scholarly journals Development and Demonstration of Graphical User Interface Spectrum Sensing Algorithm using some Wireless Systems in South Africa

2016 ◽  
Vol 2 (2) ◽  
Author(s):  
Jide Julius Popoola ◽  
Rex van Olst
Keyword(s):  
Cognitive Radio ◽  
User Interface ◽  
Spectrum Sensing ◽  
Graphical User Interface ◽  
Dynamic Spectrum Access ◽  
Cooperative Spectrum Sensing ◽  
Radio Spectrum ◽  
Spectrum Utilization ◽  
Application Program ◽  
Radio Technology

The wireless communication industry using radio spectrum is recently going through major innovations and advancements. With this transformation, the demand for and usage of radio spectrum has increased exponentially making radio spectrum indeed a scarce natural resource. In order to solve this problem, the possibility of opening up the unused portions of licensed spectrum by sharing using cognitive radio technology has been in the spotlight for maximizing radio spectrum utilization as well to as ensure sufficient radio spectrum availability for future wireless services and applications. With this objective in mind, this paper looks at the principles and technologies of cooperative spectrum sensing in cognitive radio environment in improving radio spectrum utilization. The paper provides a comprehensive review on spectrum sensing as a key functional requirement for cognitive radio technology by focusing on its application on dynamic spectrum access that enables unused portions of licensed spectrum to be used in an opportunistic manner as long as the operation of the unlicensed user will not affect that of the licensed user. In satisfying this dynamic spectrum access requirement, a friendly interactive graphical user interface (GUI) spectrum sensing application program was developed. The detail activities involve in the development of the application program, also known as spectrum sensing and detection algorithm (SSADA), was fully documented and presented in the paper. The developed graphical user interface application program after successfully developed was evaluated. The performance evaluations of developed graphical user interface sensing algorithm show that the algorithm performs favourably well. The program overall evaluation results provide bedrock information on how to improve cooperative spectrum sensing gain without incurring a cooperative overhead.

scholarly journals Cognitive Radio Spectrum Sensing Mechanisms in TV White Spaces: A Survey

2018 ◽  
Vol 8 (6) ◽  
pp. 3673-3680
Author(s):  
K. Kimani ◽  
M. Njiraine
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Limited Resource ◽  
Radio Spectrum ◽  
Spectrum Utilization ◽  
Transmission Parameters ◽  
Wireless Users ◽  
Radio Technology ◽  
Cognitive Radio Technology

Frequency spectrum is a limited resource and the increasing demand caused by emerging services, augmented number of wireless users along with the demand for high-quality multimedia applications have resulted in the overcrowding of the allocated spectrum bands. The overcrowding of spectrum bands has exacerbated by the current spectrum licensing policy which has emerged as a bottleneck to efficient spectrum utilization, due to its inflexibility, resulting in most of the licensed spectrum being severely under-utilized. However, the problem of scarcity of spectrum bands and the inefficient utilization of the already allocated radio spectrum can be smartly addressed through spectrum sharing by enabling opportunistic usage of the underutilized frequency bands. One of the most exciting ways of spectrum sharing is cognitive radio technology which allows a wireless node to sense the environment, detect the network changes, and then make intelligent decisions by dynamically changing its reception or transmission parameters to communicate while ensuring that no interference is affected to the licensed users. It thus improves the spectrum utilization by reusing the unused or underutilized spectrum owned by the incumbent systems (primary systems). In this paper, a comprehensive survey and review of recent research about the advances in cognitive radio technology will be carried out. We will also evaluate the various spectrum sensing techniques in a cognitive radio network in the UHF/VHF bands allocated for TV broadcasting.

Research of Spectrum Detecting Technology on Cognitive Radio

2013 ◽  
Vol 433-435 ◽  
pp. 911-914
Author(s):  
Hong Yan Mao
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Cooperative Spectrum Sensing ◽  
Detection Method ◽  
Radio Spectrum ◽  
Spectrum Utilization ◽  
Transmission Parameters ◽  
Spectrum Detection

Cognitive radio (CR) is an intelligent spectrum sharing technology. It can improve the spectrum utilization by sensing spectrum environment, learning intelligently and adjusting the transmission parameters. The discussion is focused on spectrum detecting technology in cognitive radio. Spectrum detecting algorithms are analyzed and compared .The centralized cooperative spectrum detection method, distributed cooperative spectrum sensing method and relay cooperative spectrum detection method are analyzed also.

