À partir du cas des dispositifs d’ouverture sociale lancés en France et en Angleterre, cette thèse aborde la question des effets des institutions d’élite sur les processus de stratification sociale, dans un contexte d’internationalisation de l’enseignement supérieur. En nous concentrant sur la mise en œuvre de ces dispositifs, nous avons apporté trois éclairages sur ce débat : - Le travail d’ajustement des institutions repose sur leur capacité à instituer des liens d’interdépendance, qui assurent une cohésion autour de la lecture commune des inégalités sociales. Plus précisément, les institutions contribuent à affecter le fonctionnement des politiques éducatives en matière d’ouverture sociale, en promouvant des modes de coopération entre des « univers » qui s’ignoraient relativement auparavant. - Par ailleurs, le travail d’ajustement engendre des changements dans les processus de certification. Il conduit les institutions à promouvoir de nouvelles conventions de jugement comme le potentiel. - Enfin, le travail des institutions concerne aussi leur capacité à transmettre des normes scolairement légitimes dans le cadre d’espaces de socialisation anticipatrice, comme le tutorat. La comparaison des dispositifs entre les deux pays étudiés souligne la convergence dans le traitement et la temporalité des ajustements. Alors que la question de la diversification des élites apparaît comme spécifique à chaque espace national, l’analyse comparée souligne l’existence de traits communs entre les institutions et l’impact de l’internationalisation sur cette question.Cette thèse porte sur les cas de Sciences Po, de l’ESSEC et de l’Université d’Oxford. / Widening participation programmes have been launched simultaneously in both France and England in the 2000s. They stem from the idea that it is necessary for elite universities, despite their traditional mission of elite education, to get involved in the field of antidiscrimination and thus develop measures to increase equality of opportunity and diversify their student body. This thesis highlights the impact of these programmes on the way to address social inequalities in the educational sector. In fact, widening participation schemes contribute to the dissemination of a new interpretation of social mobility on the basis of a compensation targeting talented pupils (Pupils identified as “with potential”) rather than sustaining the most deprived of them. It is allowed by the current withdrawal of the traditional role of the Welfare state in education (in a context of financial crisis) which increases the pressure on universities (through financial incentives), in the name of their social responsibility towards society. This work is based on an ethnographic survey led in three French and English elite institutions, including the University of Oxford, Sciences Po and ESSEC.

Las redes inal´ambricas actuales exhiben caracter´ısticas heterog´eneas de acceso m´ultiple mediante el despliegue, la coexistencia y la cooperaci´on de varias Tecnolog ´ıas de Acceso Radio (RAT2). En este escenario, la prestaci´on de servicios multimedia garantizando una cierta calidad de servicio (QoS3) es obligatoria. El objetivo global de las redes heterog´eneas de acceso inal´ambrico consiste en sustentar la realizaci´on del concepto ABC (del ingl´es Always Best Connected), en el que un usuario est´a siempre conectado a la RAT que mejor satisface sus necesidades de servicio en cualquier momento, en cualquier lugar, de cualquier modo. En este sentido, las estrat´egias de gesti´on de recursos radio comunes [del ingl´es, Common Radio Resource Management (CRRM)] se dise˜nan para proporcionar una utilizaci´on eficiente de los recursos radio y de espectro radioel´ectrico dentro de la red heterog´enea, ofreciendo un mejor rendimiento en comparaci´on con la realizaci´on independiente de RRM en cada RAT. Adem´as, los recursos de espectro asignados a cada una de las RATs deben ser utilizado de manera eficiente, ya que se trata de un recurso escaso y costoso. En este sentido, conceptos y metodolog´ıas de radio cognitiva (del ingl´es Cognitive Radio o CR) se han aplicado a la gesti´on del espectro, permitiendo una compartici´on dinamico-oportunista del mismo. En estos casos, el espectro sujeto a licencia se abre hacia el acceso de usuarios sin licencia siempre que no perjudiquen y que el funcionamiento libre de interferencias est´e garantizado. Esta tesis analiza estrategias de gesti´on de recursos radio y de espectro para ofrecer un uso mayor y eficiente de los escasos recursos radio y de espectro con el objetivo final de aumentar al m´aximo la capacidad de usuario, garantizando los requerimientos de QoS. En concreto, estas tesis se centra primero en como seleccionar una RAT al inicio de una llamada/sesi´on (en adelante, selecci´on inicial de RAT) en una red de acceso heterog´enea. Un modelo de Markov ha sido desarrollado para definir la asignaci´on de m´ultiples servicios (multi-servicio) en m´ultiples RATs (multi-acceso). En este marco, varias pol´ıticas de selecci´on de RAT son propuestas y evaluadas, gen´ericamente clasific´andose en pol´ıticas basadas en servicio (SB4) y basadas en balanceo de carga (LB5). Adem´as, el rendimiento de las pol´ıticas de selecci´on de RATs en escenarios de acceso