In this dissertation, the performance of cooperative cognitive systems with spectrum sharing is investigated. A low-complexity and high performance node selection strategy is proposed for two different of cooperative cognitive systems models. In the first model, the secondary network is composed by one source node that communicates with one among L destinations through a direct link and also assisted by one among N AF or DF relays nodes. The selected secondary destination employs a selection combining technique for choosing the best link (direct or dual-hop link) from the secondary source. Considering an underlay spectrum sharing approach, the secondary communication is performed taking into account an interference constraint, where the overall transmit power is limited by the interference at the primary receiver as well as by the maximum transmission power available at the respective nodes. An asymptotic analysis is carried out, revealing that the diversity order of the considered system is not affected by the interference, and equals to L + N. In the second model, by its turn, the secondary network is composed by one source, N AF or DF relays, and one destination. However, it is assumed the presence of M primary receivers. A relay selection strategy is proposed with the aim of maximing the end-to-end signal-to-noise ratio and, at the same time, to satisfy the interference constraints imposed by these primary receivers. After the relay selection procedure is performed, the secondary destination chooses the best path (direct link or relaying link) by employing a selection combining scheme. An asymptotic analysis is carried out, revealing that the system diversity order equals to N + 1, and showing that it is not affected neither by the number of primary receivers nor by the interference threshold. A close-form expression and an approximation for the outage probability is derived for the DF and AF protocols, respectively. / Nesta dissertaÃÃo, o desempenho de sistemas cooperativos cognitivos com compartilhamento espectral à investigado. Uma estratÃgia de seleÃÃo de nÃs de baixa complexidade e alto desempenho à proposta para dois modelos distintos de redes cooperativas cognitivas. No primeiro modelo, a rede secundÃria à composta por um nà fonte que comunica-se com um dentre L nÃs destinos atravÃs de um link direto e atravÃs de um dentre N nÃs relays decodifica-e-encaminha (DF) ou amplifica-e-encaminha (AF). O nà destino secundÃrio selecionado emprega uma tÃcnica de combinaÃÃo por seleÃÃo para selecionar o melhor link (direto ou auxiliar) a partir da fonte secundÃria. Considerando um ambiente com compartilhamento espectral, tem-se que a comunicaÃÃo secundÃria à realizada levando em consideraÃÃo uma restriÃÃo de interferÃncia, na qual a potÃncia de transmissÃo à governada pela interferÃncia no receptor primÃrio bem como pela mÃxima potÃncia de transmissÃo dos respectivos nÃs secundÃrios. Uma anÃlise assintÃtica à realizada, revelando que a ordem de diversidade do sistema nÃo à afetada pela interferÃncia, sendo igual a L + N. Jà no segundo modelo, a rede secundÃria à composta por uma fonte, N relays DF ou AF e um nà destino, no entanto assume-se a presenÃa de M receptores primÃrios. A seleÃÃo do relay deve satisfazer as restriÃÃes de interferÃncia impostas por estes Ãltimos. ApÃs a seleÃÃo de relay ser realizada, o nà destino seleciona o melhor caminho (link direto ou link via relay) proveniente da fonte utilizando um combinador por seleÃÃo. Uma anÃlise assintÃtica à realizada, revelando que a ordem de diversidade do esquema proposto iguala a N + 1, o que mostra que a mesma nÃo à afetada nem pelo nÃmero de receptores primÃrios nem pelo limiar de interferÃncia. Uma expressÃo em forma fechada para a probabilidade de outage à obtida para ambos protocolos cooperativos. SimulaÃÃes Monte Carlo sÃo apresentadas com o intuito de validar as anÃlises propostas.

Recently, there has been an increasing demand for reliable, robust and high data rate communication systems that can counteract the limitations imposed by the scarcity of two fundamental resources for communications: bandwidth and power. In turn, cooperative communications has emerged as a new communication paradigm in which network nodes share their antennas and transmission resources for distributed data exchange and processing. Recent studies have shown that cooperative communications can achieve significant performance gains in terms of signal reliability, coverage area, and power savings when compared with conventional communication schemes. However, the merits of cooperative communications can only be exploited with efficient resource allocation in terms of bandwidth utilization and power control. Additionally, the limited network resources in wireless environments can lead rational network nodes to be selfish and aim at maximizing their own benefits. Therefore, assuming fully cooperative behaviors such as unconditionally sharing of one's resources to relay for other nodes is unjustified. On the other hand, a particular network node may try to utilize resources from other nodes and also share its own resources so as to improve its own performance, which in turn may prompt other nodes to behave similarly and thus promote cooperation. This dissertation aims to answer the following three questions: ``How can bandwidth-efficient multinode cooperative communications be achieved?'', ``How can optimal power allocation be achieved in a distributed fashion?'', and finally, ``How can network nodes dynamically interact with each other so as to promote cooperation?''. In turn, this dissertation focuses on three main problems of cooperation in ad-hoc wireless networks: (i) optimal node selection in network-coded cooperative communications, (ii) auction-based distributed power allocation in single- and multi-relay cooperative networks, and finally (iii) coalitional game-theoretic analysis and modeling of the dynamic interactions among the network nodes and their coalition formations. Bi-directional relay networks are first studied in a scenario where two source nodes are communicating with each other via a set of intermediate relay nodes. The symbol error rate performance and achievable cooperative diversity orders are studied. Additionally, the effect of timing synchronization errors on the symbol error rate performance is investigated. Moreover, a sum-of-rates maximizing optimal power allocation is proposed. Relay selection is also proposed to improve the total achievable rate and mitigate the effect of timing synchronization errors. Multinode cooperative communications are then studied through the novel concept of many-to-many space-time network coding. The symbol error rate performance under perfect and imperfect timing synchronization and channel state information is theoretically analyzed and the optimal power allocation that maximizes the total network rate is derived. Optimal node selection is also proposed to fully exploit cooperative diversity and mitigate timing offsets and channel estimation errors. Further, this dissertation investigates distributed power allocation for single-relay cooperative networks. The distributed power allocation algorithm is conceived as an ascending-clock auction where multiple source nodes submit their power demands based on an announced relay price and are efficiently allocated cooperative transmit power. It is analytically and numerically shown that the proposed ascending-clock auction-based distributed algorithm leads to efficient power allocation, enforces truth-telling, and maximizes the social welfare. A distributed ascending-clock auction-based power allocation algorithm is also proposed for multi-relay cooperative networks. The proposed algorithm is shown to converge to the unique Walrasian Equilibrium allocation which maximizes the social welfare when source nodes truthfully report their cooperative power demands. The proposed algorithm achieves the same performance as could be achieved by centralized control while eliminating the need for complete channel state information and signaling overheads. Finally, the last part of the dissertation studies altruistic coalition formation and stability in cooperative wireless networks. Specifically, the aim is to study the interaction between network nodes and design a distributed coalition formation algorithm so as to promote cooperation while accounting for cooperation costs. This involves an analysis of coalitions' merge-and-split processes as well as the impact of different cooperative power allocation criteria and mobility on coalition formation and stability. A comparison with centralized power allocation and coalition formation is also considered, where the proposed distributed algorithm is shown to provide reasonable tradeoff between network sum-rate and computational complexity. / Ph. D.

Collaborative Beamforming (CB) has been introduced in Wireless Sensor Networks (WSNs) context as a long-distance and power-efficient communication scheme. One challenge for CB is the randomness of sensor node locations where different network realizations result in different CB beampatterns. First, we study the effect of sensor node spatial distribution on the CB beampattern. The characteristics of the CB beampattern are derived for circular Gaussian distributed sensor nodes and compared with the case of uniform distributed sensor nodes. It is shown that the mainlobe behavior of the CB beampattern is essentially deterministic. This suggests that the average beampattern characteristics are suitable for describing the mainlobe of a sample beampattern. However, the CB beampattern sidelobes are random and highly depends on the particular sensor node locations. Second, we introduce the multi-link CB and address the problem of random sidelobes where high level sidelobes can cause unacceptable interference to unintended Base Stations or Access Points (BSs/APs). Centralized sidelobe control techniques are impractical for distributed sensor nodes because of the associated communication overhead for each sensor node. Therefore, we propose a node selection scheme as an alternative to the centralized sidelobe control which aims at minimizing the interference at unintended BSs/APs. Our algorithm is based on the use of the inherent randomness of the channels and a low feedback that approves/rejects tested random node combinations. The performance of the proposed algorithm is analyzed in terms of the average number of trials and the achievable interference suppression and transmission rate. Finally, we study CB with power control aiming at prolonging the lifetime of a cluster of sensor nodes in the WSN. The energy available at different sensor nodes may not be the same since different sensor nodes may perform different tasks and not equally frequently. CB with power control can be used to balance the individual sensor nodes' lifetimes. Thus, we propose a distributed algorithm for CB with power control that is based on the Residual Energy Information (REI) at each sensor node while achieving the required average SNR at the BS/AP. The effectiveness of the proposed CB with power control is illustrated by simulations. / Communications

No description available.

