Joint Resource Allocation for eICIC in Heterogeneous Networks

Interference coordination between high-power macros and low-power picos deeply impacts the performance of heterogeneous networks (HetNets). It should deal with three challenges: user association with macros and picos, the amount of almost blank subframe (ABS) that macros should reserve for picos, and resource block (RB) allocation strategy in each eNB. We formulate the three issues jointly for sum weighted logarithmic utility maximization while maintaining proportional fairness of users. A class of distributed algorithms are developed to solve the joint optimization problem. Our framework can be deployed for enhanced inter-cell interference coordination (eICIC) in existing LTE-A protocols. Extensive evaluation are performed to verify the effectiveness of our algorithms.Comment: Accepted by Globecom 201

A distributed power-saving framework for LTE HetNets exploiting Almost Blank Subframes

Almost Blank Subframes (ABSs) have been defined in LTE as a means to coordinate transmissions in heterogeneous networks (HetNets), composed of macro and micro eNodeBs: the macro issues ABS periods, and refrains from transmitting during ABSs, thus creating interference-free subframes for the micros. Micros report their capacity demands to the macro via the X2 interface, and the latter provisions the ABS period accordingly. Existing algorithms for ABS provisioning usually share resources proportionally among HetNet nodes in a long-term perspective (e.g., based on traffic forecast). We argue instead that this mechanism can be exploited to save power in the HetNet: in fact, dur-ing ABSs, the macro consumes less power, since it only transmits pilot signals. Dually, the micros may inhibit data transmission themselves in some subframes, and optimally decide when to do this based on knowledge of the ABS period. This allows us to define a power saving framework that works in the short term, mod-ifying the ABS pattern at the fastest possible pace, serving the HetNet traffic at reduced power cost. Our framework is designed using only standard signaling. Simulations show that the algorithm consumes less power than its competitors, especially at low loads, and improves the UE QoS

A distributed power-saving framework for LTE Het-Nets exploiting Almost Blank Subframes

Almost Blank Subframes (ABS) have been defined in LTE as a means to coordinate transmissions in heterogeneous networks (HetNets), composed of macro and micro eNodeBs: the macro issues ABS periods, and refrains from transmitting during ABSs, thus creating interference-free subframes for the micros. Micros report their capacity demands to the macro via the X2 interface, and the latter provisions the ABS period accordingly. Existing algorithms for ABS provisioning usually share resources proportionally among HetNet nodes in a long-term perspective (e.g., based on traffic forecast). We argue instead that this mechanism can be exploited to save power in the HetNet: in fact, during ABSs, the macro consumes less power, since it only transmits pilot signals. Dually, the micros may inhibit data transmission themselves in some subframes, and optimally decide when to do this based on knowledge of the ABS period. This allows us to define a power saving framework that works in the short term, modifying the ABS pattern at the fastest possible pace, serving the HetNet traffic at reduced power cost. Our framework is designed using only standard signaling. Simulations show that the algorithm consumes less power than its competitors, especially at low loads, and improves the UE QoS

Capacity Enhancement Approaches for Long Term Evolution networks: Capacity Enhancement-Inspired Self-Organized Networking to Enhance Capacity and Fairness of Traffic in Long Term Evolution Networks by Utilising Dynamic Mobile Base-Stations

The long-term evolution (LTE) network has been proposed to provide better network capacity than the earlier 3G network. Driven by the market, the conventional LTE (3G) network standard could not achieve the expectations of the international mobile telecommunications advanced (IMT-Advanced) standard. To satisfy this gap, the LTE-Advanced was introduced with additional network functionalities to meet up with the IMT-Advanced Standard. In addition, due to the need to minimize operational expenditure (OPEX) and reduce human interventions, the wireless cellular networks are required to be self-aware, self-reconfigurable, self-adaptive and smart. An example of such network involves transceiver base stations (BTSs) within a self-organizing network (SON). Besides these great breakthroughs, the conventional LTE and LTE-Advanced networks have not been designed with the intelligence of scalable capacity output especially in sudden demographic changes, namely during events of football, malls, worship centres or during religious and cultural festivals. Since most of these events cannot be predicted, modern cellular networks must be scalable in terms of capacity and coverage in such unpredictable demographic surge. Thus, the use of dynamic BTSs is proposed to be used in modern and future cellular networks for crowd and demographic change managements. Dynamic BTSs are complements of the capability of SONs to search, determine and deploy less crowded/idle BTSs to densely crowded cells for scalable capacity management. The mobile BTSs will discover areas of dark coverages and fill-up the gap in terms of providing cellular services. The proposed network relieves the LTE network from overloading thus reducing packet loss, delay and improves fair load sharing. In order to trail the best (least) path, a bio-inspired optimization algorithm based on swarm-particle optimization is proposed over the dynamic BTS network. It uses the ant-colony optimization algorithm (ACOA) to find the least path. A comparison between an optimized path and the un-optimized path showed huge gain in terms of delay, fair load sharing and the percentage of packet loss

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

Intelligence in 5G networks

Over the past decade, Artificial Intelligence (AI) has become an important part of our daily lives; however, its application to communication networks has been partial and unsystematic, with uncoordinated efforts that often conflict with each other. Providing a framework to integrate the existing studies and to actually build an intelligent network is a top research priority. In fact, one of the objectives of 5G is to manage all communications under a single overarching paradigm, and the staggering complexity of this task is beyond the scope of human-designed algorithms and control systems. This thesis presents an overview of all the necessary components to integrate intelligence in this complex environment, with a user-centric perspective: network optimization should always have the end goal of improving the experience of the user. Each step is described with the aid of one or more case studies, involving various network functions and elements. Starting from perception and prediction of the surrounding environment, the first core requirements of an intelligent system, this work gradually builds its way up to showing examples of fully autonomous network agents which learn from experience without any human intervention or pre-defined behavior, discussing the possible application of each aspect of intelligence in future networks