One statement that we can make with absolute certainty in our current time is that wireless communication is now the standard and the de-facto type of communication. Cognitive radios are able to interpret the frequency spectrum and adapt. The aim of this work is to be able to predict whether a frequency channel is going to be busy or free in a specific time located in the future. To do this, the problem is modeled as a time series problem where each usage of a channel is treated as a sequence of busy and free slots in a fixed time frame. For this time series problem, the method being implemented is one of the latest, state-of-the-art, technique in machine learning for time series and sequence prediction: long short-term memory neural networks, or LSTMs.

Cognitive Radios are emerging communication systems which efficiently utilize the unused licensed radio spectrum called spectral holes. They run Spectrum sensing algorithms to identify these spectral holes. These holes need to be identified at very low SNR (<=-20 dB) under multipath fading, unknown channel gains and noise power. Cooperative spectrum sensing which exploits spatial diversity has been found to be particularly effective in this rather daunting endeavor. However despite many recent studies, several open issues need to be addressed for such algorithms. In this thesis we provide some novel cooperative distributed algorithms and study their performance. We develop an energy efficient detector with low detection delay using decentralized sequential hypothesis testing. Our algorithm at the Cognitive Radios employ an asynchronous transmission scheme which takes into account the noise at the fusion center. We have developed a distributed algorithm, DualSPRT, in which Cognitive Radios (secondary users) sequentially collect the observations, make local decisions and send them to the fusion center. The fusion center sequentially processes these received local decisions corrupted by Gaussian noise to arrive at a final decision. Asymptotically, this algorithm is shown to achieve the performance of the optimal centralized test, which does not consider fusion center noise. We also theoretically analyze its probability of error and average detection delay. Even though DualSPRT performs asymptotically well, a modification at the fusion node provides more control over the design of the algorithm parameters which then performs better at the usual operating probabilities of error in Cognitive Radio systems. We also analyze the modified algorithm theoretically. DualSPRT requires full knowledge of channel gains. Thus we extend the algorithm to take care the imperfections in channel gain estimates. We also consider the case when the knowledge about the noise power and channel gain statistic is not available at the Cognitive Radios. This problem is framed as a universal sequential hypothesis testing problem. We use easily implementable universal lossless source codes to propose simple algorithms for such a setup. Asymptotic performance of the algorithm is presented. A cooperative algorithm is also designed for such a scenario. Finally, decentralized multihypothesis sequential tests, which are relevant when the interest is to detect not only the presence of primary users but also their identity among multiple primary users, are also considered. Using the insight gained from binary hypothesis case, two new algorithms are proposed.

Common control channels in cognitive radio (CR) ad hoc networks are spectrum resources temporarily allocated and commonly available to CR users for control message exchange. With no presumably available network infrastructure, CR users rely on cooperation to perform spectrum management functions. One the one hand, CR users need to cooperate to establish common control channels, but on the other hand, they need to have common control channels to facilitate such cooperation. This control channel problem is further complicated by primary user (PU) activities, channel impairments, and intelligent attackers. Therefore, how to reliably and securely establish control links in CR ad hoc networks is a challenging problem. In this work, a framework for control channel design and analysis is proposed to address control channel reliability and security challenges for seamless communication and spectral efficiency in CR ad hoc networks. The framework tackles the problem from three perspectives: (i) responsiveness to PU activities: an efficient recovery control channel method is devised to efficiently establish control links and extend control channel coverage upon PU's return while mitigating the interference with PUs, (ii) robustness to channel impairments: a reinforcement learning-based cooperative sensing method is introduced to improve cooperative gain and mitigate cooperation overhead, and (iii) resilience to jamming attacks: a jamming-resilient control channel method is developed to combat jamming under the impacts of PU activities and spectrum sensing errors by leveraging intrusion defense strategies. This research is particularly attractive to emergency relief, public safety, military, and commercial applications where CR users are highly likely to operate in spectrum-scarce or hostile environment.

