Resource Allocation Schemes for Multiuser Wireless Communication Systems Powered by Renewable Energy Sources

In the future cyber-physical systems, such as smart grids, a large amount of sensors will be distributively deployed in di erent locations throughout the systems for the purpose of monitoring and control. Conventionally, sensors are powered by xed energy supplies, e.g., regular batteries, which can provide stable energy output. However, such energy sources require periodical recharging or replacement, which incurs high maintenance cost and may become impractical in hazardous environments. Self-sustaining devices powered by energy harvesting (EH) sources are thus highly desirable. However, energy provided by energy harvesters is uctuating over time and thus introduces the EH constraints to the systems, i.e., the total energy consumed until an arbitrary time cannot be larger than the harvested amount up to this time, which invokes the need of advanced power control and scheduling schemes. This thesis studies both the o ine and online resource allocation strategies for wireless communication systems empowered by EH sources. First, the resource allocation problems for a Gaussian multiple access channel (MAC), where the two transmitters are powered by a shared energy harvester, are studied. For both in nite and nite battery capacity cases, the optimal o ine resource allocation schemes for maximising the weighted sum throughput over a nite time horizon are derived. It is proved that there exists a capping rate for the user with stronger channel gain. Moreover, the duality property between the MAC with a shared energy harvester and its dual broadcast channel powered is demonstrated. Numerical results are presented to compare the performance of several online schemes. Moreover, the utility of a greedy scheme against the optimal o ine one is measured by using competitive analysis technique, where the competitive ratios of the online greedy scheme, i.e., the maximum ratios between the pro ts obtained by the o ine and online schemes over arbitrary energy arrival pro les, are derived. Then, the resource allocation schemes for the Gaussian MAC with conferencing links, where the two transmitters could talk to each other via some wired rate-limited channels and share a common EH source, are studied. The optimal o ine resource allocations are developed for both in nite and nite battery cases. It is shown that the optimal resource allocation in this scenario is more complicated than in the traditional MAC scenario and there exists a capping rate at one of the two transmitters, depending on the weighting factors. Online resource allocation strategies are also examined. Numerical results are used to illustrate the performance comparison of the online schemes. Furthermore, the competitive ratios of the online greedy scheme are derived under di erent weighting factors.China Scholarship Counci

Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Models and Methods for Network Selection and Balancing in Heterogeneous Scenarios

The outbreak of 5G technologies for wireless communications can be considered a response to the need for widespread coverage, in terms of connectivity and bandwidth, to guarantee broadband services, such as streaming or on-demand programs offered by the main television networks or new generation services based on augmented and virtual reality (AR / VR). The purpose of the study conducted for this thesis aims to solve two of the main problems that will occur with the outbreak of 5G, that is, the search for the best possible connectivity, in order to offer users the resources necessary to take advantage of the new generation services, and multicast as required by the eMBMS. The aim of the thesis is the search for innovative algorithms that will allow to obtain the best connectivity to offer users the resources necessary to use the 5G services in a heterogeneous scenario. Study UF that allows you to improve the search for the best candidate network and to achieve a balance that allows you to avoid congestion of the chosen networks. To achieve these two important focuses, I conducted a study on the main mathematical methods that made it possible to select the network based on QoS parameters based on the type of traffic made by users. A further goal was to improve the computational computation performance they present. Furthermore, I carried out a study in order to obtain an innovative algorithm that would allow the management of multicast. The algorithm that has been implemented responds to the needs present in the eMBMS, in realistic scenarios

