Comparison among Cognitive Radio Architectures for Spectrum Sensing

Bixio, Luca; Ottonello, Marina; Raffetto, Mirco; Regazzoni, Carlo S.

doi:10.1155/2011/749891

Cited by 14 publications

(8 citation statements)

References 18 publications

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“…An example of such an SVC based discriminator is illustrated in Figure 1 corresponding to a single user. Further, the proposed algorithm has much lower computational complexity as it does not employ a non-linear kernel [5] as is employed in conventional SVC based approaches. Moreover, it results in optimal detection performance since, as discussed earlier, linear discrimination is optimal in such scenarios [7].…”

Section: Support Vector Classifiermentioning

confidence: 99%

“…Let us define the binary random variable , as follows, ,1 denotes the absence and presence of the primary user respectively. The logistic regression based probability density function of can be described as, The quantities which are the parameters of the LR, can be obtained by maximizing the log-likelihood function corresponding to training sets and as, It can be seen that the above log-likelihood function is a concave function [5] of parameters and . Hence, the ML estimate of corresponding to maximizing the log-likelihood function above can be formulated as a convex optimization problem.…”

Section: Logistic Regressionmentioning

confidence: 99%

“…Further, since the proposed classifiers are not based on the communicated channel state and noise PSD parameter estimates, their performance is highly robust compared to existing schemes in the presence of voluntary and involuntary report distortion arising due to malicious users and Doppler induced shifts respectively. Moreover, unlike existing SVM approaches in works such as [5], which employ classifiers based on non-linear kernel functions, the proposed classifiers have much lower complexity since they are linear. However, they do not result in a degradation of accuracy of spectrum sensing since it has been established in literature that linear classification is optimal in such matched filtering based additive white Gaussian noise baseband communication scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Optimal classifier based spectrum sensing in cognitive radio wireless systems

Sharma

Jagannatham

2011

Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief

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In this work, we present and investigate the performance of novel classification schemes for spectrum sensing in cooperative multiple-input multiple-output (MIMO) wireless cognitive radio (CR) networks. In this context, we consider several optimal classification schemes such as support vector classifiers (SVC), logistic regression (LR) and quadratic discrimination (QD) for primary user detection. It is demonstrated that these classification techniques have a significantly reduced complexity of implementation in practical CR applications compared to conventional likelihood based detection schemes as they do not require knowledge of the channel state information and noise power. Further, in the presence of disruptive malicious users, the proposed classifiers have a significantly lower detection error compared to conventional detection schemes. Also, we propose a novel QD classifier for blind MIMO spectrum sensing scenarios. The detection performance of the proposed classifiers is compared with existing schemes in co-operative CR scenarios. It is demonstrated through simulation of several scenarios including the presence of malicious users, Doppler shift, and carrier frequency offset that the proposed classifiers offer a robust and significantly superior alternative to existing schemes for cooperative MIMO CR spectrum sensing.

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Section: Support Vector Classifiermentioning

confidence: 99%

Section: Logistic Regressionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal classifier based spectrum sensing in cognitive radio wireless systems

Sharma

Jagannatham

2011

Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief

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“…It has been shown that cooperative sensing provides reliable detection if the number of cooperating sensors is large enough [17]. In addition, cooperative sensing also shortens the sensing time of the spectrum while improving the overall sensitivity [18]. Nonetheless, related literature does not substantially clarify the optimum cooperative decision criteria to be followed.…”