Les principaux objectifs des opérateurs ferroviaires visent à accroître la sécurité, réduire les coûts d’exploitation et de maintenance et augmenter l’attractivité et les bénéfices du transport ferroviaire en offrant de nouveaux services aux passagers. Ceci ne pourra être atteint que grâce à la multiplication des échanges de données entre les différents acteurs du monde ferroviaire. L’interopérabilité, l’efficacité spectrale, l’optimisation de l’usage des ressources radio et l’amélioration de la fiabilité des communications sont des exigences fortes pour les applications de télécommunication ferroviaires. Les recherches dans le domaine de la radio cognitive ont vu le jour afin de répondre aux besoins de communication de l’armée ainsi qu’aux besoins dans les secteurs de la sécurité publique. Ces domaines partagent souvent les mêmes exigences que les chemins de fers. Ainsi, la radio cognitive a montré un potentiel prometteur pour répondre aux besoins listés précédemment. Une des principales fonctionnalités d’un dispositif de radio cognitive est de prendre conscience de son environnement radioélectrique et de détecter les bandes disponibles. Trois principaux éléments définissent l’environnement de la radio cognitive : l’utilisateur, les règles d’accès au spectre radio et les domaines radio. Cette thèse met en avant plusieurs contributions relatives à la reconnaissance de l’environnement radiofréquence et la détection de bandes libres. Plus spécifiquement, ces contributions portent sur la reconnaissance par la radio cognitive de l’occupation du spectre et de la modulation des signaux présents dans les bandes analysées. Ces fonctions ont été conçues pour le contexte ferroviaire, c’est-à-dire la grande vitesse et un environnement électromagnétique difficile en présence de bruit impulsif. / An essential goal of railway operators is to increase safety, reduce operation and maintenance costs, and increase attraction and profit by offering new services to passengers. These objectives will be reached thanks to a huge increase of data fluxes exchanges between railways stakeholders and infrastructures.Interoperability, spectral efficiency, optimization of radio resource usages, and improvement of communications reliability are of significant interest for railway applications. The Cognitive Radio (CR) research has been successfully applied to meet the communication needs of the military as well as the public-safety sectors, which share many of the same needs as railway. CRs have shown significant promise to answer all of the previously listed requirements. One of the main capabilities of a CR device is to sense and finally become aware of its environment. Three major domains define the environment of the CR, namely, the user, policy, and radio domains. This thesis highlights several contributions to radio environment awareness of a CR device. More specifically, these contributions lie in the spectrum awareness and waveform awareness functions of the CR. We designed these functions for the railways context, that is, a high speed vehicular context, besides difficult electromagnetic environments resulting a heavy-tailed impulsive noise.

As more and more wireless applications/services emerge in the market, the already heavily crowded radio spectrum becomes much scarcer. Meanwhile, however,as it is reported in the recent literature, there is a large amount of radio spectrum that is under-utilized. This motivates the concept of cognitive radio wireless networks that allow the unlicensed secondary-users (SUs) to dynamically use the vacant radio spectrum which is not being used by the licensed primary-users (PUs). In this dissertation, we investigate protocol design for both the synchronous and asynchronous cognitive radio networks with emphasis on the medium access control (MAC) layer. We propose various spectrum sharing schemes, opportunistic packet scheduling schemes, and spectrum sensing schemes in the MAC and physical (PHY) layers for different types of cognitive radio networks, allowing the SUs to opportunistically utilize the licensed spectrum while confining the level of interference to the range the PUs can tolerate. First, we propose the cross-layer based multi-channel MAC protocol, which integrates the cooperative spectrum sensing at PHY layer and the interweave-based spectrum access at MAC layer, for the synchronous cognitive radio networks. Second, we propose the channel-hopping based single-transceiver MAC protocol for the hardware-constrained synchronous cognitive radio networks, under which the SUs can identify and exploit the vacant channels by dynamically switching across the licensed channels with their distinct channel-hopping sequences. Third, we propose the opportunistic multi-channel MAC protocol with the two-threshold sequential spectrum sensing algorithm for asynchronous cognitive radio networks. Fourth, by combining the interweave and underlay spectrum sharing modes, we propose the adaptive spectrum sharing scheme for code division multiple access (CDMA) based cognitive MAC in the uplink communications over the asynchronous cognitive radio networks, where the PUs may have different types of channel usage patterns. Finally, we develop a packet scheduling scheme for the PU MAC protocol in the context of time division multiple access (TDMA)-based cognitive radio wireless networks, which is designed to operate friendly towards the SUs in terms of the vacant-channel probability. We also develop various analytical models, including the Markov chain models, M=GY =1 queuing models, cross-layer optimization models, etc., to rigorously analyze the performance of our proposed MAC protocols in terms of aggregate throughput, access delay, and packet drop rate for both the saturation network case and non-saturation network case. In addition, we conducted extensive simulations to validate our analytical models and evaluate our proposed MAC protocols/schemes. Both the numerical and simulation results show that our proposed MAC protocols/schemes can significantly improve the spectrum utilization efficiency of wireless networks.

