A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Self-organising comprehensive handover strategy for multi-tier LTE-advanced heterogeneous networks

Long term evolution (LTE)-advanced was introduced as real fourth generation (4G) with its new features and additional functions, satisfying the growing demands of quality and network coverage for the network operators' subscribers. The term muti-tier has also been recently used with respect to the heterogeneity of the network by applying the various subnetwork cooperative systems and functionalities with self-organising capabilities. Using indoor short-range low-power cellular base stations, for example, femtocells, in cooperation with existing long-range macrocells are considered as the key technical challenge of this multi-tier configuration. Furthermore, shortage of network spectrum is a major concern for network operators which forces them to spend additional attentions to overcome the degradation in performance and quality of services in 4G HetNets. This study investigates handover between the different layers of a heterogeneous LTE-advanced system, as a critical attribute to plan the best way of interactive coordination within the network for the proposed HetNet. The proposed comprehensive handover algorithm takes multiple factors in both handover sensing and decision stages, based on signal power reception, resource availability and handover optimisation, as well as prioritisation among macro and femto stations, to obtain maximum signal quality while avoiding unnecessary handovers

Context-Aware Handover Policies in HetNets

Next generation cellular systems are expected to entail a wide variety of wireless coverage zones, with cells of different sizes and capacities that can overlap in space and share the transmission resources. In this scenario, which is referred to as Heterogeneous Networks (HetNets), a fundamental challenge is the management of the handover process between macro, femto and pico cells. To limit the number of handovers and the signaling between the cells, it will hence be crucial to manage the user's mobility considering the context parameters, such as cells size, traffic loads, and user velocity. In this paper, we propose a theoretical model to characterize the performance of a mobile user in a HetNet scenario as a function of the user's mobility, the power profile of the neighboring cells, the handover parameters, and the traffic load of the different cells. We propose a Markov-based framework to model the handover process for the mobile user, and derive an optimal context-dependent handover criterion. The mathematical model is validated by means of simulations, comparing the performance of our strategy with conventional handover optimization techniques in different scenarios. Finally, we show the impact of the handover regulation on the users performance and how it is possible to improve the users capacity exploiting context information

A Vertical Handover Algorithm in Integrated Macrocell Femtocell Networks

The explosion in wireless telecommunication technologies has lead to a huge increase in the number of mobile users. The greater dependency on the mobile devices has raised the user’s expectations to always remain best connected. In the process, the user is always desiring good signal strength even at certain black spots and indoors. Moreover, the exponential growth of the number of mobile devices has overloaded macrocells. Femtocells have emerged out as a good promising solution for complete coverage indoors and for offloading macrocell. Therefore, a new handover strategy between femtocells and macrocell is proposed in this paper. The proposed handover algorithm is mainly based on calculating equivalent received signal strength along with dynamic margin for performing handover. The simulation results of proposed algorithm are compared with the traditional algorithm. The proposed strategy shows improvement in two major performance parameters namely reduction in unnecessary handovers and Packet Loss Ratio. The quantitative analysis further shows 55.27% and 23.03% reduction in packet loss ratio and 61.85% and 36.78% reduction in unnecessary handovers at a speed of 120kmph and 30kmph respectively. Moreover, the proposed algorithm proves to be an efficient solution for both slow and fast moving vehicles

