Efficient Spectrum Management Techniques for Cognitive Radio Networks for Proximity Service
20 Mar 2019-IEEE Access (Institute of Electrical and Electronics Engineers (IEEE))-Vol. 7, pp 43795-43805
TL;DR: The concept of multiple attributes for decision making was implemented, under which, the simple additive weights method and the technique for order preference by similarity to ideal solution method were compared based on a performance involving the triple play of services.
Abstract: Cognitive radio networks improve spectrum efficiency by employing vigilant and accurate spectrum management techniques. This is done to enable an unlicensed user to use the underutilized spectrum. Spectrum sensing determines if a spectrum hole exists for the unlicensed user, this is accomplished using various techniques such as energy detection, minimum Eigen value detection, and matched filter technique. Conventional energy detection techniques do not achieve high values of detection; hence an improved adaptive energy detection technique has been proposed to improve the efficiency. The proposed methodology exhibits better numerical results than conventional techniques. Another important spectrum management procedure is spectrum handoff. The concept of multiple attributes for decision making was implemented, under which, the simple additive weights method and the technique for order preference by similarity to ideal solution method were compared based on a performance involving the triple play of services.
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TL;DR: The results indicate that the accuracy of the target model reduce significantly by adversarial attacks, when the perturbation factor is 0.001, and iterative methods show greater attack performances than that of one-step method.
Abstract: Deep learning (DL) models are vulnerable to adversarial attacks, by adding a subtle perturbation which is imperceptible to the human eye, a convolutional neural network (CNN) can lead to erroneous results, which greatly reduces the reliability and security of the DL tasks. Considering the wide application of modulation recognition in the communication field and the rapid development of DL, by adding a well-designed adversarial perturbation to the input signal, this article explores the performance of attack methods on modulation recognition, measures the effectiveness of adversarial attacks on signals, and provides the empirical evaluation of the reliabilities of CNNs. The results indicate that the accuracy of the target model reduce significantly by adversarial attacks, when the perturbation factor is 0.001, the accuracy of the model could drop by about 50 ${\%}$ on average. Among them, iterative methods show greater attack performances than that of one-step method. In addition, the consistency of the waveform before and after the perturbation is examined, to consider whether the added adversarial examples are small enough (i.e., hard to distinguish by human eyes). This article also aims at inspiring researchers to further promote the CNNs reliabilities against adversarial attacks.
89 citations
Cites background from "Efficient Spectrum Management Techn..."
...In addition, spectrum monitoring, spectrum management, and other fields are also inseparable from modulation recognition as an important technical means [9], [10]....
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TL;DR: A fuzzy genetic based dynamic spectrum allocation (FGDSA) system for deciding spectrum allocation in cognitive radio sensor networks is introduced and it was observed that the hybrid system of FGDSA outperforms fuzzy system by 2% in channel utilization, by also ensuring 16% less SINR, and 41% less channel access delay.
Abstract: Cognitive radio sensor network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such a system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here the concept of dynamic spectrum access defines the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the primary user (PU) has the license to access the spectrum band. On the other hand, the secondary user (SU) tries to access the unused spectrum efficiently, by not disturbing the PU. Considering that issue, this study introduces a fuzzy genetic based dynamic spectrum allocation (FGDSA) system for deciding spectrum allocation in cognitive radio sensor networks. In detail, the primary objective of the FGDSA system is to increase channel use without causing too much interference to the PU. In order to achieve that, some parameters such as signal interference noise ratio (SINR), bit error rate (BER), available channel bandwidth, SU transmission power, and the SU data rate are used as input variables for the fuzzy based inference mechanism taking place in the FGDSA. After development of the system, a performance analysis was done by comparing some metrics such as channel utilization, signal noise interference ratio, and the channel access delay for fuzzy based inference and the fuzzy genetic based inference that are both performing spectrum allocation. It was observed that the hybrid system of FGDSA outperforms fuzzy system by 2% in channel utilization, by also ensuring 16% less SINR, and 41% less channel access delay. The FGDSA was compared with also some existing spectrum allocation techniques such as edge coloring heuristic (ECH) and clique heuristic algorithm (CHA). It was seen that the FGDSA outperforms both ECH and CHA in average channel utilization, with the rates of 6% and 8%, respectively.
7 citations
Cites methods from "Efficient Spectrum Management Techn..."
...proposed an improved adaptive energy detection technique [26]....
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01 Nov 2019
TL;DR: The simulation shows that SAW method is powerful for choosing the ideal network for spectrum handoff as per triple play benefits in CR systems.
Abstract: Intellectual radio(IR) is an innovation that can be utilized to discover the accessible channels in wireless spectrum for transmission of data. The cognitive radio is a technology to avoid user interference and congestion. The network consists of multiple parameters to identify the possible network for transmission without delay. The perfect system determination for range handoff is done by MADM technique is simple additive weighting method. SAW strategy use a Triple play administration known as video, voice and information administrations are based on CR preferences. The simulation shows that SAW method is powerful for choosing the ideal network for spectrum handoff as per triple play benefits in CR systems.
7 citations
Cites methods from "Efficient Spectrum Management Techn..."
...Vitality identification procedure has been proposed to improve the productivity [1]....
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TL;DR: The results show channel-switching savings can be achieved in a CR network with the proposed approach, and an increase in throughput was observed for multi-step-ahead prediction with three future states.
Abstract: This paper analyzes multi-step-ahead spectrum prediction for Cognitive Radio (CR) systems using several future states. A slot-based scenario is used, and prediction is based on the Support Vector Machine (SVM) algorithm. The aim is to determine whether multi-step-ahead spectrum prediction has gains in terms of reduced channel-switching and increased network throughput compared with short-term prediction. The system model is simulated in software using an exponential on-off distribution for primary-user traffic. A classical energy detector is used to perform sensing. With the help of simplifications, we present new closed-form expressions for the detection probability under AWGN and Rayleigh fading channels which allows the appropriate number of samples for these scenarios to be found. The performance of the proposed predictor is thoroughly assessed in these scenarios. The SVM algorithm had low prediction error rates, and multi-step-ahead idle-channel scheduling resulted in a reduction in channel switching by the SU of up to 51%. An increase in throughput of approximately 4% was observed for multi-step-ahead prediction with three future states. The results also show channel-switching savings can be achieved in a CR network with the proposed approach.
5 citations
Cites background from "Efficient Spectrum Management Techn..."
...The SU listens to the states of the channels and, after processing historical data, predicts future channel occupancy [10]....
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20 Dec 2020
TL;DR: In this article, the authors provide a technical insight in gauging the level of effectiveness in the existing security aspect and facilitate the upcoming researchers with information about the current research gap and possible solutions to leverage the security.
Abstract: Inclusion of Cognitive Radio Network (CRN) in different networking technologies is proven to offer an efficient communication system due to its potential characteristics of managing the transmission and reception attributes, especially in the wireless environment. CRN harnesses the capability of resisting interference between the licensed users and unlicensed user. However, it is still challenging to countermeasure the level of threats in the wireless medium by CRN. With various research-based solutions towards securing CRN, existing approaches still witness security breach when CRN is deployed over complex networking technologies. Therefore, this paper provides a technical insight in gauging the level of effectiveness in the existing security aspect and facilitates the upcoming researchers with information about the current research gap and possible solutions to leverage the security.
4 citations
References
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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
"Efficient Spectrum Management Techn..." refers background in this paper
...Cognitive radio networks address this issue by using a concept where the spectrum can be used by unlicensed users in the absence of licensed users to provide maximum spectrum efficiency [1]....
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TL;DR: Recent developments and open research issues in spectrum management in CR networks are presented and four main challenges of spectrum management are discussed: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility.
Abstract: Cognitive radio networks will provide high bandwidth to mobile users via heterogeneous wireless architectures and dynamic spectrum access techniques. However, CR networks impose challenges due to the fluctuating nature of the available spectrum, as well as the diverse QoS requirements of various applications. Spectrum management functions can address these challenges for the realization of this new network paradigm. To provide a better understanding of CR networks, this article presents recent developments and open research issues in spectrum management in CR networks. More specifically, the discussion is focused on the development of CR networks that require no modification of existing networks. First, a brief overview of cognitive radio and the CR network architecture is provided. Then four main challenges of spectrum management are discussed: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility.