The cognitive radio-based wireless networks have been proposed as a promising technology to improve the utilization of the radio spectrum through opportunistic spectrum access. In this context, the cognitive radios opportunistically access the spectrum which is licensed to primary users when the primary user transmission is detected to be absent. For opportunistic spectrum access, the cognitive radios should sense the radio environment and allocate the spectrum and power based on the sensing results. To this end, in this thesis, I develop a novel cooperative spectrum sensing scheme for cognitive radio networks (CRNs) based on machine learning techniques which are used for pattern classification. In this regard, unsupervised and supervised learning-based classification techniques are implemented for cooperative spectrum sensing. Secondly, I propose a novel joint channel and power allocation scheme for downlink transmission in cellular CRNs. I formulate the downlink resource allocation problem as a generalized spectral-footprint minimization problem. The channel assignment problem for secondary users is solved by applying a modified Hungarian algorithm while the power allocation subproblem is solved by using Lagrangian technique. Specifically, I propose a low-complexity modified Hungarian algorithm for subchannel allocation which exploits the local information in the cost matrix. Finally, I propose a novel dynamic common control channel-based medium access control (MAC) protocol for CRNs. Specifically, unlike the traditional dedicated control channel-based MAC protocols, the proposed MAC protocol eliminates the requirement of a dedicated channel for control information exchange. / October 2015

Les systèmes de communications sans fil ne cessent de se multiplier pour devenir incontournables de nos jours. Cette croissance cause une augmentation de la demande des ressources spectrales, qui sont devenues de plus en plus rares. Afin de résoudre ce problème de pénurie de fréquences, Joseph Mitola III, en 2000, a introduit l'idée de l'allocation dynamique du spectre. Il définit ainsi le terme " Cognitive Radio " (Radio Intelligente), qui est largement pressenti pour être le prochain Big Bang dans les futures communications sans fil [1]. Dans le cadre de ce travail on s'intéresse à la problématique du spectrum sensing qui est la détection de présence des Utilisateurs Primaires dans un spectre sous licence, dans le contexte de la radio intelligente. L'objectif de ce travail est de proposer des méthodes de détection efficaces à faible complexité et/ou à faible temps d'observation et ceci en utilisant le minimum d'information a priori sur le signal à détecter. Dans la première partie on traite le problème de détection d'un signal aléatoire dans le bruit. Deux grandes méthodes de détection sont utilisées : la détection d'énergie ou radiomètre et la détection cyclostationnaire. Dans notre contexte, ces méthodes sont plus complémentaires que concurrentes. Nous proposons une architecture hybride de détection des bandes libres, qui combine la simplicité du radiomètre et la robustesse des détecteurs cyclostationnaires. Deux méthodes de détection sont proposées qui se basent sur cette même architecture. Grâce au caractère adaptatif de l'architecture, la détection évolue au cours du temps pour tendre vers la complexité du détecteur d'énergie avec des performances proches du détecteur cyclostationnaire ou du radiomètre selon la méthode utilisée et l'environnement de travail. Dans un second temps on exploite la propriété parcimonieuse de la Fonction d'Autocorrelation Cyclique (FAC) pour proposer un nouvel estimateur aveugle qui se base sur le compressed sensing afin d'estimer le Vecteur d'Autocorrelation Cyclique (VAC), qui est un vecteur particulier de la Fonction d'Autocorrelation Cyclique pour un délai fixe. On montre par simulation que ce nouvel estimateur donne de meilleures performances que celles obtenues avec l'estimateur classique, qui est non aveugle et ceci dans les mêmes conditions et en utilisant le même nombre d'échantillons. On utilise l'estimateur proposé, pour proposer deux détecteurs aveugles utilisant moins d'échantillons que nécessite le détecteur temporel de second ordre de [2] qui se base sur l'estimateur classique de la FAC. Le premier détecteur exploite uniquement la propriété de parcimonie du VAC tandis que le second détecteur exploite en plus de la parcimonie la propriété de symétrie du VAC, lui permettant ainsi d'obtenir de meilleures performances. Ces deux détecteurs outre qu'ils sont aveugles sont plus performants que le détecteur non aveugle de [2] dans le cas d'un faible nombre d'échantillons.

Made available in DSpace on 2014-12-17T14:56:19Z (GMT). No. of bitstreams: 1 ArthurDLL_DISSERT.pdf: 2517302 bytes, checksum: c3d693c770dc1c58bad5f378aba6d268 (MD5) Previous issue date: 2014-06-28 / The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures / O aumento da demanda por sistemas de comunica??o sem fio de alto desempenho tem evidenciado a inefici?ncia do atual modelo de aloca??o fixa do espectro de r?dio. Nesse contexto, o r?dio cognitivo surge como uma alternativa mais eficiente, ao proporcionar o acesso oportunista ao espectro, com a maior largura de banda poss?vel. Para garantir esses requisitos, ? necess?rio que o transmissor identifique as oportunidades de transmiss?o e que o receptor reconhe?a os par?metros definidos para o sinal de comunica??o. As t?cnicas que utilizam a an?lise cicloestacion?ria podem ser aplicadas tanto em problemas de sensoriamento espectral, quanto na classifica??o de modula??es, mesmo em ambientes de baixa rela??o sinal-ru?do (SNR). Entretanto, apesar da robustez, uma das principais desvantagens da cicloestacionariedade est? no elevado custo computacional para o c?lculo das suas fun??es. Este trabalho prop?e arquiteturas eficientes de obten??o de caracter?sticas cicloestacion?rias para serem empregadas no sensoriamento espectral e na classifica??o autom?tica de modula??es (AMC). No contexto do sensoriamento espectral, um algoritmo paralelizado para extrair as caracter?sticas cicloestacion?rias de sinais de comunica??o ? apresentado. O desempenho da paraleliza??o desse extrator de caracter?sticas ? avaliado atrav?s das m?tricas de speedup e efici?ncia paralela. A arquitetura de sensoriamento espectral ? analisada para diversas configura??es de probabilidades de falso alarme, n?veis de SNR e tempo de observa??o das modula??es BPSK e QPSK. No contexto da AMC, o perfil-alfa reduzido ? proposto como uma assinatura cicloestacion?ria calculada para um conjunto reduzido de frequ?ncia c?clicas. Essa assinatura ? validada por meio de uma arquitetura de classifica??o baseada no casamento de padr?es. A arquitetura para AMC ? investigada para as taxas de acerto obtidas para as modula??es AM, BPSK, QPSK, MSK e FSK, considerando diversos cen?rios de tempo de observa??o e n?veis de SNR. Os resultados num?ricos de desempenho obtidos neste trabalho demonstram a efici?ncia das arquiteturas propostas

