESS MODELS FOR COGNITIVE RADIO EVOLUTION

2012 ◽  
Vol 18 (2) ◽  
pp. 230-247 ◽  
Author(s):  
Vladislav V. Fomin ◽  
Artūras Medeišis ◽  
Daiva Vitkutė-Adžgauskienė
Keyword(s):  
Cognitive Radio ◽  
Mobile Communications ◽  
Software Defined Radio ◽  
Business Models ◽  
Spectrum Access ◽  
New Paradigm ◽  
Sustainable Business ◽  
Radio Communications ◽  
Telecommunications Infrastructure ◽  
Radio Frequency Spectrum

In this paper we examine the emerging industry of Cognitive Radio/Software Defined Radio (CR/SDR), a sector which in some ways seconds the industry structure of the cellular mobile communications, while bearing distinctive characteristics. Any radio telecommunications infrastructure depends on scarce resources – radio frequency spectrum – that require policy decisions for allocation to specific countries and services. CR/SDR may constitute a new paradigm in radio communications as it may completely or partially eliminate the role of the regulator in minutiae of spectrum access authorization. In this paper, we review scarce literature on CR/SDR to analyze the relationships between political, technological and economic factors in order to identify drivers and barriers to the emergence of new techno-economic paradigm of CR/SDR. Our discussion of business opportunities for CR/SDR includes analysis of applicable spectrum access policies and identification of those of them, which would be most fertile for the development of future CR/SDR business.

scholarly journals Optimization of spectrum sensing in cognitive radio using genetic algorithm

2012 ◽  
Vol 25 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Rashmi Deka ◽  
Soma Chakraborty ◽  
Sekhar Roy
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Rapid Development ◽  
Probability Of Detection ◽  
Radio System ◽  
Probability Of False Alarm ◽  
Space Allocation ◽  
Wireless Environment ◽  
Better Than

Spectrum availability is becoming scarce due to the rise of number of users and rapid development in wireless environment. Cognitive radio (CR) is an intelligent radio system which uses its in-built technology to use the vacant spectrum holes for the use of another service provider. In this paper, genetic algorithm (GA) is used for the best possible space allocation to cognitive radio in the spectrum available. For spectrum reuse, two criteria have to be fulfilled - 1) probability of detection has to be maximized, and 2) probability of false alarm should be minimized. It is found that with the help of genetic algorithm the optimized result is better than without using genetic algorithm. It is necessary that the secondary user should vacate the spectrum in use when licensed users are demanding and detecting the primary users accurately by the cognitive radio. Here, bit error rate (BER) is minimized for better spectrum sensing purpose using GA.

An Algorithm Based on Double-Threshold Energy Detection in Cognitive Radio

2014 ◽  
Vol 643 ◽  
pp. 105-110
Author(s):  
Yuan Li ◽  
Jia Yin Chen ◽  
Xiao Feng Liu ◽  
Ming Chuan Yang
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Mathematical Proof ◽  
Threshold Energy ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Double Threshold

Aiming at the situation where the double-threshold detection has been widely used without complete mathematical proof and condition of application, this paper proves its correctness under the circumstance of spectrum sensing, and circulates the condition where this method can work. The proof and simulation show that, comparing with traditional energy detection, this method can increase the probability of detection by 27% to 42% at most when the SNR is between-15dB and-2dB, while the probability of false alarm is increased by less than 2%.

Iterative Optimization of Energy Detector Sensing Time and Periodic Sensing Interval in Cognitive Radio Networks

2013 ◽  
pp. 53-69
Author(s):  
Mohamed Hamid ◽  
Niclas Björsell ◽  
Abbas Mohammed
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Performance Metrics ◽  
False Alarm Probability ◽  
Transmission Efficiency ◽  
Radio Networks ◽  
Probability Of Detection ◽  
Convergence Criterion ◽  
Probability Of False Alarm ◽  
Sensing Time

In this chapter the authors propose a new approach for optimizing the sensing time and periodic sensing interval for energy detectors in cognitive radio networks. The optimization of the sensing time depends on maximizing the summation of the probability of right detection and transmission efficiency, while the optimization of periodic sensing interval is subject to maximizing the summation of transmission efficiency and captured opportunities. Since the optimum sensing time and periodic sensing interval are dependent on each other, an iterative approach to optimize them simultaneously is proposed and a convergence criterion is devised. In addition, the probability of detection, probability of false alarm, probability of right detection, transmission efficiency, and captured opportunities are taken as performance metrics for the detector and evaluated for various values of channel utilization factors and signal-to-noise ratios.