Les réseaux de capteurs sans fil est une technologie nouvelle dont les applications s'étendent sur plusieurs domaines: militaire, scientifique, médicale, industriel, etc. La collaboration entre les noeuds capteurs, caractérisés par des capacités minimales en termes de capture, de transmission, de traitement et d'énergie, est une nécessité pour réaliser des tâches aussi complexes que la collecte des données, le pistage des objets mobiles, la surveillance des zones sensibles, etc. La contrainte matérielle sur le développement des ressources énergétiques des noeuds capteurs est persistante. D'où la nécessité de l'optimisation logicielle dans les différentes couches de la pile protocolaire et du système d'exploitation des noeuds. Dans cette thèse, nous approchons le problème d'optimisation d'énergie pour les applications collaboratives via les méthodes de sélection des capteurs basées sur la prédiction et la corrélation des données issues du réseau lui-même. Nous élaborons plusieurs méthodes pour conserver les ressources énergétiques du réseau en utilisant la prédiction comme un moyen pour anticiper les actions des noeuds et leurs rôles afin de minimiser le nombre des noeuds impliqués dans la tâche en question. Nous prenons l'application de pistage d'objets mobiles comme un cas d'étude. Ceci, après avoir dresser un état de l'art des différentes méthodes et approches récentes utilisées dans ce contexte. Nous formalisons le problème à l'aide d'un programme linéaire à variables binaires dans le but de trouver une solution générale exacte. Nous modélisons ainsi le problème de minimisation de la consommation d'énergie des réseaux de capteurs sans fil, déployé pour des applications de collecte de données soumis à la contrainte de précision de données, appelé EMDP. Nous montrons que ce problème est NP-Complet. D'où la nécessité de solutions heuristiques. Comme solution approchée, nous proposons un algorithme de clustering dynamique, appelé CORAD, qui adapte la topologie du réseau à la dynamique des données capturées afin d'optimiser la consommation d'énergie en exploitant la corrélation qui pourrait exister entre les noeuds. Toutes ces méthodes ont été implémentées et testées via des simulations afin de montrer leur efficacité. / Wireless Sensor Networks is an emerging technology enabled by the recent advances in Micro-Electro-Mechanical Systems, that led to design tiny wireless sensor nodes characterized by small capacities of sensing, data processing and communication. To accomplish complex tasks such as target tracking, data collection and zone surveillance, these nodes need to collaborate between each others to overcome the lack of battery capacity. Since the development of the batteries hardware is very slow, the optimization effort should be inevitably focused on the software layers of the protocol stack of the nodes and their operating systems. In this thesis, we investigated the energy problem in the context of collaborative applications and proposed an approach based on node selection using predictions and data correlations, to meet the application requirements in terms of energy-efficiency and quality of data. First, we surveyed almost all the recent approaches proposed in the literature that treat the problem of energy-efficiency of prediction-based target tracking schemes, in order to extract the relevant recommendations. Next, we proposed a dynamic clustering protocol based on an enhanced version of the Distributed Kalman Filter used as a prediction algorithm, to design an energy-efficient target tracking scheme. Our proposed scheme use these predictions to anticipate the actions of the nodes and their roles to minimize their number in the tasks. Based on our findings issued from the simulation data, we generalized our approach to any data collection scheme that uses a geographic-based clustering algorithm. We formulated the problem of energy minimization under data precision constraints using a binary integer linear program to find its exact solution in the general context. We validated the model and proved some of its fundamental properties. Finally and given the complexity of the problem, we proposed and evaluated a heuristic solution consisting of a correlation-based adaptive clustering algorithm for data collection. We showed that, by relaxing some constraints of the problem, our heuristic solution achieves an acceptable level of energy-efficiency while preserving the quality of data.

Opportunistic selection algorithms have grown in importance as next generation wireless systems strive towards higher data rates and spectral efficiencies. For example, in orthogonal frequency division multiple access(OFDMA), the system bandwidth is divided into many sub channels. For each sub channel, the user with the highest channel gain is opportunistically assigned to it. .Likewise, in a multi-source, multi-destination (MSD) cooperative relay system, a relay node must be assigned for every source-destination (SD) pair. The assignment decisions are based on local channel knowledge and must be fast so as to maximize the time available for data transmission. We develop novel multiple access based splitting-based selection algorithms for OFDMA and MSD systems. These systems are unique in that the same user and relay can be the most suitable one for multiple sub channels and multiple SD pairs, respectively. For OFDMA systems, we propose an algorithm called Split Select that assigns for every sub channel the user with the highest channel gain over it. For MSD systems, we propose a contention-based en masse assignment (CBEA) algorithm that assigns to each SD pair a relay that is capable of aiding it. Both Split Select and CBEA are fast and scale well with the number of nodes. For example, Split Select requires just 2.2 slots, on average, to assign a sub channel to its best user even when there are an asymptotically large number of contending users. Likewise, CBEA often takes far less than one slot, on average, to assign a relay to each SD pair.

