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Security threats, detection, and countermeasures for physical layer in cognitive radio networks: A survey

Physical Communication, 2020
Cyber-security threats and issues have been exponentially increasing over the last two decades, including in cognitive radio networks. These attacks and vulnerabilities negatively impact the normal functioning of these networks.
Fatima Salahdine, N. Kaabouch
semanticscholar   +1 more source

Radio Environment Prediction for Cognitive Radio

2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), 2008
The evaluation and the prediction of the radio environment is one of the key issues to improve the cognitive radio. The prediction accuracy of the transmission capability in each wireless media will directly affect the performance of the transmission performance.
Kazunori Takeuchi   +2 more
openaire   +1 more source

Deep Learning-Based Spectrum Sensing in Cognitive Radio: A CNN-LSTM Approach

IEEE Communications Letters, 2020
For most existing spectrum sensing detectors, the design of their test statistics relies on certain signal-noise model assumptions and hence, their detection performance heavily depends on the accuracy of the assumed models.
Jiandong Xie   +3 more
semanticscholar   +1 more source

On cognitive processes in cognitive radio networks

Wireless Networks, 2013
In this article we model the cognitive processes and evaluate their impact on the performance of cognitive radio networks (CRN). Operation of the cognitive radio nodes, can be characterized by two types of processes: communication processes such as packets transmission, and cognitive processes such as estimation of the network state and decision-making
Boris Oklander, Moshe Sidi
openaire   +1 more source

Physical Layer Security in Cognitive Radio Inspired NOMA Network

IEEE Journal on Selected Topics in Signal Processing, 2019
This paper investigates physical layer security (PLS) in cognitive radio inspired non-orthogonal multiple access (CR-NOMA) networks with multiple primary and secondary users.
Zhongwu Xiang   +4 more
semanticscholar   +1 more source

Outage Probability for Cooperative NOMA Systems With Imperfect SIC in Cognitive Radio Networks

IEEE Communications Letters, 2019
In this letter, a cooperative non-orthogonal multiple access system with imperfect successive interference cancellation is investigated in an underlay cognitive radio network.
Gyeongrae Im, Jae Hong Lee
semanticscholar   +1 more source

5G Based on Cognitive Radio

Wireless Personal Communications, 2010
Both the cognitive radio (CR) and the fifth generation of cellular wireless standards (5G) are considered to be the future technologies: on one hand, CR offers the possibility to significantly increase the spectrum efficiency, by smart secondary users (CR users) using the free licensed users spectrum holes; on the other hand, the 5G implies the whole ...
Cornelia-Ionela Badoi   +3 more
openaire   +1 more source

Progression on spectrum sensing for cognitive radio networks: A survey, classification, challenges and future research issues

Journal of Network and Computer Applications, 2019
It is widely believed that the advances of networking technologies will reshape the future of telecommunication system. The continuous growth in data traffic originated by mobile users will be witnessed very serious problem in future. By 2021, the number
M. Gupta, Krishan Kumar
semanticscholar   +1 more source

AI-Based Abnormality Detection at the PHY-Layer of Cognitive Radio by Learning Generative Models

IEEE Transactions on Cognitive Communications and Networking, 2020
Introducing a data-driven Self-Awareness (SA) module in Cognitive Radio (CR) can support the system to establish secure networks against various attacks from malicious users.
Andrea Toma   +6 more
semanticscholar   +1 more source

Cognitive Radio Networks


Dynamic spectrum networks enable fast deployment of new wireless technologies by. ondary devices are next-generation cognitive radio devices. ?common control channel saturation detection and.
Shamik Sengupta   +3 more
semanticscholar   +1 more source

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