limitado debido a la deficiente cobertura radio, la falta de disponibilidad de terminales multi-modo y la incompatibilidad entre RAT y servicios tambi´en es evaluada. Principios espec´ıficos para la asignaci´on de servicios a RATs ser´an provistos en los escenarios antes mencionados con el objetivo general de aumentar la capacidad de usuarios, garantizando los requisitos m´ınimos de calidad de servicio. Finalmente, la congesti´on en el acceso radio tambi´en se trata en este escenario multi-acceso/multi-servicio y el impacto de la selecci´on de RAT evaluado. Los principios para la asignaci´on inicial de RAT con tal de evitar la congesti´on radio ser´an tambi´en proporcionados. En segundo lugar, esta tesis investiga sobre la forma de maximizar el uso eficiente del espectro sujeto a licencia (o licenciado) por medio del acceso din´amicooportunista de espectro a usuarios sin licencia. En este sentido, se concibe un modelo de Markov para captar el problema del uso compartido de espectro entre usuarios con y sin licencia. Un modelo basado en sensado de espectro se propone con el fin de detectar porciones de espectro no utilizados (en ingl´es white spaces) que pueden ser usados por los usuarios sin licencia mientras este siga libre. En este marco, los beneficios obtenidos de la compartici´on del espectro son investigados y las ventajas que implican evaluadas. En concreto, se eval´ua el rendimiento obtenido al ajustar el punto de funcionamiento (en ingl´es operating point ) del mecanismo de sensado, el cual determina los errores de no-detecci´on y falsa-alarma. Por otra parte, sistemas de canalizaci´on de espectro fijos versus adaptativos ser´an propuestos y analizados bajo dos disciplinas de servicio diferentes, cuya duraci´on (o tiempo de permanencia en el sistema) esta basada en tiempo y en contenido respectivamente. / Current wireless networks exhibit heterogeneous multi-access features by means of the coexisting and cooperative deployment of several Radio Access Technologies (RATs). In this scenario, the provision of multimedia services with ensured Quality of Service (QoS) is mandatory. The overall goal of heterogeneous wireless access networks is to enable the realization of the Always Best Connected concept in which a user is seamlessly connected to the RAT best suiting its service requirements anytime, anywhere, anyhow. In this sense, Common Radio Resource Management (CRRM) strategies are devoted to provide an efficient utilization of radio resources within the heterogeneous network offering improved performances as opposed to performing stand-alone RRM in each RAT. In addition, allocated spectrum resources to each RAT must be efficiently utilized since it is a scarce and expensive resource. In this respect, cognitive radio concepts and methodologies have been applied to spectrum management by enabling dynamic/opportunistic spectrum sharing. In these scenarios, licensed spectrum is opened towards unlicensed access provided a non-harmful operation is guaranteed. This dissertation discusses both radio resource and spectrum management strategies to provide an utmost and efficient use of scarce radio/spectrum resources with the overall goal of maximizing user capacity while guaranteeing QoS constraints.Specifically, the thesis is first focused on how to select an appropriate RAT upon call/session initiation (henceforth, initial RAT selection) in a heterogeneous access network. A Markovian framework is developed to such extent supporting the allocation of multiple service-type users (multi-service) on multiple RATs (multi-access). Under this framework, several RAT selection policies are proposed and evaluated, broadly categorized into service-based (SB) and load-balancing (LB). In addition, the performance of RAT selection policies in access-limited scenarios due to poor radio coverage, non multi-mode terminal availability and RAT-service incompatibility is also evaluated. Specific guiding principles for the allocation of services on several RATs are provided in the abovementioned scenarios with the overall goal of increasing user capacity while guaranteeing minimum QoS requirements. Finally, radio access congestion is also addressed in this multi-access/multi-service scenario and the impact RAT selection assessed. Suitable allocation principles avoiding congestion are also provided.Secondly, this dissertation investigates on how to efficiently maximize the use of licensed spectrum by means of dynamic/opportunistic unlicensed spectrum access. Hereof, a Markovian framework is also devised to capture the problem of licensed spectrum sharing towards unlicensed users. A sensing-based spectrum awareness model is proposed in order to detect unused spectrum (so-called white spaces) which may be accessed by unlicensed users while remaining unused. Under this framework, the benefits of spectrum sharing are investigated and the involved gains assessed. Specifically, the sensing-throughput tradeoff and the adjustment of the sensing mechanism’s operating point, which tradeoffs missed-detection and false-alarm errors, is evaluated. Moreover, fixed vs. adaptive spectrum channelization schemes are proposed and analyzed under two different service disciplines considering time-based and volume-based content delivery.

