A modular web-based software solution for mobile networks planning, operation and optimization

Mobile networks management is increasingly critical due to heavy communications usage by customers and complex due to the multiple technologies and systems deployed. Thus, Mobile Network Operators (MNOs) are constantly looking for better software solutions and tools to help them increase network performance and manage their networks more efficiently. In this paper, we present a modular web-based software solution to tackle problems related to mobile network planning, operation and optimization. The solution is focused on a set of functional requirements carefully chosen to support the network life cycle management, from planning to Operation and Maintenance (OAM) and optimisation stages. Based on a 3-tier modular architecture and implemented using only open-source software, the solution handles multiple data sources (e.g., Drive Test (DT) and Performance Management (PM)) and multiple Radio Access Network (RAN) technologies. MNOs can explore all available data through a flexible and user-friendly web interface, that also includes map-based visualization of the network. Moreover, the solution incorporates a set of recently developed and validated RAN algorithms, supporting tasks of network diagnosis, optimization, and planning. Also, with the purpose of optimizing the network, MNOs can investigate network simulations, using the RAN algorithms, of how the network will behave under certain conditions, and visualize the outcome of those simulations.info:eu-repo/semantics/publishedVersio

Machine Learning at the Edge: A Data-Driven Architecture with Applications to 5G Cellular Networks

The fifth generation of cellular networks (5G) will rely on edge cloud deployments to satisfy the ultra-low latency demand of future applications. In this paper, we argue that such deployments can also be used to enable advanced data-driven and Machine Learning (ML) applications in mobile networks. We propose an edge-controller-based architecture for cellular networks and evaluate its performance with real data from hundreds of base stations of a major U.S. operator. In this regard, we will provide insights on how to dynamically cluster and associate base stations and controllers, according to the global mobility patterns of the users. Then, we will describe how the controllers can be used to run ML algorithms to predict the number of users in each base station, and a use case in which these predictions are exploited by a higher-layer application to route vehicular traffic according to network Key Performance Indicators (KPIs). We show that the prediction accuracy improves when based on machine learning algorithms that rely on the controllers' view and, consequently, on the spatial correlation introduced by the user mobility, with respect to when the prediction is based only on the local data of each single base station.Comment: 15 pages, 10 figures, 5 tables. IEEE Transactions on Mobile Computin

Handover Parameter Optimisation of a Cellular Network The Kenyan Case

Handover, also known as Handoff is a key procedure that ensures that the cellular users move freely through the network while still being connected and being offered quality services. It is an event taking place whenever a mobile node moves from one wireless cell to another, abandoning the connection with the first base station and getting attached to the second one.  Since its success rate is a key indicator of user satisfaction, it is vital that this procedure happens as fast and as seamlessly as possible. This paper aims to optimize the handover decision process of a cellular radio network for an in-vehicle mobile station. This is first by determining the optimal handover parameters then developing an algorithm that determines the best time to handover using the fuzzy logic system

Enhanced mobility management mechanisms for 5G networks

Many mechanisms that served the legacy networks till now, are being identified as being grossly sub-optimal for 5G networks. The reason being, the increased complexity of the 5G networks compared previous legacy systems. One such class of mechanisms, important for any wireless standard, is the Mobility Management (MM) mechanisms. MM mechanismsensure the seamless connectivity and continuity of service for a user when it moves away from the geographic location where it initially got attached to the network. In this thesis, we firstly present a detailed state of the art on MM mechanisms. Based on the 5G requirements as well as the initial discussions on Beyond 5G networks, we provision a gap analysis for the current technologies/solutions to satisfy the presented requirements. We also define the persistent challenges that exist concerning MM mechanisms for 5G and beyond networks. Based on these challenges, we define the potential solutions and a novel framework for the 5G and beyond MM mechanisms. This framework specifies a set of MM mechanisms at the access, core and the extreme edge network (users/devices) level, that will help to satisfy the requirements for the 5G and beyond MM mechanisms. Following this, we present an on demand MM service concept. Such an on-demand feature provisions the necessary reliability, scalability and flexibility to the MM mechanisms. It's objective is to ensure that appropriate resources and mobility contexts are defined for users who will have heterogeneous mobility profiles, versatile QoS requirements in a multi-RAT network. Next, in this thesis we tackle the problem of core network signaling that occurs during MM in 5G/4G networks. A novel handover signaling mechanism has been developed, which eliminates unnecessary handshakes during the handover preparation phase, while allowing the transition to future softwarized network architectures. We also provide a handover failure aware handover preparation phase signaling process. We then utilize operator data and a realistic network deployment to perform a comparative analysis of the proposed strategy and the 3GPP handover signaling strategy on a network wide deployment scenario. We show the benefits of our strategy in terms of latency of handover process, and the transmission and processing cost incurred. Lastly, a novel user association and resource allocation methodology, namely AURA-5G, has been proposed. AURA-5G addresses scenarios wherein applications with heterogeneous requirements, i.e., enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC), are present simultaneously. Consequently, a joint optimization process for performing the user association and resource allocation while being cognizant of heterogeneous application requirements, has been performed. We capture the peculiarities of this important mobility management process through the various constraints, such as backhaul requirements, dual connectivity options, available access resources, minimum rate requirements, etc., that we have imposed on a Mixed Integer Linear Program (MILP). The objective function of this established MILP problem is to maximize the total network throughput of the eMBB users, while satisfying the minimum requirements of the mMTC and eMBB users defined in a given scenario. Through numerical evaluations we show that our approach outperforms the baseline user association scenario significantly. Moreover, we have presented a system fairness analysis, as well as a novel fidelity and computational complexity analysis for the same, which express the utility of our methodology given the myriad network scenarios.Muchos mecanismos que sirvieron en las redes actuales, se están identificando como extremadamente subóptimos para las redes 5G. Esto es debido a la mayor complejidad de las redes 5G. Un tipo de mecanismo importante para cualquier estándar inalámbrico, consiste en el mecanismo de gestión de la movilidad (MM). Los mecanismos MM aseguran la conectividad sin interrupciones y la continuidad del servicio para un usuario cuando éste se aleja de la ubicación geográfica donde inicialmente se conectó a la red. En esta tesis, presentamos, en primer lugar, un estado del arte detallado de los mecanismos MM. Bas ándonos en los requisitos de 5G, así como en las discusiones iniciales sobre las redes Beyond 5G, proporcionamos un análisis de las tecnologías/soluciones actuales para satisfacer los requisitos presentados. También definimos los desafíos persistentes que existen con respecto a los mecanismos MM para redes 5G y Beyond 5G. En base a estos desafíos, definimos las posibles soluciones y un marco novedoso para los mecanismos 5G y Beyond 5G de MM. Este marco especifica un conjunto de mecanismos MM a nivel de red acceso, red del núcleo y extremo de la red (usuarios/dispositivos), que ayudarán a satisfacer los requisitos para los mecanismos MM 5G y posteriores. A continuación, presentamos el concepto de servicio bajo demanda MM. Tal característica proporciona la confiabilidad, escalabilidad y flexibilidad necesarias para los mecanismos MM. Su objetivo es garantizar que se definan los recursos y contextos de movilidad adecuados para los usuarios que tendrán perfiles de movilidad heterogéneos, y requisitos de QoS versátiles en una red multi-RAT. Más adelante, abordamos el problema de la señalización de la red troncal que ocurre durante la gestión de la movilidad en redes 5G/4G. Se ha desarrollado un nuevo mecanismo de señalización de handover, que elimina los intercambios de mensajes innecesarios durante la fase de preparación del handover, al tiempo que permite la transición a futuras arquitecturas de red softwarizada. Utilizamos los datos de operadores y consideramos un despliegue de red realista para realizar un análisis comparativo de la estrategia propuesta y la estrategia de señalización de 3GPP. Mostramos los beneficios de nuestra estrategia en términos de latencia del proceso de handover y los costes de transmisión y procesado. Por último, se ha propuesto una nueva asociación de usuarios y una metodología de asignación de recursos, i.e, AURA-5G. AURA-5G aborda escenarios en los que las aplicaciones con requisitos heterogéneos, i.e., enhanced Mobile Broadband (eMBB) y massive Machine Type Communications (mMTC), están presentes simultáneamente. En consecuencia, se ha llevado a cabo un proceso de optimización conjunta para realizar la asociación de usuarios y la asignación de recursos mientras se tienen en cuenta los requisitos de aplicaciónes heterogéneas. Capturamos las peculiaridades de este importante proceso de gestión de la movilidad a través de las diversas restricciones impuestas, como son los requisitos de backhaul, las opciones de conectividad dual, los recursos de la red de acceso disponibles, los requisitos de velocidad mínima, etc., que hemos introducido en un Mixed Integer Linear Program (MILP). La función objetivo de este problema MILP es maximizar el rendimiento total de la red de los usuarios de eMBB, y a la vez satisfacer los requisitos mínimos de los usuarios de mMTC y eMBB definidos en un escenario dado. A través de evaluaciones numéricas, mostramos que nuestro enfoque supera significativamente el escenario de asociación de usuarios de referencia. Además, hemos presentado un análisis de la justicia del sistema, así como un novedoso análisis de fidelidad y complejidad computacional para el mismo, que expresa la utilidad de nuestra metodología.Postprint (published version