Les télécommunications sans fil ont connu ces dernières années un immense succès à tel point que le spectre des fréquences est désormais surchargé et nécessite la disponibilité de nouvelles ressources. Pour répondre à ce besoin, des techniques de réutilisation dynamique du spectre ont alors vu le jour sous la dénomination de radio cognitive. Elles consistent à partager de manière opportuniste et efficace certaines fréquences ayant été initialement allouées à d'autres systèmes. Cette thèse se place dans le contexte de réseaux sans fil tactiques hétérogènes comportant des segments de radios cognitives. La difficulté provient alors de la garantie de qualité de service de bout en bout : respect du débit négocié, du délai et de la gigue. Nous nous sommes tout d'abord intéressés au contrôle d'admission dans ce type de réseaux en proposant une méthode de calcul de bande passante résiduelle de bout en bout s'appuyant sur un algorithme de complexité polynomiale et pouvant être implanté de manière distribuée. Nous nous sommes ensuite concentrés sur le routage en proposant une nouvelle métrique tenant compte des particularités de ce type de réseaux. Enfin, nous nous focalisons sur la thématique du routage à contraintes multiples en étudiant et implantant en environnement réel des algorithmes d'approximation proposés dans la littérature. / The unprecedented success of wireless telecommunication systems has resulted in the wireless spectrum becoming a scarce resource. Cognitive Radio systems have been proposed as the enabling technology allowing unlicensed equipments to opportunistically access the licensed spectrum when not in use by the licensed users. The focus of this thesis is on heterogeneous tactical networks deploying cognitive radios in parts or in their entirety. Such networks can be organized in multiple sub-networks, each characterized by a specific topology, medium access scheme and spectrum access policy. As a result, providing end-to-end Quality of Service guarantees in terms of bandwidth, delay and jitter, emerges as a key challenge. We first address the admission control in multi-hop cognitive radio networks and propose a polynomial time algorithm that can be implemented in a distributed fashion for estimating the end-to-end bandwidth. Then, we focus on routing and propose a new metric that takes into account the specifics of such networks. Finally, as quality of service requirements can be expressed using multiple metrics, we turn our attention to multi-constrained routing and implement on a real testbed low complexity approximation algorithms.

Considerando a atual subutilização do espectro de rádio frequências para comunicação sem fio, o rádio cognitivo é visto como um conceito chave para permitir uma melhoria da utilização deste recurso de comunicação. A implementação de dispositivos de rádio cognitivo deve basear-se nas quatro principais funções cognitivas: sensoriamento espectral, decisão espectral, compartilhamento espectral e mobilidade espectral. Através dessas funções, um dispositivo de rádio cognitivo é capaz de procurar canais livres para transmitir de forma oportunista em uma rede de rádios cognitivos. No entanto, as redes de rádios cognitivos devem ser gerenciadas, com o objetivo de garantir seu pleno funcionamento, melhorando o desempenho destes dispositivos. Este gerenciamento deve melhorar o conhecimento do administrador sobre o funcionamento da rede. Assim, a configuração, o monitoramento e a visualização das funções cognitivas são fundamentais para o processo de aprendizagem contínua do administrador de rede. Neste trabalho, propõe-se Kitsune, um sistema de gerenciamento com base em um modelo hierárquico que permite gerenciar as informações sobre as funções cognitivas em redes de rádios cognitivos. Kitsune é projetado para gerenciar todas as quatro funções cognitivas, permitindo que o administrador da rede possa configurar os dispositivos de rádio cognitivo, monitorar os resultados de cada função cognitiva e analisar importantes visualizações destes resultados. Além disso, um protótipo de Kitsune foi desenvolvido e avaliado por meio de um cenário experimental baseado na norma IEEE 802.22. O resultado obtido mostra que Kitsune fornece ao administrador um melhor conhecimento sobre a rede, melhorando a taxa de transferência média para cada canal. / Considering the current underutilization of radio frequency spectrum for wireless communication, the Cognitive Radio is seen as a key concept to enable the improvement of the radio frequency spectrum utilization. The implementation of cognitive radio devices must be based on the four main cognitive functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Through these functions, a cognitive radio device is able to search for vacant channels to opportunistically transmit in a cognitive radio network. However, cognitive radio networks should be managed, aiming to guaranty the proper operation of the cognitive radio devices, improving the performance of these devices. This management should improve the administrator knowledge about the cognitive radio network operation. Therefore, the configuration, monitoring and visualization of the cognitive functions are fundamental to the continuous knowledge building process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about cognitive functions in radio networks. Kitsune is designed to manage all four cognitive functions, enabling the network administrator to configure the cognitive radio devices, monitor the results of each cognitive function, and make important visualizations of these results. Moreover, a Kitsune prototype was developed and evaluated through an experimental IEEE 802.22 scenario. The result obtained show that Kitsune allows the administrator to achieve a better knowledge about the network and improve the average throughput for each channel.