Adaptive Two-Stage Sensing Based on Energy Detection and Cyclostationary Feature Detection for Cognitive Radio Systems

2013 ◽  
Vol 411-414 ◽  
pp. 1521-1528 ◽  
Author(s):  
Yu Yang ◽  
Yan Li Ji ◽  
Han Hui Li ◽  
Du Lei ◽  
Meng Rui
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Two Stage ◽  
Probability Of False Alarm ◽  
Detection Model ◽  
Radio Systems ◽  
Cyclostationary Feature Detection

In this paper, we investigate the features of energy detection and cyclostationary feature detection for spectrum sensing. In order to combine their advantages, we propose an adaptive two-stage sensing scheme which performs spectrum sensing using an energy detector first in cognitive radio networks. Then in the second stage, this scheme decides whether or not to implement cyclostationary feature detection based on the sensing results of the first stage. On the premise of meeting a given constraint on the probability of false alarm, the goal of our proposed scheme is to optimize the probability of detection and sensing speed at the same time. In order to obtain the optimal detection thresholds, we can formulate the detection model as a nonlinear optimization problem. Furthermore, the simulation results show that the proposed scheme improves the performance of spectrum sensing compared with the ones where only energy detection or cyclostationary feature detection is performed.

A hybrid model for energy efficient spectrum sensing in cognitive radio

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahua Bhowmik ◽  
P. Malathi P. Malathi
Keyword(s):  
Cognitive Radio ◽  
Prediction Model ◽  
Spectrum Sensing ◽  
Hybrid Model ◽  
Energy Efficient ◽  
Probability Of Detection ◽  
Content Type ◽  
Hybrid Prediction ◽  
Probability Of False Alarm ◽  
Sensing Time

Purpose Cognitive radio (CR) plays a very important role in enabling spectral efficiency in wireless communication networks, where the secondary user (SU) allows the licensed primary users (PUs). The purpose of this paper is to develop a prediction model for spectrum sensing in CR. Design/methodology/approach This paper proposes a hybrid prediction model, called krill-herd whale optimization-based actor critic neural network and hidden Markov model (KHWO-ACNN-HMM). The spectral bands are determined optimally using the proposed hybrid prediction model for allocating the spectrum bands to the PUs. For better sensing, the eigenvalue based on cooperative sensing used in CR. Finally, a hybrid model is designed by hybridizing KHWO-ACNN and HMM to enhance the accuracy of sensing. The predicted results of KHWO-ACNN and HMM are combined by a fusion model, for which a weighted entropy fusion is employed to determine the free spectrum available in CRs. Findings The performance of the prediction model is evaluated based on metrics, such as probability of detection, probability of false alarm, throughput and sensing time. The proposed spectrum sensing method achieves maximum probability of detection of 0.9696, minimum probability of false alarm rate as 0.78, minimum throughput of 0.0303 and the maximum sensing time of 650.08 s. Research implications The proposed method is useful in various applications, including authentication applications, wireless medical networks and so on. Originality/value A hybrid prediction model is introduced for energy efficient spectrum sensing in CR and the performance of the proposed model is evaluated with the existing models. The proposed hybrid model outperformed the other techniques.

Agility Improvement in Cognitive Radio under Bluetooth Paradigm Using Ant Colony Metaphor

2012 ◽  
pp. 373-390
Author(s):  
Ashraf Darwish
Keyword(s):  
Cognitive Radio ◽  
Wireless Communication ◽  
Radio Frequency ◽  
Frequency Spectrum ◽  
User Behavior ◽  
Ant Colony ◽  
Network State ◽  
Radio Frequency Spectrum ◽  
The Relationship ◽  
Wireless Node

Cognitive radio is a paradigm for wireless communication in which either network or wireless node itself changes particular transmission or reception parameters to execute its tasks efficiently. This parameter alteration is based on observations of several factors from external and internal cognitive radio environment, such as radio frequency spectrum, user behavior, and network state. The chapter presents the relationship between cognitive radio and ant colony. The bio-inspired cognitive radio algorithm is presented.

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