Traffic offloading in future, heterogeneous mobile networks

The rise of third-party content providers and the introduction of numerous applications has been driving the growth of mobile data traffic in the past few years. In order to tackle this challenge, Mobile Network Operators (MNOs) aim to increase their networks' capacity by expanding their infrastructure, deploying more Base Stations (BSs). Particularly, the creation of Heterogeneous Networks (HetNets) and the application of traffic offloading through the dense deployment of low-power BSs, the small cells (SCs), is one promising solution to address the aforementioned explosive data traffic increase. Due to their financial implementation requirements, which could not be met by the MNOs, the emergence of third parties that deploy small cell networks creates new business opportunities. Thus, the investigation of frameworks that facilitate the implementation of outsourced traffic offloading, the collaboration and the transactions among MNOs and third-party small cell owners, as well as the provision of participation incentives for all stakeholders is essential for the deployment of the necessary new infrastructure and capacity expansion. The aforementioned emergence of third-party content providers and their applications not only drives the increase in mobile data traffic, but also create new Quality of Service (QoS) as well as Quality of Experience (QoE) requirements that the MNOs need to guarantee for the satisfaction of their subscribers. Moreover, even though the MNOs accommodate this traffic, they do not get any monetary compensation or subsidization for the required capacity expansion. On the contrary, their revenues reduce continuously. To that end, it is necessary to research and design network and economic functionalities adapted to the new requirements, such as QoE-aware Radio Resource Management and Dynamic Pricing (DP) strategies, which both guarantee the subscriber satisfaction and maximization the MNO profit (to compensate the diminished MNOs' revenues and the increasing deployment investment). Following a thorough investigation of the state-of-the-art, a set of research directions were identified. This dissertation consists of contributions on network sharing and outsourced traffic offloading for the capacity enhancement of MNO networks, and the design of network and economic functions for the sustainable deployment and use of the densely constructed HetNets. The contributions of this thesis are divided into two main parts, as described in the following. The first part of the thesis introduces an innovative approach on outsourced traffic offloading, where we present a framework for the Multi-Operator Radio Access Network (MORAN) sharing. The proposed framework is based on an auction scheme used by a monopolistic Small Cell Operator (SCO), through which he leases his SC infrastructure to MNOs. As the lack of information on the future offered load and the auction strategies creates uncertainty for the MNOs, we designed a learning mechanism that assists the MNOs in their bid-placing decisions. Our simulations show that our proposal almost maximizes the social welfare, satisfying the involved stakeholders and providing them with participation incentives. The second part of the thesis researches the use of network and economic functions for MNO profit maximization, while guaranteeing the users' satisfaction. Particularly, we designed a model that accommodates a plethora of services with various QoS and QoE requirements, as well as diverse pricing, that is, various service prices and different charging schemes. In this model, we proposed QoE-aware user association, resource allocation and joint resource allocation and dynamic pricing algorithms, which exploit the QoE-awareness and the network's economic aspects, such as the profit. Our simulations have shown that our proposals gain substantial more profit compared to traditional and state-of-the-art solutions, while providing a similar or even better network performance.El aumento de los proveedores de contenido de terceros y la introducción de numerosas aplicaciones ha impulsado el crecimiento del tráfico de datos en redes móviles en los últimos años. Para hacer frente a este desafío, los operadores de redes móviles (Mobile Network Operators, MNOs) apuntan a aumentar la capacidad de sus redes mediante la expansión de su infraestructura y el despliegue de más estaciones base (BS). Particularmente, la creación de Redes Heterogéneas (Heterogenous Networks, HetNets) y la aplicación de descarga de tráfico a través del despliegue denso de BSs de baja potencia, las células pequeñas (small cells, SCs), es una solución prometedora para abordar el aumento del tráfico de datos explosivos antes mencionado. Debido a sus requisitos de implementación financiera, que los MNO no pudieron cumplir, la aparición de terceros que implementan redes de células pequeñas crea nuevas oportunidades comerciales. Por lo tanto, la investigación de marcos que faciliten la implementación de la descarga tercerizada de tráfico, la colaboración y las transacciones entre MNOs y terceros propietarios de células pequeñas, así como la provisión de incentivos de participación para todas las partes interesadas esencial para el despliegue de la nueva infraestructura necesaria y la expansión de la capacidad. La aparición antes mencionada de proveedores de contenido de terceros y sus aplicaciones no solo impulsa el aumento del tráfico de datos móviles, sino también crea nuevos requisitos de calidad de servicio (Quality of Service, QoS) y calidad de la experiencia (Quality of Experience, QoE) que los operadores de redes móviles deben garantizar para la satisfacción de sus suscriptores. Además, a pesar de que los operadores de redes móviles adaptan este tráfico, no obtienen ninguna compensación monetaria o subsidio por la expansión de capacidad requerida. Por el contrario, sus ingresos se reducen continuamente. Para ello, es necesario investigar y diseñar funcionalidades económicas y de red adaptadas a los nuevos requisitos, tales como las estrategias QoE-conscientes de gestión de recursos de radio y de precios dinámicos (Dynamic Pricing, DP), que garantizan la satisfacción del abonado y la maximización de la ganancia de operador móvil (para compensar los ingresos de los MNOs disminuidos y la creciente inversión de implementación). Después de una investigación exhaustiva del estado del arte, se identificaron un conjunto de direcciones de investigación. Esta disertación consiste en contribuciones sobre el uso compartido de redes y la descarga tercerizada de tráfico para la mejora de la capacidad de redes MNO, y el diseño de funciones económicas y de red para el despliegue y uso sostenible de las HetNets densamente construidas. Las contribuciones de esta tesis se dividen en dos partes principales, como se describe a continuación. La primera parte de la tesis presenta un enfoque innovador sobre la descarga subcontratada de tráfico, en el que presentamos un marco para el uso compartido de la red de acceso de radio de múltiples operadores (Multi-Operator RAN, MORAN). El marco propuesto se basa en un esquema de subasta utilizado por un operador monopólico de celda pequeña (Small Cell Operator, SCO), a través del cual arrienda su infraestructura SC a MNOs. Como la falta de información sobre la futura carga de red y las estrategias de subasta creaban incertidumbre para los MNO, diseñamos un mecanismo de aprendizaje que asiste a los MNO en sus decisiones de colocación de pujas. Nuestras simulaciones muestran que nuestra propuesta casi maximiza el bienestar social, satisfaciendo a las partes interesadas involucradas y proporcionándoles incentivos de participación. La segunda parte de la tesis investiga el uso de las funciones económicas y de red para la maximización de los beneficios de los MNOs, al tiempo que garantiza la satisfacción de los usuarios. Particularmente, diseñamos un modelo que acomoda una gran cantidad de servicios con diversos requisitos de QoS y QoE, tanto como diversos precios, es decir, varios precios de servicio y diferentes esquemas de cobro. En este modelo, propusimos algoritmos QoE-conscientes para asociación de usuarios, asignación de recursos y conjunta asignación de recursos y de fijación dinámica de precios, que explotan la conciencia de QoE y los aspectos económicos de la red, como la ganancia. Nuestras simulaciones han demostrado que nuestras propuestas obtienen un beneficio sustancial en comparación con las soluciones tradicionales y del estado del arte, a la vez que proporcionan un rendimiento de red similar o incluso mejor.Postprint (published version