[SPA] Tradicionalmente, las agencias reguladoras han otorgado acceso a espectro radioeléctrico a través de licencias fijas y de largo plazo para grandes áreas geográficas. La creciente demanda de comunicación inalámbrica ha llevado a un espectro casi totalmente asignado. Sin embargo, es escaso y desigualmente utilizado. Una mejora dramática en la utilización del espectro es posible gracias a la operación de radios cognitivas, capaces de recopilar información sobre el entorno circundante del espectro y adaptar sus parámetros de transmisión en consecuencia. Las radios cognitivas permiten a los usuarios sin licencia explotar dinámicamente fragmentos no utilizados del espectro. Nuestra principal preocupación en este trabajo es proteger a los usuarios con licencia de las interferencias causadas por las transmisiones de los usuarios sin licencia y crear incentivos para que las redes con licencia implementen mecanismos que faciliten la coexistencia con usuarios sin licencia. Otra guía importante de nuestro trabajo es el enfoque en algoritmos de baja complejidad que pueden operar a la pequeña escala de tiempo de las oportunidades de espectro. Esta tesis enfatiza el uso de herramientas matemáticas como el modelado estocástico, la programación dinámica, el aprendizaje de refuerzo, entre otros, en el desarrollo de mecanismos de acceso al espectro dinámico. La primera parte de esta tesis se centra en el acceso oportunista al espectro (OSA), proponiendo esquemas que simultáneamente aumentan la eficiencia del espectro y mejoran la protección de los usuarios primarios. Los mecanismos desarrollados no requieren señalización directa entre los dispositivos primarios y secundarios. En la segunda parte, nos centramos en los incentivos, mediante el desarrollo de dos marcos para el comercio de espectro, en el que los usuarios con licencia pueden alquilar el ancho de banda no utilizado a los no licenciados, a cambio de dinero y servicios de retransmisión, respectivamente. También incluimos una extensa encuesta sobre el tema, única en su alcance. [ENG] Public regulatory agencies have traditionally granted access to radio-electric spectrum through fixed, long term licenses for large geographical areas. The increasing demand of wireless communication has led to an almost fully assigned spectrum. However, it is sparsely and unevenly used. A dramatic improvement on spectrum usage eciency is possible through the operation of cognitive radios, capable of gathering information about their surrounding spectrum environment and adapting their transmission parameters accordingly. Cognitive radios allow unlicensed users to dynamically exploit unused fragments of spectrum. Our main concern in this work is protecting licensed users from interferences caused by unlicensed users' transmissions, and creating incentives for the licensed networks to implement mechanisms easing the coexistence with unlicensed users. Another important guideline of our work is the focus on low-complexity algorithms that can operate at the small time-scale of the spectrum opportunities. This thesis emphasizes the use of mathematical tools such as stochastic modeling, dynamic programming, reinforcement learning, among others, in the development of mechanisms for dynamic spectrum access. The first part of this thesis focuses on Opportunistic Spectrum Access (OSA), proposing schemes that simultaneously increase spectrum eefficiency and improve the protection of primary users. The developed mechanisms do not require direct signaling between the primary and the secondary devices. In the second part, we focus on incentives, by developing two frameworks for spectrum trading, in which the licensed users can lease unused bandwidth to unlicensed ones, in exchange of money and relay services, respectively. We also include an extensive survey on the topic, unique in its scope.[ENG] Public regulatory agencies have traditionally granted access to radio-electric spectrum through fixed, long term licenses for large geographical areas. The increasing demand of wireless communication has led to an almost fully assigned spectrum. However, it is sparsely and unevenly used. A dramatic improvement on spectrum usage eciency is possible through the operation of cognitive radios, capable of gathering information about their surrounding spectrum environment and adapting their transmission parameters accordingly. Cognitive radios allow unlicensed users to dynamically exploit unused fragments of spectrum. Our main concern in this work is protecting licensed users from interferences caused by unlicensed users' transmissions, and creating incentives for the licensed networks to implement mechanisms easing the coexistence with unlicensed users. Another important guideline of our work is the focus on low-complexity algorithms that can operate at the small time-scale of the spectrum opportunities. This thesis emphasizes the use of mathematical tools such as stochastic modeling, dynamic programming, reinforcement learning, among others, in the development of mechanisms for dynamic spectrum access. The first part of this thesis focuses on Opportunistic Spectrum Access (OSA), proposing schemes that simultaneously increase spectrum eefficiency and improve the protection of primary users. The developed mechanisms do not require direct signaling between the primary and the secondary devices. In the second part, we focus on incentives, by developing two frameworks for spectrum trading, in which the licensed users can lease unused bandwidth to unlicensed ones, in exchange of money and relay services, respectively. We also include an extensive survey on the topic, unique in its scope.
Redes de ordenadores, Radiocomunicaciones
Networked Digital Library of Theses and Dissertations