[pt] Sistemas multi-input multi-output (MIMO) massivos livres de células são uma variante de sistemas MIMO multi-celulares que consideram a ausência de células. Desta forma, a interferência entre as células é minimizada e a capacidade de cobertura do sistema é melhorada devido à menor distância entre os pontos de acesso (APs) e os usuários. É uma solução de comunicação MIMO massiva multi-usuário que envolve um número estendido de APs que podem ser equipados com tecnologia MIMO para fornecer serviço a usuários simultaneamente. Os APs são controlados por uma unidade central de processamento (CPU) para garantir a coordenação dentro da rede e para processamento e decodificação de informação. Possíveis arranjos para a arquitetura livre de células incluem esquemas centralizados e descentralizados. Para a configuração centralizada, os APs enviam todas as suas estimativas de canal e informações recebidas para a CPU por meio de enlaces de transporte frontais para processamento e detecção de sinais. Além disso, na arquitetura centralizada, os APs atuam como repetidores na rede. Outro nível de cooperação para sistemas MIMO massivos livre de células é o esquema descentralizado. Nesta proposta de tese, a arquitetura dos sistema MIMO massivos livres de células no canal reverso é estudada para as implementações centralizadas e descentralizadas. Em particular, estuda-se o desempenho de técnicas de mitigação de interferência para essas redes supondo-se conhecimento perfeito de canal e usando técnicas de detecção lineares e não lineares, seleção de APs, e esquemas iterativos de detecção e decodificação com códigos LDPC para melhorar o desempenho do sistema e reduzir a carga de sinalização. Para o caso em que há falta de compartilhamento de informações sobre os canais, o uso de pilotos para obter estimativas de canais é considerado e explorado. / [en] Cell-free massive multiple-input multiple-output (CF-mMIMO) is an advanced variant of network multiple-input multiple-output (MIMO) which considers absence of cell boundaries. Thus, the interference between cells in cellular systems is greatly minimised and the system s coverage capacity is improved due to the shorter distances between the access points (APs) and the users. It is a multi-user massive MIMO communications solution that involves an extended number of APs that can either be equipped with MIMO or single antennas to provide service to users simultaneously. The APs are controlled by a central processing unit (CPU) to ensure coordination within the network and for information processing and decoding. Possible arrangements for the CF-mMIMO architecture include, but are not limited to: centralized and decentralized schemes. In this thesis, the uplink of a CF-mMIMO system architecture is studied for the centralized and decentralized implementations. In particular, we study the performance of interference mitigation techniques for CF-mMIMO networks using iterative detection and decoding (IDD) schemes. The performance of the system is studied assuming perfect and imperfect channel state information (CSI). Access point selection based on the effective channel gain to make the network more practical and scalable are devised. The use of low-density parity check (LDPC) codes that adopt message passing has been investigated. Furthermore, log likelihood ratio (LLR) refinement strategies have been proposed to improve decentralized processing for CF-mMIMO networks. Finally, the performance of the considered schemes is analyzed theoretically and simulations are used to assess the performance in terms of BER, number of fronthaul signaling, and computational cost.

<p>The objective of the thesis research is to design such vertical handoff decision algorithms in order for mobile field workers and other mobile users equipped with contemporary multimode mobile devices to communicate seamlessly in the NGWN. In order to tackle this research objective, we used fuzzy logic and fuzzy inference systems to design a suitable handoff initiation algorithm that can handle imprecision and uncertainties in data and process multiple vertical handoff initiation parameters (criteria) / used the fuzzy multiple attributes decision making method and context awareness to design a suitable access network selection function that can handle a tradeoff among many handoff metrics including quality of service requirements (such as network conditions and system performance), mobile terminal conditions, power requirements, application types, user preferences, and a price model / used genetic algorithms and simulated annealing to optimise the access network selection function in order to dynamically select the optimal available access network for handoff / and we focused in particular on an interesting use case: vertical handoff decision between mobile WiMAX and UMTS access networks. The implementation of our handoff decision algorithm will provide a network selection mechanism to help mobile users select the best wireless access network among all available wireless access networks, that is, one that provides always best connected services to users.</p>

<p>The objective of the thesis research is to design such vertical handoff decision algorithms in order for mobile field workers and other mobile users equipped with contemporary multimode mobile devices to communicate seamlessly in the NGWN. In order to tackle this research objective, we used fuzzy logic and fuzzy inference systems to design a suitable handoff initiation algorithm that can handle imprecision and uncertainties in data and process multiple vertical handoff initiation parameters (criteria) / used the fuzzy multiple attributes decision making method and context awareness to design a suitable access network selection function that can handle a tradeoff among many handoff metrics including quality of service requirements (such as network conditions and system performance), mobile terminal conditions, power requirements, application types, user preferences, and a price model / used genetic algorithms and simulated annealing to optimise the access network selection function in order to dynamically select the optimal available access network for handoff / and we focused in particular on an interesting use case: vertical handoff decision between mobile WiMAX and UMTS access networks. The implementation of our handoff decision algorithm will provide a network selection mechanism to help mobile users select the best wireless access network among all available wireless access networks, that is, one that provides always best connected services to users.</p>

Philosophiae Doctor - PhD / The objective of the thesis research is to design such vertical handoff decision algorithms in order for mobile field workers and other mobile users equipped with contemporary multimode mobile devices to communicate seamlessly in the NGWN. In order to tackle this research objective, we used fuzzy logic and fuzzy inference systems to design a suitable handoff initiation algorithm that can handle imprecision and uncertainties in data and process multiple vertical handoff initiation parameters (criteria); used the fuzzy multiple attributes decision making method and context awareness to design a suitable access network selection function that can handle a tradeoff among many handoff metrics including quality of service requirements (such as network conditions and system performance), mobile terminal conditions, power requirements, application types, user preferences, and a price model; used genetic algorithms and simulated annealing to optimise the access network selection function in order to dynamically select the optimal available access network for handoff; and we focused in particular on an interesting use case: vertical handoff decision between mobile WiMAX and UMTS access networks. The implementation of our handoff decision algorithm will provide a network selection mechanism to help mobile users select the best wireless access network among all available wireless access networks, that is, one that provides always best connected services to users. / South Africa

Philosophiae Doctor - PhD / Seamless mobility is the missing ingredient needed to address the inefficient communication problems faced by the field workforces of service companies that are using field workforce automation solutions to streamline and optimise the operations of their field workforces in an increasingly competitive market place. The key enabling function for achieving seamless mobility and seamless service continuity is seamless handoffs across heterogeneous wireless access networks. A challenging issue in the multi-service next generation wireless network (NGWN) is to design intelligent and optimal vertical handoff decision algorithms, beyond traditional ones that are based on only signal strength, to determine when to perform a handoff and to provide optimal choice of access network technology among all available access networks for users equipped with multimode mobile terminals. The objective of the thesis research is to design such vertical handoff decision algorithms in order for mobile field workers and other mobile users equipped with contemporary multimode mobile devices to communicate seamlessly in the NGWN. In order to tackle this research objective, we used fuzzy logic and fuzzy inference systems to design a suitable handoff initiation algorithm that can handle imprecision and uncertainties in data and process multiple vertical handoff initiation parameters (criteria); used the fuzzy multiple attributes decision making method and context awareness to design a suitable access network selection function that can handle a tradeoff among many handoff metrics including quality of service requirements (such as network conditions and system performance), mobile terminal conditions, power requirements, application types, user preferences, and a price model; used genetic algorithms and simulated annealing to optimise the access network selection function in order to dynamically select the optimal available access network for handoff; and we focused in particular on an interesting use case: vertical handoff decision between mobile WiMAX and UMTS access networks. The implementation of our handoff decision algorithm will provide a network selection mechanism to help mobile users select the best wireless access network among all available wireless access networks, that is, one that provides always best connected services to users