With the rapid proliferation of new wireless communication devices and services, the demand for the radio spectrum is increasing at a rapid rate, which leads to making the spectrum more and more crowded. The limited available spectrum and the inefficiency in the spectrum usage have led to the emergence of cognitive radio (CR) and dynamic spectrum access (DSA) technologies, which enable future wireless communication systems to exploit the empty spectrum in an opportunistic manner. To do so, future wireless devices should be aware of their surrounding radio environment in order to adapt their operating parameters according to the real-time conditions of the radio environment. From this viewpoint, spectrum sensing is becoming increasingly important to new and future wireless communication systems, which is designed to monitor the usage of the radio spectrum and reliably identify the unused bands to enable wireless devices to switch from one vacant band to another, thereby achieving flexible, reliable, and efficient spectrum utilisation. This thesis focuses on issues related to local and cooperative spectrum sensing for CR networks, which need to be resolved. These include the problems of noise uncertainty and detection in low signal to noise ratio (SNR) environments in individual spectrum sensing. In addition to issues of energy consumption, sensing delay and reporting error in cooperative spectrum sensing. In this thesis, we investigate how to improve spectrum sensing algorithms to increase their detection performance and achieving energy efficiency. To this end, first, we propose a new spectrum sensing algorithm based on energy detection that increases the reliability of individual spectrum sensing. In spite of the fact that the energy detection is still the most common detection mechanism for spectrum sensing due to its simplicity. Energy detection does not require any prior knowledge of primary signals, but has the drawbacks of threshold selection, and poor performance due to noise uncertainty especially at low SNR. Therefore, a new adaptive optimal energy detection algorithm (AOED) is presented in this thesis. In comparison with the existing energy detection schemes the detection performance achieved through AOED algorithm is higher. Secondly, as cooperative spectrum sensing (CSS) can give further improvement in the detection reliability, the AOED algorithm is extended to cooperative sensing; in which multiple cognitive users collaborate to detect the primary transmission. The new combined approach (AOED and CSS) is shown to be more reliable detection than the individual detection scheme, where the hidden terminal problem can be mitigated. Furthermore, an optimal fusion strategy for hard-fusion based cognitive radio networks is presented, which optimises sensing performance. Thirdly, the need for denser deployment of base stations to satisfy the estimated high traffic demand in future wireless networks leads to a significant increase in energy consumption. Moreover, in large-scale cognitive radio networks some of cooperative devices may be located far away from the fusion centre, which causes an increase in the error rate of reporting channel, and thus deteriorating the performance of cooperative spectrum sensing. To overcome these problems, a new multi-hop cluster based cooperative spectrum sensing (MHCCSS) scheme is proposed, where only cluster heads are allowed to send their cluster results to the fusion centre via successive cluster heads, based on higher SNR of communication channel between cluster heads. Furthermore, in decentralised CSS as in cognitive radio Ad Hoc networks (CRAHNs), where there is no fusion centre, each cognitive user performs the local spectrum sensing and shares the sensing information with its neighbours and then makes its decision on the spectrum availability based on its own sensing information and the neighbours’ information. However, cooperation between cognitive users consumes significant energy due to heavy communications. In addition to this, each CR user has asynchronous sensing and transmission schedules which add new challenges in implementing CSS in CRAHNs. In this thesis, a new multi-hop cluster based CSS scheme has been proposed for CRAHNs, which can enhance the cooperative sensing performance and reduce the energy consumption compared with other conventional decentralised cooperative spectrum sensing modes.