1,722 citations
"Efficient Spectrum Management Techn..." refers background in this paper
...the best network for the service at play have to be executed accurately, and in a short time span to warrant efficiency [5]....
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TL;DR: An overview of the regulatory requirements and major challenges associated with the practical implementation of spectrum sensing functionality in cognitive radio systems is provided and different design trade-offs that have to be made in order to enhance various aspects of the system's performance are outlined.
Abstract: Opportunistic unlicensed access to the (temporarily) unused frequency bands across the licensed radio spectrum is currently being investigated as a means to increase the efficiency of spectrum usage. Such opportunistic access calls for implementation of safeguards so that ongoing licensed operations are not compromised. Among different candidates, sensing-based access, where the unlicensed users transmit if they sense the licensed band to be free, is particularly appealing due to its low deployment cost and its compatibility with the legacy licensed systems. The ability to reliably and autonomously identify unused frequency bands is envisaged as one of the main functionalities of cognitive radios. In this article we provide an overview of the regulatory requirements and major challenges associated with the practical implementation of spectrum sensing functionality in cognitive radio systems. Furthermore, we outline different design trade-offs that have to be made in order to enhance various aspects of the system's performance.
1,036 citations
"Efficient Spectrum Management Techn..." refers background in this paper
...This is achieved by using dynamic spectrum access which allows users to access spectrum bands in an opportunistic manner through continuous sensing and selection [3]–[4]....
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13 Apr 2008
TL;DR: This work provides closed form analysis on secondary user performance, presents a tight capacity upper bound, and reveals the impact of various design options, such as sensing, packet length distribution, back-off time, packet overhead, and grouping.
Abstract: Driven by regulatory initiatives and radio technology advances, opportunistic spectrum access has the potential to mitigate spectrum scarcity and meet the increasing demand for spectrum. In this paper, we consider a scenario where secondary users can opportunistically access unused spectrum vacated by idle primaries. We introduce two metrics to protect primary performance, namely collision probability and overlapping time. We present three spectrum access schemes using different sensing, back-off, and transmission mechanisms. We show that they achieve indistinguishable secondary performance under given primary constraints. We provide closed form analysis on secondary user performance, present a tight capacity upper bound, and reveal the impact of various design options, such as sensing, packet length distribution, back-off time, packet overhead, and grouping. Our work sheds light on the fundamental properties and design criteria on opportunistic spectrum access.
400 citations
"Efficient Spectrum Management Techn..." refers methods in this paper
...Algorithms such as simple additive weight, technique for order preference by similarity to ideal solution assess the networks to select the one that exhibits the characteristics best suited for the service at play [14]–[15]....
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TL;DR: The future cognitive radio with the expanded capabilities a network radio is called, and its architecture as well as the design issues for future DSA are discussed, which should consider the political, social, economic, and technological factors all together to pave the way for the commercial success of DSA.
Abstract: Dynamic spectrum access is a new spectrum sharing paradigm that allows secondary users to access the abundant spectrum holes or white spaces in the licensed spectrum bands. DSA is a promising technology to alleviate the spectrum scarcity problem and increase spectrum utilization. While DSA has attracted many research efforts recently, in this article, we discuss the challenges of DSA and aim to shed light on its future. We first give an introduction to the state-of- the-art in spectrum sensing and spectrum sharing. Then, we examine the challenges that prevent DSA from major commercial deployment. We believe that, to address these challenges, a new DSA model is critical, where the licensed users cooperate in DSA and hence much more flexible spectrum sharing is possible. Furthermore, the future DSA model should consider the political, social, economic, and technological factors all together, to pave the way for the commercial success of DSA. To support this future DSA model, the future cognitive radio is expected to have additional components and capabilities, to enforce policy, provide incentive and coexistence mechanisms, etc. We call the future cognitive radio with the expanded capabilities a network radio, and discuss its architecture as well as the design issues for future DSA.
302 citations
"Efficient Spectrum Management Techn..." refers background in this paper
...This is achieved by using dynamic spectrum access which allows users to access spectrum bands in an opportunistic manner through continuous sensing and selection [3]–[4]....
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