scholarly journals Optimal linear weighted cooperative spectrum sensing for clustered-based cognitive radio networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Haiyan Ye ◽  
Jiabao Jiang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Spectrum Utilization ◽  
Channel Characteristics ◽  
Optimal Linear ◽  
Static Division ◽  
Cooperative Nodes

AbstractThe lack of spectrum resources restricts the development of wireless communication applications. In order to solve the problems of low spectrum utilization and channel congestion caused by the static division of spectrum resource, this paper proposes an optimal linear weighted cooperative spectrum sensing for clustered-based cognitive radio networks. In this scheme, different weight values will be assigned for cooperative nodes according to the SNR of cognitive users and the historical sensing accuracy. In addition, the cognitive users can be clustered, and the users with the better channel characteristics will be selected as cluster heads for gathering the local sensing information. Simulation results show that the proposed scheme can obtain better sensing performance, improve the detection probability and reduce the error probability.

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 Design of Hybrid Blind Detection Based Spectrum Sensing Technique

2020 ◽  
Vol 12 (4) ◽  
pp. 575-583
Author(s):  
V. Sharma ◽  
S. Joshi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Research Area ◽  
Detection Accuracy ◽  
Blind Detection ◽  
Spectrum Utilization ◽  
Detection Techniques ◽  
Generation Spectrum

Cognitive Radio is a boon to efficient utilization of spectrum to meet the demand of next generation. Spectrum Sensing (SS) is an active research area, essential to meet the requirement of efficient spectrum utilization as it detects the vacant bands. This paper develops a Hybrid Blind Detection (HBD) technique for cooperative spectrum sensing which combines the Energy Detector (ED) and the Anti-Eigen Value Detection (AVD) techniques together to enhance the detection accuracy of a cognitive radio. Collaboration among the cognitive users is achieved to reduce the error and hard fusion based detection is implemented to detect the existence of primary user. The detection accuracy of the design is evaluated with respect to detection probabilities and the results are examined for improvements with the traditional two stage detection techniques. Fusion rules for the cooperative environment are implemented and compared to detect majority rule suitable for the proposed design.

scholarly journals An Optimized and Trained Model of Cooperative Sensing for Cognitive Radio Networks

2019 ◽  
Vol 8 (3) ◽  
pp. 5176-5182
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Search Algorithm ◽  
Decision Threshold ◽  
Secondary Users ◽  
Communication Problems ◽  
Local Decision ◽  
Huge Impact ◽  
Radio Technology

Sensing based spectrum allocation is one of the solutions to bridge the gap between spectrum scarcity and underutilization of allocated spectrum. In this context, cognitive radio technology has become the prominent solution for future wireless communication problems. To accurately detect the spectrum availability, CRN uses cooperative spectrum sensing where N number of selected nodes will be involved in making a decision on spectrum occupation. Various sensing parameters such as sensing duration (τ), decision threshold (λ), number of nodes (N) and decision rule (K) have huge impact on the performance of cooperative spectrum sensing. In addition, there are constraints on energy consumption and protection of licensed user’s needs to be considered. Our work focuses on optimization of sensing parameters to maximize the throughput of the cognitive radio network maintaining the energy efficiency and protecting the licensed users from the interference caused by the secondary users. The proposed work uses convex optimization to optimize sensing duration and two-dimensional search algorithm to find the values N and K. Further optimization is done by comparing local decision with cooperative decision.

scholarly journals An Authentication Based Approach for Prevention of Spectrum Sensing Data Falsification Attacks in Cognitive Radio Network

2021 ◽  
Author(s):  
Nikhil Marriwala ◽  
Himanshu Punj ◽  
Sunita Panda ◽  
Inderjeet Kaur ◽  
Deepak Rathore
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Radio Networks ◽  
Radio Network ◽  
Spectrum Utilization ◽  
Authentication Mechanism ◽  
Free Spectrum ◽  
Radio Technology ◽  
Cognitive Radio Technology

Abstract This is the era of Intelligent cognitive radio network technology that provides the available spectrum with efficient utilization. Cognitive Radio technology must promise to allow interference-free spectrum access by users. The paper discusses the several attacks and motives of attacks. The authentication mechanism role to prevent the attacks for hassle-free spectrum utilization is demonstrated. In this paper, resolving the cognitive network security issues by the authentication mechanism and the methods and need of authentication is discussed. This paper addresses the research challenges in the way of securing the cognitive radio network and countermeasures in CRN security strategies. Cognitive radio is an empowering innovation that guarantees to achieve spectrum utilization. In cognitive radio networks, several security threats affect the process of cognitive radio. Spectrum sensing data falsification (SSDF) attack is most disruptive in which the malicious users degrade the decision-making process by sending the false sensing reports to data fusion centres thus preventing honest users from utilizing the spectrum. Hence, security is a very important issue in cognitive radio networks that needs to be addressed for proper utilization of available spectrum by the users. Cognitive radio technology must promise secure spectrum dynamic access to users. In this paper, to counter the SSDF attack, the trust-based security mechanism is demonstrated to authenticate the honest users and it is observed that the proposed framework in the MATLAB environment is efficient and able to detect malicious users. Cognitive radio technology is the strategy applied to the spectrum to make it efficient for wireless communication. The strategy is an intelligent way to access the spectrum as it can learn its environment and make decisions by easy adaptation of operating parameters. The multiple nodes scenario is a good perspective. Software-defined radio is an essential component of cognitive radio Here, secondary users can access the spectrum to primary users whenever their vacant spectrum is available. The initial step is to sense the spectrum available further steps are spectrum decision making, spectrum management, and spectrum mobility. The network is vulnerable to various attacks on spectrum sensing and policy protocols which lead to disturbing functionality of cognitive radio technology. The defence mechanism based on public-key cryptography is proposed in which PU is authenticated by appending signature provided to PU signal. Authentication with a tag to the primary users is another perspective proposed. CRN technology should provide integrity, confidentiality and authenticity to the users.

scholarly journals Cooperative Spectrum Sensing with Selection Diversity Reception in Cognitive Radio

2021 ◽  
pp. 1-7
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Recognition Performance ◽  
Fusion Rule ◽  
Diversity Reception ◽  
Selection Diversity ◽  
Simulation Evaluation ◽  
Radio Technology ◽  
Cognitive Radio Technology

Spectrum sensing is the key component of cognitive radio technology. But, detection is compromised when a user reports shadowing or fading consequences. In such instances, the customer cannot apprehend between an unexploited band and a profound fade. Hence, communal spectrum sensing is suggested to optimize sensing overall performance. We recognition performance of communal Spectrum Sensing with Selection Diversity Reception in Cognitive Radio. This study presents a simulation evaluation of choice diversity Reception based totally on the fusion rule. The fusion rule is finished at the fusion center (FC) to make the very last selection about the presence of PU. This leads that spectrum sensing is enthusiastically in the presence of Rayleigh.

Analysis of Spectrum Sensing in Cognitive Radio Network with OFDM

2018 ◽  
Vol 8 (6) ◽  
pp. 84
Author(s):  
Shadab Ahmed Khan ◽  
Pawandeep Kaur
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Energy Detection ◽  
Radio Spectrum ◽  
Probability Of Detection ◽  
Spectrum Utilization ◽  
Wireless Applications ◽  
Novel Technology ◽  
Cognitive Environment

With the development of a new and ever expanding wireless applications and services, spectrum resources are facing in demands. In present scenario, the spectrum allotment has been done by providing each new service with its own fixed frequency Slot. Most of the user’s spectrum is already assigned, so it becomes very difficult to find spectrum for other users or existing users. This leads to the scarcity of available spectrum and inefficient channel utilization. Cognitive radio is a novel technology which improves the spectrum utilization by allowing secondary user to borrow unused radio spectrum from primary licensed users or to share the spectrum with the primary users. Present paper deals with the spectrum sensing in which multiple users detect the spectrum gap through energy detection and investigate the detection performance in an efficient and implementable way. Simulation results showed that the probability of detection is achieved at small value SNR in case of OFDM modulation as compare the other and simple cognitive environment.

scholarly journals Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey on Machine Learning-based Methods

2020 ◽  
Vol 3 ◽  
pp. 36-46
Author(s):  
Sundous Khamayseh ◽  
Alaa Halawani
Keyword(s):  
Machine Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Continuous Growth ◽  
Radio Technology ◽  
Promising Solution

The continuous growth of demand experienced by wireless networks creates a spectrum availability challenge. Cognitive radio (CR) is a promising solution capable of overcoming spectrum scarcity. It is an intelligent radio technology that may be programmed and dynamically configured to avoid interference and congestion in cognitive radio networks (CRN). Spectrum sensing (SS) is a cognitive radio life cycle task aiming to detect spectrum holes. A number of innovative approaches are devised to monitor the spectrum and to determine when these holes are present. The purpose of this survey is to investigate some of these schemes which are constructed based on machine learning concepts and principles. In addition, this review aims to present a general classification of these machine learningbased schemes

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