Considerando a atual subutilização do espectro de rádio frequências para comunicação sem fio, o rádio cognitivo é visto como um conceito chave para permitir uma melhoria da utilização deste recurso de comunicação. A implementação de dispositivos de rádio cognitivo deve basear-se nas quatro principais funções cognitivas: sensoriamento espectral, decisão espectral, compartilhamento espectral e mobilidade espectral. Através dessas funções, um dispositivo de rádio cognitivo é capaz de procurar canais livres para transmitir de forma oportunista em uma rede de rádios cognitivos. No entanto, as redes de rádios cognitivos devem ser gerenciadas, com o objetivo de garantir seu pleno funcionamento, melhorando o desempenho destes dispositivos. Este gerenciamento deve melhorar o conhecimento do administrador sobre o funcionamento da rede. Assim, a configuração, o monitoramento e a visualização das funções cognitivas são fundamentais para o processo de aprendizagem contínua do administrador de rede. Neste trabalho, propõe-se Kitsune, um sistema de gerenciamento com base em um modelo hierárquico que permite gerenciar as informações sobre as funções cognitivas em redes de rádios cognitivos. Kitsune é projetado para gerenciar todas as quatro funções cognitivas, permitindo que o administrador da rede possa configurar os dispositivos de rádio cognitivo, monitorar os resultados de cada função cognitiva e analisar importantes visualizações destes resultados. Além disso, um protótipo de Kitsune foi desenvolvido e avaliado por meio de um cenário experimental baseado na norma IEEE 802.22. O resultado obtido mostra que Kitsune fornece ao administrador um melhor conhecimento sobre a rede, melhorando a taxa de transferência média para cada canal. / Considering the current underutilization of radio frequency spectrum for wireless communication, the Cognitive Radio is seen as a key concept to enable the improvement of the radio frequency spectrum utilization. The implementation of cognitive radio devices must be based on the four main cognitive functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Through these functions, a cognitive radio device is able to search for vacant channels to opportunistically transmit in a cognitive radio network. However, cognitive radio networks should be managed, aiming to guaranty the proper operation of the cognitive radio devices, improving the performance of these devices. This management should improve the administrator knowledge about the cognitive radio network operation. Therefore, the configuration, monitoring and visualization of the cognitive functions are fundamental to the continuous knowledge building process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about cognitive functions in radio networks. Kitsune is designed to manage all four cognitive functions, enabling the network administrator to configure the cognitive radio devices, monitor the results of each cognitive function, and make important visualizations of these results. Moreover, a Kitsune prototype was developed and evaluated through an experimental IEEE 802.22 scenario. The result obtained show that Kitsune allows the administrator to achieve a better knowledge about the network and improve the average throughput for each channel.

abstract: Dynamic channel selection in cognitive radio consists of two main phases. The first phase is spectrum sensing, during which the channels that are occupied by the primary users are detected. The second phase is channel selection, during which the state of the channel to be used by the secondary user is estimated. The existing cognitive radio channel selection literature assumes perfect spectrum sensing. However, this assumption becomes problematic as the noise in the channels increases, resulting in high probability of false alarm and high probability of missed detection. This thesis proposes a solution to this problem by incorporating the estimated state of channel occupancy into a selection cost function. The problem of optimal single-channel selection in cognitive radio is considered. A unique approach to the channel selection problem is proposed which consists of first using a particle filter to estimate the state of channel occupancy and then using the estimated state with a cost function to select a single channel for transmission. The selection cost function provides a means of assessing the various combinations of unoccupied channels in terms of desirability. By minimizing the expected selection cost function over all possible channel occupancy combinations, the optimal hypothesis which identifies the optimal single channel is obtained. Several variations of the proposed cost-based channel selection approach are discussed and simulated in a variety of environments, ranging from low to high number of primary user channels, low to high levels of signal-to-noise ratios, and low to high levels of primary user traffic. / Dissertation/Thesis / M.S. Electrical Engineering 2014

Considerando a atual subutilização do espectro de rádio frequências para comunicação sem fio, o rádio cognitivo é visto como um conceito chave para permitir uma melhoria da utilização deste recurso de comunicação. A implementação de dispositivos de rádio cognitivo deve basear-se nas quatro principais funções cognitivas: sensoriamento espectral, decisão espectral, compartilhamento espectral e mobilidade espectral. Através dessas funções, um dispositivo de rádio cognitivo é capaz de procurar canais livres para transmitir de forma oportunista em uma rede de rádios cognitivos. No entanto, as redes de rádios cognitivos devem ser gerenciadas, com o objetivo de garantir seu pleno funcionamento, melhorando o desempenho destes dispositivos. Este gerenciamento deve melhorar o conhecimento do administrador sobre o funcionamento da rede. Assim, a configuração, o monitoramento e a visualização das funções cognitivas são fundamentais para o processo de aprendizagem contínua do administrador de rede. Neste trabalho, propõe-se Kitsune, um sistema de gerenciamento com base em