Pour faire face à la croissance rapide du trafic mobile, différentes technologies d'accès radio (par exemple, HSPA, LTE, WiFi, et WiMAX) sont intégrées et gérées conjointement. Dans ce contexte, la sélection de TAR est une fonction clé pour améliorer les performances du réseau et l'expérience de l'utilisateur. Elle consiste à décider quelle TAR est la plus appropriée aux mobiles. Quand l'intelligence est poussée à la périphérie du réseau, les mobiles décident de manière autonome de leur meilleur TAR. Ils cherchent à maximiser égoïstement leur utilité. Toutefois, puisque les mobiles ne disposent d'aucune information sur les conditions de charge du réseau, leurs décisions peuvent conduire à une inefficacité de la performance. En outre, déléguer les décisions au réseau optimise la performance globale, mais au prix d'une augmentation de la complexité du réseau, des charges de signalisation et de traitement. Dans cette thèse, au lieu de favoriser une de ces deux approches décisionnelles, nous proposons un cadre de décision hybride: le réseau fournit des informations pour les mobiles pour mieux décider de leur TAR. Plus précisément, les utilisateurs mobiles choisissent leur TAR en fonction de leurs besoins et préférences individuelles, ainsi que des paramètres de coût monétaire et de QoS signalés par le réseau. En ajustant convenablement les informations du réseau, les décisions des utilisateurs répondent globalement aux objectifs de l'opérateur. Nous introduisons d'abord notre cadre de décision hybride. Afin de maximiser l'expérience de l'utilisateur, nous présentons une méthode de décision multicritère (MDMC) basée sur la satisfaction. Outre leurs conditions radio, les utilisateurs mobiles tiennent compte des paramètres de coût et de QoS, signalées par le réseau, pour évaluer les TAR disponibles. En comparaison avec les solutions existantes, notre algorithme répond aux besoins de l'utilisateur (par exemple, les demandes en débit, la tolérance de coût, la classe de trafic), et évite les décisions inadéquates. Une attention particulière est ensuite portée au réseau pour s'assurer qu'il diffuse des informations décisionnelles appropriées, afin de mieux exploiter ses ressources radio alors que les mobiles maximisent leur propre utilité. Nous présentons deux méthodes heuristiques pour dériver dynamiquement quoi signaler aux mobiles. Puisque les paramètres de QoS sont modulées en fonction des conditions de charge, l'exploitation des ressources radio s'est avérée efficace. Aussi, nous nous concentrons sur l'optimisation de l'information du réseau. La dérivation des paramètres de QoS est formulée comme un processus de décision semi-markovien, et les stratégies optimales sont calculées en utilisant l'algorithme de Policy Iteration. En outre, et puisque les paramètres du réseau ne peuvent pas être facilement obtenues, une approche par apprentissage par renforcement est introduite pour dériver quoi signaler aux mobiles. / To cope with the rapid growth of mobile broadband traffic, various radio access technologies (e.g., HSPA, LTE, WiFi, and WiMAX) are being integrated and jointly managed. Radio Access Technology (RAT) selection, devoted to decide to what RAT mobiles should connect, is a key functionality to improve network performance and user experience. When intelligence is pushed to the network edge, mobiles make autonomous decisions regarding selection of their most appropriate RAT. They aim to selfishly maximize their utility. However, because mobiles have no information on network load conditions, their decisions may lead to performance inefficiency. Moreover, delegating decisions to the network optimizes overall performance, but at the cost of increased network complexity, signaling, and processing load. In this thesis, instead of favoring either of these decision-making approaches, we propose a hybrid decision framework: the network provides information for the mobiles to make robust RAT selections. More precisely, mobile users select their RAT depending on their individual needs and preferences, as well as on the monetary cost and QoS parameters signaled by the network. By appropriately tuning network information, user decisions are globally expected to meet operator objectives, avoiding undesirable network states. We first introduce our hybrid decision framework. Decision makings, on the network and user sides, are investigated. To maximize user experience, we present a satisfaction-based Multi-Criteria Decision-Making (MCDM) method. In addition to their radio conditions, mobile users consider the cost and QoS parameters, signaled by the network, to evaluate serving RATs. In comparison with existing MCDM solutions, our algorithm meets user needs (e.g., traffic class, throughput demand, cost tolerance), avoiding inadequate decisions. A particular attention is then addressed to the network to make sure it broadcasts suitable decisional information, so as to better exploit its radio resources while mobiles maximize their own utility. We present two heuristic methods to dynamically derive what to signal to mobiles. While QoS parameters are modulated as a function of the load conditions, radio resources are shown to be efficiently exploited. Moreover, we focus on optimizing network information. Deriving QoS parameters is formulated as a semi-Markov decision process, and optimal policies are computed using the Policy Iteration algorithm. Also, and since network parameters may not be easily obtained, a reinforcement learning approach is introduced to derive what to signal to mobiles. The performances of optimal, learning-based, and heuristic policies are analyzed. When thresholds are pertinently set, our heuristic method provides performance very close to the optimal solution. Moreover, although lower performances are observed, our learning-based algorithm has the crucial advantage of requiring no prior parameterization.