Dans cette thèse, les techniques de coopération ont été étudiées pour un canal multi-accès multi-relais composé d'au moins deux sources qui communiquent avec une seule destination à l'aide d'au moins deux nœuds de relayage en mode semi-duplex. Le multiplexage par répartition dans le temps est supposé. Tout d'abord, l’algorithme d’adaptation de lien est exécuté par l'ordonnanceur centralisé. Durant la première phase de transmission, les sources transmettent chacune à leur tour leur message respectif pendant des intervalles de temps consécutifs. Dans chaque intervalle de temps dans la deuxième phase, la destination planifie un nœud pour transmettre les redondances, mettant en œuvre un protocole coopératif d'Hybrid Automatic Repeat reQuest (HARQ), où les canaux de contrôle limités bidirectionnels sont disponibles depuis les sources et les relais vers la destination. Dans la première partie de la thèse, les stratégies de sélection des nœuds centralisé sont proposées pour la deuxième phase de transmission. Les décisions d’ordonnancement sont prises en fonction de la connaissance des ensembles de sources correctement décodées par chaque noeud et ayant comme objectif de maximiser l’efficacité spectrale moyenne. L'analyse de la probabilité de coupure de l'information ainsi que les simulations Monte-Carlo (MC) sont effectués afin de valider ces stratégies. Dans la seconde partie, un algorithme d’adaptation de lien lent est proposé afin de maximiser l’efficacité spectrale moyenne sous contrainte de vérification d'une qualité de service individuelle cible pour une famille donnée de schémas de modulation et de codage, réposant sur l'information sur la distribution des canaux signalée. Les débits des sources discrets sont déterminés en utilisant l’approche "Genie-Aided" suivie d’un algorithme itératif de correction de débit. Les simulations MC montrent que l’algorithme d’adaptation de lien proposé offre des performances proches de celles de la recherche exhaustive. Dans la troisième partie, les performances de protocole HARQ à redondance incrémentale (IR) avec codage mono et multi-utilisateur, ainsi que l'HARQ de type Chase Combining avec codage mono-utilisateur sont comparées. Les simulations MC montrent que l'IR-HARQ avec codage mono-utilisateur offre le meilleur compromis entre performance et complexité pour le scénario de petit nombre de sources. Un schéma de codage pratique est proposé et validé à l'aide de simulations MC. / In this thesis, cooperation techniques have been studied for Multiple Access Multiple Relay Channel, consisted of at least two sources which communicate with a single destination with the help of at least two half-duplex relaying nodes. Time Division Multiplexing is assumed. First, the link adaptation algorithm is performed at the centralised scheduler. Sources transmit in turns in consecutive time slots during the first transmission phase. In each time slot of the second phase, the destination schedules a node to transmit redundancies, implementing a cooperative Hybrid Automatic Repeat reQuest (HARQ) protocol, where bidirectional limited control channels are available from sources and relays towards the destination. In the first part of the thesis, centralized node selection strategies are proposed for the second phase. The scheduling decisions are made based on the knowledge of the correctly decoded source sets of each node, with the goal to maximize the average spectral efficiency. An information outage analysis is conducted and Monte-Carlo (MC) simulations are performed to evaluate their performance. In the second part, a slow-link adaptation algorithm is proposed which aims at maximizing the average spectral efficiency under individual QoS targets for a given modulation and coding scheme family relying on the reported Channel Distribution Information of all channels. Discrete source rates are first determined using the "Genie-Aided" assumption, which is followed by an iterative rate correction algorithm. The resulting link adaptation algorithm yields performance close to the exhaustive search approach as demonstrated by MC simulations. In the third part, performances of Incremental Redundancy (IR) HARQ with Single and Multi User encoding, as well as the Chase Combining HARQ with Single User encoding are compared. MC simulations demonstrate that IR-HARQ with Single User encoding offers the best trade-off between performance and complexity for a small number of sources in our setting. Practical coding scheme is proposed and validated using MC simulations.