um modelo hierárquico que permite gerenciar as informações sobre as funções cognitivas em redes de rádios cognitivos. Kitsune é projetado para gerenciar todas as quatro funções cognitivas, permitindo que o administrador da rede possa configurar os dispositivos de rádio cognitivo, monitorar os resultados de cada função cognitiva e analisar importantes visualizações destes resultados. Além disso, um protótipo de Kitsune foi desenvolvido e avaliado por meio de um cenário experimental baseado na norma IEEE 802.22. O resultado obtido mostra que Kitsune fornece ao administrador um melhor conhecimento sobre a rede, melhorando a taxa de transferência média para cada canal. / Considering the current underutilization of radio frequency spectrum for wireless communication, the Cognitive Radio is seen as a key concept to enable the improvement of the radio frequency spectrum utilization. The implementation of cognitive radio devices must be based on the four main cognitive functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Through these functions, a cognitive radio device is able to search for vacant channels to opportunistically transmit in a cognitive radio network. However, cognitive radio networks should be managed, aiming to guaranty the proper operation of the cognitive radio devices, improving the performance of these devices. This management should improve the administrator knowledge about the cognitive radio network operation. Therefore, the configuration, monitoring and visualization of the cognitive functions are fundamental to the continuous knowledge building process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about cognitive functions in radio networks. Kitsune is designed to manage all four cognitive functions, enabling the network administrator to configure the cognitive radio devices, monitor the results of each cognitive function, and make important visualizations of these results. Moreover, a Kitsune prototype was developed and evaluated through an experimental IEEE 802.22 scenario. The result obtained show that Kitsune allows the administrator to achieve a better knowledge about the network and improve the average throughput for each channel.

In this thesis, the spectrum and energy efficiency of cooperative spectrum prediction (CSP) in cognitive radio networks are investigated. In addition, the performance of CSP is evaluated using a hidden Markov model (HMM) and a multilayer perceptron (MLP) neural network. The cooperation between secondary users in predicting the next channel status employs AND, OR and majority rule fusion schemes. These schemes are compared for HMM and MLP predictors as a function of channel occupancy in terms of prediction error, spectrum efficiency and energy efficiency. The impact of busy and idle state prediction errors on the spectrum efficiency is determined. Further, the spectrum efficiency is compared for different numbers of primary users (PUs). Simulation results are presented which show a significant improvement in the spectrum efficiency using CSP with the majority rule at the cost of a small degradation in energy efficiency compared to single spectrum prediction (SSP) and traditional spectrum sensing (TSS). The HMM predictor provides better performance than the MLP predictor. Moreover, the total probability of prediction error with the majority rule provides the best performance compared to SSP and the other fusion rules. On the other hand, the AND and OR rules have the worst performance in the high and low traffic cases, respectively. The majority rule provides a good tradeoff between busy and idle state prediction errors compared with the AND and OR rules and SSP. Further, a reduction in the busy state prediction error increases the SE more compared to a reduction in the idle state prediction error. / Graduate

The demand of wireless spectrum is increasing very fast as the field of telecommunication is advancing rapidly. The spectrum was underutilized because of fixed spectrum assignment policy and this valuable spectrum can be utilized efficiently by cognitive radio technology. In this thesis we have studied spectrum selection problems in cognitive radio network. Channel sharing and channel contention problems arise when multiple secondary users tend to select same channel. The thesis work is focused on spectrum selection issue with the aim to minimize the overall system time and to solve the problem of channel contention and channel sharing. The overall system time of secondary connection is an important performance measure to provide quality of service for secondary users in cognitive radio network. We studied two spectrum selection schemes that considerably reduce the overall system time and resolve the problems of channel sharing and channel contention. An analytical model associated with Preemptive Resume Priority (PRP) M/G/1 queuing model has been provided to evaluate the studied spectrum selection scheme. This model also analyzes the effect of multiple handoffs due to arrival of primary users. According to this scheme, the traffic load is distributed among multiple channels to balance the traffic load. Secondary users select the operating channels based on the spectrum selection algorithm. They can intelligently adopt better channel selection scheme by considering traffic statistics and overall transmission time. All simulation scenarios are developed in MATLAB. Based on our result we can conclude that both channel selection schemes considerably reduce the overall transmission time of secondary users in cognitive radio network. The overall transmission time increase with the rise of arrival rate of secondary user. The probability based channel selection scheme perform better with lower arrival rate and sensing based channel selection scheme perform better with higher arrival rate of secondary users. These channel selection schemes help distribute the traffic load of secondary users evenly among multiple channels. Hence, increase the channel utilization and resolve the channel contention problem.

The work presented in this thesis concerns one of the key enabling techniques related to cognitive radio functionalities which is spectrum sensing as well as cooperative spectrum sensing. As cooperative spectrum sensing (CSS) approaches are commonly used for combating fading and improving detection performance, their performances using different combining rules have been analyzed. Due to the low implementation complexity, Goodness of Fit based spectrum sensing has been studied for cognitive radio applications. Motivated by its nice features of local sensing, a distributed consensus spectrum sensing for CR, has been presented, integrating a Goodness of Fit based spectrum sensing scheme. / Le travail présenté dans cette thèse concerne l'une des techniques clés dans les fonctionnalités de la radio cognitive qui est la détection du spectre ainsi que la détection coopérative du spectre. La détection coopérative est couramment utilisée pour la lutte contre l’évanouissement du canal à fin d'améliorer les performances de la détection. Les performances de la détection coopérative en utilisant différentes règles de fusion ont été analysées. En raison sa simplicité, la détection du spectre par les testes d’adéquation a été étudiée pour les applications de la radio cognitive. Motivé par la caractéristique d’être indépendant de bruit, ces testes d’adéquation ont été utilisés pour la détection locale, pour la détection coopérative distribuée. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Resource allocation consists in allocating spectrum and power on every link of a network, possibly under power and rate requirements. In the context of cognitive radios, almost 15 years of research produced an impressive amount of theoretical contributions, exploring a wide range of possibilities. However, despite the ever-growing list of imaginable scenarios, we observe in Chapter 2 that most of these studies are based on similar working hypotheses. Our first contribution is to challenge some of these hypotheses, and propose a novel resource allocation scheme. Sticking to realistic assumptions, we show how our scheme reduces both computational complexity and control traffic, compared to other state-of-the-art techniques.<p><p>Due to a majority of the abovementioned studies making some constraining assumptions, realistic system designs and experimental demonstrations are much more quiet and unharvested fields. In an effort to help this transition from theory to practice, our second contribution is a four-nodes cognitive network demonstrator, presented in Chapter 3. In particular, we aim at providing a modular platform available for further open collaboration: different options for spectrum sensing, resource allocation, synchronisation and others can be experimented on this demonstrator. As an example, we develop a simple protocol to show that our proposed resource allocation scheme is fully implementable, and that primary users can be avoided using our approach.<p><p>Chapter 4 aims at removing another working hypothesis made when developping our resource allocation scheme. Indeed, resource alloca- tion is traditionally a Media Access Control (MAC) layer problem. This means that when solving a resource allocation problem in a network, the routing paths are usually assumed to be known. Conversely, the routing problem, which is a network layer issue, usually assumes that the available capacities on each link of the network (which depend on resource allocation) are known. Nevertheless, these two problems are mathematically entangled, and a cross-layer allocation strategy can best decoupled approaches in several ways, as we discuss in Chapter 4. Accordingly, our third and last contribution is to develop such a cross-layer allocation scheme for the scenario proposed in previous chapters.<p><p>All conclusions are summarised in Chapter 5, which also points to a few tracks for future research. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished