Energy and throughput efficient strategies for heterogeneous future communication networks

As a result of the proliferation of wireless-enabled user equipment and data-hungry applications, mobile data traffic has exponentially increased in recent years.This in-crease has not only forced mobile networks to compete on the scarce wireless spectrum but also to intensify their power consumption to serve an ever-increasing number of user devices. The Heterogeneous Network (HetNet) concept, where mixed types of low-power base stations coexist with large macro base stations, has emerged as a potential solution to address power consumption and spectrum scarcity challenges. However, as a consequence of their inflexible, constrained, and hardware-based configurations, HetNets have major limitations in adapting to fluctuating traffic patterns. Moreover, for large mobile networks, the number of low-power base stations (BSs) may increase dramatically leading to sever power consumption. This can easily overwhelm the benefits of the HetNet concept. This thesis exploits the adaptive nature of Software-defined Radio (SDR) technology to design novel and optimal communication strategies. These strategies have been designed to leverage the spectrum-based cell zooming technique, the long-term evolution licensed assisted access (LTE-LAA) concept, and green energy, in order to introduce a novel communication framework that endeavors to minimize overall network on-grid power consumption and to maximize aggregated throughput, which brings significant benefits for both network operators and their customers. The proposed strategies take into consideration user data demands, BS loads, BS power consumption, and available spectrum to model the research questions as optimization problems. In addition, this thesis leverages the opportunistic nature of the cognitive radio (CR) technique and the adaptive nature of the SDR to introduce a CR-based communication strategy. This proposed CR-based strategy alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the introduced strategy takes into account user-related factors, such as user battery levels and user data types, and network-related factors, such as the number of unutilized bands and vulnerability level, and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solutions for the above-mentioned strategies, heuristic solutions were proposed and examined against existing solutions. The obtained results show that the proposed strategies can save energy consumption up to 18%, increase user throughput up to 23%, and achieve better spectrum utilization. Therefore, the proposed strategies offer substantial benefits for both network operators and users

Radio resource management strategies for interference mitigation in 4G heterogeneous wireless networks