Algoritmos de transferência de redes LTE em meios de transporte massivo

Handover in LTE occurs when a device moves from the cell coverage serving it towards another; a process where the user established session must not be interrupted due to this cell change. Handovers in LTE are classified as hard ones, since the link with the serving cell is interrupted before establishing the new link with the target cell. This entails a larger failure risk and, consequently, a potential deterioration in the quality of service. This article presents a review of the handover algorithms in LTE, focusing on the ones oriented to massive means of transport. We show how the new algorithms offer a larger success in handovers, increasing the networkdata rate. This indicates that factors such as speed, position, and direction should be included in the algorithms to improve the handover in means of transport. We also present the algorithms focused on mobile relays such as an important study field for future research works.El traspaso en LTE se presenta cuando un equipo pasa de la cobertura de una celda a la de otra, un proceso en el que se debe asegurar que el usuario no vea interrumpida su sesión, como efecto de ese cambio de celda. Los traspasos en LTE son del tipo duro, en ellos, el enlace con la celda servidora se interrumpe antes de establecer el nuevo enlace con la celda destino, lo que conlleva a un mayor riesgo de falla y con ello a un probable deterioro de la calidad del servicio al usuario. Este artículo revisa algoritmos de traspaso LTE, enfocándose en aquellos orientados a medios de trasporte masivo. Muestra cómo los nuevos algoritmos ofrecen una tasa mayor de traspasos exitosos y con ello una mejor tasa de transferencia de datos; evidencia que factores como la velocidad, la posición y la dirección deben ser incluidos en los algoritmos dirigidos a mejorar el traspaso en medios de transporte; y presenta a los algoritmos enfocados en relays móviles, como un importante campo de estudio para futuras investigaciones.A transferência em LTE ocorre quando um dispositivo passa da cobertura de uma célula para outra, um processo no qual deve ser assegurado que o usuário não veja sua sessão interrompida, como resultado dessa mudança de célula. As transferências em LTE são do tipo duro, nelas, o link com a célula do servidor é interrompido antes de se estabelecer o novo link com a célula alvo, o que leva a um maior risco de falha e, portanto, a uma provável deterioração da qualidade do serviço ao usuário. Este artigo revisa os algoritmos de transferência LTE, com foco naqueles orientados a meios de transporte massivo. Mostra como os novos algoritmos oferecem uma taxa maior de transferências bem-sucedidas e, com isso, uma melhor taxa de transferência de dados; evidencia de que fatores como a velocidade, a posição e a direção devem ser incluídos nos algoritmos que visam melhorar a transferência nos meios de transporte; e apresenta os algoritmos focados em relés móveis, como um importante campo de estudo para futuras pesquisas

Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks

Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased

Cell identity allocation and optimisation of handover parameters in self-organised LTE femtocell networks

A thesis submitted to the University of Bedfordshire in partial ful lment of the requirements for the degree of Doctor of PhilosophyFemtocell is a small cellular base station used by operators to extend indoor service coverage and enhance overall network performance. In Long Term Evolution (LTE), femtocell works under macrocell coverage and combines with the macrocell to constitute the two-tier network. Compared to the traditional single-tier network, the two-tier scenario creates many new challenges, which lead to the 3rd Generation Partnership Project (3GPP) implementing an automation technology called Self-Organising Network (SON) in order to achieve lower cost and enhanced network performance. This thesis focuses on the inbound and outbound handovers (handover between femtocell and macrocell); in detail, it provides suitable solutions for the intensity of femtocell handover prediction, Physical Cell Identity (PCI) allocation and handover triggering parameter optimisation. Moreover, those solutions are implemented in the structure of SON. In order to e ciently manage radio resource allocation, this research investigates the conventional UE-based prediction model and proposes a cell-based prediction model to predict the intensity of a femtocell's handover, which overcomes the drawbacks of the conventional models in the two-tier scenario. Then, the predictor is used in the proposed dynamic group PCI allocation approach in order to solve the problem of PCI allocation for the femtocells. In addition, based on SON, this approach is implemented in the structure of a centralised Automated Con guration of Physical Cell Identity (ACPCI). It overcomes the drawbacks of the conventional method by reducing inbound handover failure of Cell Global Identity (CGI). This thesis also tackles optimisation of the handover triggering parameters to minimise handover failure. A dynamic hysteresis-adjusting approach for each User Equipment (UE) is proposed, using received average Reference Signal-Signal to Interference plus Noise Ratio (RS-SINR) of the UE as a criterion. Furthermore, based on SON, this approach is implemented in the structure of hybrid Mobility Robustness Optimisation (MRO). It is able to off er the unique optimised hysteresis value to the individual UE in the network. In order to evaluate the performance of the proposed approach against existing methods, a System Level Simulation (SLS) tool, provided by the Centre for Wireless Network Design (CWiND) research group, is utilised, which models the structure of two-tier communication of LTE femtocell-based networks