Cognitive radio technology has been an important area of research in telecommunications for solving the problem of spectrum scarcity. That\'s because in addition to allowing dynamic allocation of the electromagnetic spectrum, cognitive radios must be able to identify the non cognitive user\'s transmission on the channel. This operation is only possible through the continuous sensing of the electromagnetic spectrum. In this context, this paper presents a detailed study on spectrum sensing, an important stage in cognitive radio technology. For the presentation of this work, a detailed study on software dened radio (SDR) was carried out, without which it would be impossible to work with cognitive radios, once they are implemented by means of SDR technology. It was also presented the tools GNU Radio and USRP, which together form a solution of SDR, through implementation of AM receivers. The theoretical foundations of spectrum sensing and blind source separation (BSS) are presented and then is made a detailed study of the use of BSS for spectral sensing. From the study of BSS, it is possible to use new metrics for decision making about the presence or the absence of a primary user in the channel. Throughout the study, simulations and implementations were conducted on MATLAB in order to perform various situations, and, nally, it is presented outcomes and conclusions reached during the work. / A tecnologia de rádio cognitivo tem sido uma importante área de pesquisa em telecomunicações para a solução do problema da escassez espectral. Isto porque, além de permitirem a alocação dinâmica do espectro eletromagnético, os rádios cognitivos devem ser capazes de identificar as transmissões de usuários não cognitivos no canal. Esta operação só é possível por meio do sensoriamento contínuo do espectro eletromagnético. Neste contexto, este trabalho apresenta um estudo detalhado sobre o sensoriamento de espectro, uma importante etapa da tecnologia de rádios cognitivos. Para a apresentação deste trabalho foi realizado um estudo detalhado a respeito de rádio definido por software (SDR), sem o qual não seria possível o trabalho com rádios cognitivos, uma vez que este é implementado por meio da tecnologia de SDR. Também foram apresentadas as ferramentas GNU Radio e USRP, que, juntas, formam uma solução de SDR, por meio de implementações de receptores AM. Os fundamentos teóricos de sensoriamento de espectro e separação cega de fontes (BSS) são apresentados e, em seguida, é realizado um estudo aprofundado do uso de BSS para o sensoriamento espectral. A partir do estudo de BSS, é possível utilizar novas métricas de decisão a respeito da presença ou não de um usuário primário no canal. Durante todo este trabalho foram realizadas implementações e simulações no MATLAB com a finalidade de executar diversas situações e, finalmente, são apresentados resultados verificados e conclusões obtidas neste trabalho. / Mestre em Ciências

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-02-16T09:52:46Z No. of bitstreams: 1 alamsilvamenezes.pdf: 8301590 bytes, checksum: aed618e30f38206da4bf4f329924f87e (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-02-26T12:30:53Z (GMT) No. of bitstreams: 1 alamsilvamenezes.pdf: 8301590 bytes, checksum: aed618e30f38206da4bf4f329924f87e (MD5) / Made available in DSpace on 2016-02-26T12:30:53Z (GMT). No. of bitstreams: 1 alamsilvamenezes.pdf: 8301590 bytes, checksum: aed618e30f38206da4bf4f329924f87e (MD5) Previous issue date: 2014-09-01 / A presente tese propõe soluções ao problema da explicitação do conteúdo espectral de processos estacionários e não estacionários, com aplicações na estimação de frequência, estimação da densidade espectral de potência e no monitoramento do espectro. A técnica de estimação de frequência proposta nesta tese, baseada na warped discrete Fourier transform, apresenta, de acordo com as simulações computacionais, o melhor desempenho frente às demais técnicas comparadas, atingindo o Cramer-Rao bound para uma ampla faixa de relação sinal ruído. Em relação a estimação da densidade espectral de potência, a Hartley Multitaper method, proposta nesta tese, apresenta desempenho similar à multitaper method, em termos da variância de estimação e da polarização do espectro, mas simpli cação de implementação. Uma técnica para monitoramento do espectro para sistemas power line communication é proposta, levando em consideração o conceito de quanta e a diversidade observada quando os sinais são aquisitados a partir da rede de energia elétrica e do ar. Baseando-se em sinais sintéticos, gerados em computador, assim como dados de medição do espectro, obtidos utilizando uma antena e o cabo de energia elétrica como elementos sensores, veri fica-se que o desempenho da técnica proposta supera a monitoração padrão, sobretudo quando a diversidade gerada pelo cabo e pela antena sobre o sinal monitorado é explorada na detecção. / This dissertation aims at discussing solutions to deal with spectral analysis of stationary and non-stationary processes for frequency estimation, power spectral density estimation and spectral monitoring applications. The frequency estimation techniques are assessed through computer simulations. The proposed technique for frequency estimation is based on warped discrete Fourier transform outperforms other techniques, achieving the Cramer-Rao Bound for a wide range of signal to noise ratio. Regarding the power spectral density estimation, the proposed Hartley Multitaper Method shows similar performance, in terms of variance of estimates and polarization spectrum; however, it can simplify the implementation complexity. The introduced spectrum sensing technique is based on quanta de nition and the diversity o ered by the signals acquired from the electric power grids and the air. Based on computer-generation data and those one obtained during a measurement campaign, which one in this thesis is evaluated using synthetic signals, generated by computer, as well as measurement data of the spectrum. The numerical results show that the proposed technique outperforms a previous technique and can attain the very detection ratio and the very low false alarm when the diversity yielded by electric power grid and air is exploited.