The new era of mobile communications is dictated by the user demand for robust and high speed connections, data hungry applications and seamless connectivity. Operators and researchers all over the world are challenged to fulfill these requirements by providing enhanced coverage, increased capacity and efficient usage of the scarce spectrum. The introduction of the fourth generation systems (4G), LTE and LTE-A, have set the initiative for a technology evolution that offers new possibilities and is able to satisfy the user requirements and overcome the imposed challenges. However, and despite the improvements brought by the LTE and LTE-A systems, there are certain constraints that still need to be surpassed. LTE for example adopts innovating technologies, such as Orthogonal Frequency Division Multiplexing Access (OFDMA) that improves the spectral efficiency and reduces the Intra-Cell Interference. Nevertheless, Inter-Cell Interference (ICI) remains a constraining factor that can degrade the system capacity and limit the overall performance of the network. On that respect, Inter-Cell Interference Coordination (ICIC) techniques are adopted with target the interference mitigation. One of the limitations of these techniques is that follow static configurations lacking of flexibility and adaptation on network changes. Moreover, LTE-A employs enhanced and new techniques and involves alternative strategies. A promising solution lies on the introduction of Heterogeneous Networks (HetNets), which are networks that include low power small cells under the already existing macro cellular network and exploit several other technologies, such as WiFi. HetNets can further improve the network capacity, enhance the coverage and provide higher speed data transfer. However, due to the heterogeneous nature of the network, traditional methods for the user association, resource allocation and interference mitigation may not always be suitable since their design was based on homogeneous deployments. As such, new and enhanced methods are introduced, such as enhanced ICIC (eICIC), with their accompanied requirements and challenges. Motivated by the abovementioned aspects, this thesis has been focused on the study of ICIC and eICIC schemes, the identification of the related challenges, the enhancement of existing schemes and the proposal of novel solutions. In particular in the initial stages of the work, ICIC techniques have been studied and analyzed. A distributed algorithm that performs dynamic channel allocation has been developed for homogeneous deployments and extended later on to include heterogeneous networks. The solution has been optimized with the use of the Gibbs Sampler, while the setting of algorithm related parameters has been addressed through a detailed analysis. Moreover, a possible implementation of the solution has been presented in detail. The efficiency of the proposed schemes has been demonstrated through simulations and comparisons with benchmark schemes. In the next steps, the work has targeted eICIC techniques with purpose the investigation and analysis of the main constraining issues related to the user association, resource management and interference mitigation. Novel eICIC schemes that aim a better resource management and the overall capacity improvement have been developed and presented in detail, while the performance of the solutions has been shown through simulations and comparisons with reference schemes. Moreover, an optimized eICIC solution has been implemented based on genetic algorithms. Simulation results and comparisons with reference schemes have demonstrated the efficiency of the solution, while the selected configurations are discussed and analyzed.La nueva era de las comunicaciones móviles viene marcada por la demanda de los usuarios por conseguir conexiones robustas de alta velocidad que permitan soportar aplicaciones de datos de elevados requerimientos. El cumplimiento de estos requisitos conlleva la necesidad de mejorar la cobertura, incrementar la capacidad y utilizar el espectro eficientemente. La introducción de los sistemas de cuarta generación (4G), LTE y LTE-A, ha dado lugar a una tecnología que ofrece nuevas posibilidades y es capaz de satisfacer las necesidades de los usuarios y superar los retos impuestos. Sin embargo, y a pesar de las mejoras introducidas por estos sistemas, hay ciertas limitaciones que todavía tienen que ser superadas. LTE, por ejemplo, adopta tecnologías tales como OFDMA que mejora la eficiencia espectral y reduce la interferencia intracelular. Sin embargo, la interferencia intercelular (ICI) sigue siendo un factor limitante que puede degradar la capacidad del sistema y limitar el rendimiento global de la red. En ese sentido, se requieren técnicas de coordinación de interferencias intercelulares (ICIC) con el objetivo de mitigar dicha interferencia. Una de las limitaciones de estas técnicas es que siguen configuraciones estáticas que carecen de flexibilidad y capacidad de adaptación a los cambios de la red. Por otra parte, LTE-A introduce nuevas mejoras, como las redes heterogéneas (HetNets), que son redes que incluyen pequeñas células de baja potencia conjuntamente con la red macrocellular y también pueden explotar diferentes tecnologías, como WiFi. Las HetNets pueden mejorar aún más la capacidad de la red, mejorar la cobertura y facilitar la transferencia de datos de mayor velocidad. Sin embargo, debido a la naturaleza heterogénea de la red, los métodos tradicionales para la asociación de usuarios, asignación de recursos y reducción de la interferencia pueden no ser siempre adecuados, ya que su diseño se basó en despliegues homogéneos. En este sentido, es preciso introducir técnicas mejoradas de ICIC, denominadas en inglés eICIC (enhanced-ICIC), que involucran nuevos requerimientos y retos. En base a todos estos aspectos, esta tesis se ha centrado en el estudio de los sistemas de ICIC y eICIC en redes celulares, incluyendo la identificación de los retos relacionados con la mejora de los sistemas existentes y la propuesta de soluciones novedosas. En particular, en las etapas iniciales de la tesis se han estudiado y analizado las técnicas ICIC, y se ha desarrollado un algoritmo distribuido que realiza la asignación dinámica de canales para despliegues homogéneos, ampliándose posteriormente para su utilización en redes heterogéneas. La solución opera de forma optimizada mediante el uso de la técnica denominada Gibbs Sampler, mientras que el ajuste de parámetros relacionado con el algoritmo se ha abordado a través de un análisis detallado basado en simulaciones. Por otra parte, una posible implementación de la solución se ha presentado en detalle. La eficiencia de los esquemas propuestos se ha demostrado a través de simulaciones y comparaciones con sistemas de referencia. En los siguientes pasos, el trabajo se ha centrado en las técnicas eICIC con el propósito de investigar y analizar los principales problemas relacionadas con la asociación de usuarios, gestión de recursos y mitigación de la interferencia. A partir de aquí se han desarrollado nuevos esquemas de eICIC que tienen como objetivo una mejor gestión de los recursos y la mejora general de la capacidad. El rendimiento de las soluciones se ha demostrado a través de simulaciones y comparaciones con sistemas de referencia. Por otra parte, se ha propuesto una solución eICIC optimizada basada en algoritmos genéticos. La eficacia de dicha solución se ha demostrado mediante simulaciones, a la vez que se han analizado las diferentes configuraciones seleccionadas por el proceso de optimización.Postprint (published version

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected