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Proceedings ArticleDOI

Artifical neural network based multi dimensional spectrum sensing in full duplex cognitive radio networks

TL;DR: This work focuses the implementation of neural network by means of Levenberg-Maquardt algorithm in case of an energy detector in single and multi channel to solve a set of objective functions with minimum iterations and increases the efficiency of cognitive radio network (CRN).
Abstract: Cognitive Radio is the prime key for spectrum shortage and used to detect the unused spectrum by a way of multidimensional spectrum sensing concept. Though Spectrum sensing applies a huge load of energy, it can be shortened by utilizing different artificial neural network methods for determining proper spectrum vacancy. This work focuses the implementation of neural network by means of Levenberg-Maquardt algorithm in case of an energy detector in single and multi channel. It is used to solve a set of objective functions with minimum iterations and increases the efficiency of cognitive radio network (CRN).
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Book ChapterDOI
01 Jan 2019
TL;DR: This chapter undertake a comprehensive analysis of 30 peer-reviewed scientific publications collated from 2017 to 2018 April that examine cognitive radio networks to identify practical solutions proposed to overcome critical challenges in this field.
Abstract: Cognitive radio technology (CRNs) will be the fundamental driving force behind the next generation (5G) mobile communication systems as it provides the optimal solution for the problem of spectrum scarcity via dynamic spectrum usage. The CRNs, however, pose several key challenges such as network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and quality of service (QoS). In this chapter, the authors undertake a comprehensive analysis of 30 peer-reviewed scientific publications collated from 2017 to 2018 April that examine cognitive radio networks to identify practical solutions proposed to overcome critical challenges in this field. Nine distinct challenges were considered: network management, spectrum allocation, and access, energy efficiency, interference, cost, spectrum sensing, security, and QoS. The analysis demonstrates that the majority of research work related to CRN focuses on approaches to improve network management and, specifically, optimization of networks.
Journal ArticleDOI
24 Jan 2023-Sensors
TL;DR: In this paper , the authors used GRU in CRN to train and test the dataset of spectrum sensing results and achieved a high testing accuracy of 82.45%, training accuracy of 80.99% and detection probability of 1 is achieved at 65 epochs in this proposed work.
Abstract: Cognitive radio networks are vulnerable to numerous threats during spectrum sensing. Different approaches can be used to lessen these attacks as the malicious users degrade the performance of the network. The cutting-edge technologies of machine learning and deep learning step into cognitive radio networks (CRN) to detect network problems. Several studies have been conducted utilising various deep learning and machine learning methods. However, only a small number of analyses have used gated recurrent units (GRU), and that too in software defined networks, but these are seldom used in CRN. In this paper, we used GRU in CRN to train and test the dataset of spectrum sensing results. One of the deep learning models with less complexity and more effectiveness for small datasets is GRU, the lightest variant of the LSTM. The support vector machine (SVM) classifier is employed in this study’s output layer to distinguish between authorised users and malicious users in cognitive radio network. The novelty of this paper is the application of combined models of GRU and SVM in cognitive radio networks. A high testing accuracy of 82.45%, training accuracy of 80.99% and detection probability of 1 is achieved at 65 epochs in this proposed work.
References
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Journal ArticleDOI
Simon Haykin1
TL;DR: Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks: radio-scene analysis, channel-state estimation and predictive modeling, and the emergent behavior of cognitive radio.
Abstract: Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: /spl middot/ highly reliable communication whenever and wherever needed; /spl middot/ efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.

12,172 citations


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Journal ArticleDOI
TL;DR: In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented and the cooperative sensing concept and its various forms are explained.
Abstract: The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.

4,812 citations

01 Jan 2000
TL;DR: This article briefly reviews the basic concepts about cognitive radio CR, and the need for software-defined radios is underlined and the most important notions used for such.
Abstract: An Integrated Agent Architecture for Software Defined Radio. Rapid-prototype cognitive radio, CR1, was developed to apply these.The modern software defined radio has been called the heart of a cognitive radio. Cognitive radio: an integrated agent architecture for software defined radio. Http:bwrc.eecs.berkeley.eduResearchMCMACR White paper final1.pdf. The cognitive radio, built on a software-defined radio, assumes. Radio: An Integrated Agent Architecture for Software Defined Radio, Ph.D. The need for software-defined radios is underlined and the most important notions used for such. Mitola III, Cognitive radio: an integrated agent architecture for software defined radio, Ph.D. This results in the set-theoretic ontology of radio knowledge defined in the. Cognitive Radio An Integrated Agent Architecture for Software.This article first briefly reviews the basic concepts about cognitive radio CR. Cognitive Radio-An Integrated Agent Architecture for Software Defined Radio. Cognitive Radio RHMZ 2007. Software-defined radio SDR idea 1. Cognitive radio: An integrated agent architecture for software.Cognitive Radio SOFTWARE DEFINED RADIO, AND ADAPTIVE WIRELESS SYSTEMS2 Cognitive Networks. 3 Joseph Mitola III, Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio Stockholm.

3,814 citations


Additional excerpts

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Proceedings ArticleDOI
01 Jan 2005
TL;DR: This paper considers the case of two cognitive users and shows how the inherent asymmetry in the network can be exploited to increase the agility, and extends the protocol to study multi-user multi-carrier cognitive network.
Abstract: In this paper, we illustrate the benefits of cooperation in cognitive radio. Cognitive (unlicensed) users need to continuously monitor spectrum for the presence of primary (licensed) users. We show that by allowing the cognitive radios operating in the same band to cooperate we can reduce the detection time and thus increase the overall agility. We first consider the case of two cognitive users and show how the inherent asymmetry in the network can be exploited to increase the agility. We then extend our protocol to study multi-user multi-carrier cognitive network. We compare our cooperation scheme with the non-cooperation scheme and derive expressions for agility gain. We show that our cooperation scheme reduces the detection time for the cognitive users by as much as 35%

279 citations

Proceedings ArticleDOI
11 Sep 2005
TL;DR: This paper addresses design issues involved in an implementation of cognitive radio functions that could limit their performance or even make them infeasible and introduces algorithms and techniques whose implementation could meet these challenging requirements.
Abstract: Cognitive radio systems offer the opportunity to improve spectrum utilization by detecting unoccupied spectrum bands and adapting the transmission to those bands while avoiding the interference to primary users. This novel approach to spectrum access introduces unique functions at the physical layer: reliable detection of primary users and adaptive transmission over a wide bandwidth. In this paper, we address design issues involved in an implementation of these functions that could limit their performance or even make them infeasible. The critical design problem at the receiver is to achieve stringent requirements on radio sensitivity and perform signal processing to detect weak signals received by a wideband RF front-end with limited dynamic range. At the transmitter, wideband modulation schemes require adaptation to different frequency bands and power levels without creating interference to active primary users. We introduce algorithms and techniques whose implementation could meet these challenging requirements

226 citations


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