Section: Introductionmentioning

confidence: 99%

Implementing opportunistic spectrum access in LTE-advanced

Osa

Herranz

Monserrat

et al. 2012

J Wireless Com Network

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Long term evolution advanced (LTE-A) has emerged as a promising mobile broadband access technology aiming to cope with the increasing traffic demand in wireless networks. However, the enhanced spectral efficiency offered by LTE-A may become futile without a better management of scarce and overcrowded electromagnetic spectrum. In this sense, cognitive radio (CR) has been proposed as a potential solution to the problem of spectrum scarcity. Among all the mechanisms provided by CR, opportunistic spectrum access (OSA) aims at a dynamic and seamless use of certain licensed bands provided the licensee is not harmfully affected. This operation requires spectral awareness in order to avoid interferences with licensed systems. In spite of implementing some spectrum sensing mechanisms, LTE-A technology lacks other tools that are needed in order to improve the knowledge of the radio environment. This work studies the adoption of a Geo-located data base (Geo-DB) that cooperatively retrieves and maintains information regarding the location of unutilized portions of spectrum potentially available for OSA. Moreover, the potential benefit of this LTE-compliant OSA solution is evaluated using a calibrated simulation tool, by which numerical results allow us to optimally configure the system and show that the proposed opportunistic system is able to significantly improve its performance.

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“…Se ha demostrado que la detección de espectro cooperativa proporciona resultados fiables cuando el número de usuarios cooperando es lo suficientemente elevado [113]. Además, la detección cooperativa acorta los tiempos de detección necesarios a la vez que mejora la capacidad global de detección [114]. Sin embargo, la literatura relacionada no clarifica sustancialmente el criterioóptimo de decisión a emplear.…”

Section: Acceso Oportunista Al Espectrounclassified

Planificación y Optimización Automática de Redes Móviles LTE

Ginés¹

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Currently, wireless mobile communications are immersed in a process of evolution. 3G technologies give way to 4G, in a context of tremendous growth in traffic demand by users of mobile broadband, and the introduction of LTE technology is starting to spread.In this process of improvement, which is a major financial outlay for mobile operators, there is a growing interest in reducing operational expenditures of planning and network optimization, for which automatic mechanisms that perform these functions emerge as the ideal solution.This PhD Thesis proposes various automatic mechanisms for planning and optimization of LTE networks and provides a detailed study of its performance. The content is structured in three sections, preceded by a description of the followed methodology, which is based on simulations, and the different assumptions made.The first part focuses on the treatment of available information and describes a set of tools designed to assist in the proposed processes. Of great relevance to the rest of the thesis is the designed location algorithm, which is a fundamental tool in all automatic planning and optimisation mechanisms due to the ability of geo-referencing the information used. The great advantage of the algorithm is that it is possible to use it without introducing any new elements in the network which enable it, as it is based on measurements made during normal operation of the network, acquired through call tracing tools. It is also worth mentioning the use of expert systems based on neural networks for obtaining feedback for specific recommendations given by the designed optimization tool.Secondly, the planning and optimization of LTE radio access network using heuristic search methods of the optimal solution are treated. The use of realistic traffic maps, enabled by the location algorithm, and the estimation of the load in each cell allows accurate assessment of the performance of the different candidate solutions in an acceptable time, thanks to the linearization of the models used among other methods proposed for efficient execution of the process. It also assesses the impact of the localization algorithm error on the planning and optimization solutions obtained.Finally, because of radio spectrum resources are limited and need to be managed properly, the best options are analysed when it comes to the reuse of available resources and the migration of base stations of legacy technologies. Furthermore, in order to mitigate the shortage of available resources in frequency, the usage of opportunistic spectrum access mechanisms are proposed to make use of underutilized resources in other wireless systems. This opportunistic access applies to macrocellular environments, where again the location algorithm is an essential tool, and femtocellular environments. Additionally, implementation details of the necessary coordination mechanisms and performance evaluation results are provided. El estándar Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) representa la evoluci...

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Comparison among Cognitive Radio Architectures for Spectrum Sensing

Cited by 14 publications

References 18 publications

Optimal classifier based spectrum sensing in cognitive radio wireless systems

Optimal classifier based spectrum sensing in cognitive radio wireless systems

Implementing opportunistic spectrum access in LTE-advanced

Planificación y Optimización Automática de Redes Móviles LTE

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