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

System optimisation and radio planning for future LTE-advanced

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis work is related to wireless communication. In this Thesis three main issues are addressed for future cellular networks: power consumption, interference and mobility. These issues continue to be a burden on the system’s performance as long as technology keeps evolving. In the presented chapters, the focus was to introduce greater intelligence to the LTE system algorithms and bring to them a dynamic and self-organizing approach. The first approach concerns power consumption in wireless terminals. The currently applied solution to save energy is the DRX mechanism. It organizes the time when the terminal wakes up and starts receiving data, and when it goes into sleep mode in order to save its battery power. The current DRX is described as static or fixed which makes its parameters unsuitable for the nature of the bursty traffic. In this work an adaptive DRX mechanism is proposed and evaluated as the wireless terminal battery saving algorithm. The second approach is co-channel interference mitigation. To increase the system’s capacity and avoid spectrum scarcity, small cells such as Femtocells are deployed and operate on the same frequency bands as the Macrocell. Although these small nodes increase the system capacity, however, the challenges will be in the femtocells planning and management in addition to the interference issues. Here a dynamic interference cancellation approach is presented to enable the Femtocell to track the allocated resources to the Macro-users, and to avoid using them. The third approach concerns mobility management in heterogeneous networks. The wireless terminal may have different mobility levels during handover which increases the handover failures due to failure in handover commands and aging of the reported parameters. This issue is presented in detail with the aim to avoid performance degradation and improve the reporting mechanisms during fast mobility levels. For this regard the presented method proposes more cooperation between the serving cell and the end-user so that the large amount of overhead and measurement are reduced. Simulations with different configurations are conducted to present the results of the proposed models. Results show that the proposed models bring improvements to the LTE system. The enhanced self-organized architecture in the three presented approaches performs well in terms of power saving, dynamic spectrum utilization by Femtocells, and mitigation of sudden throughput degradation due to the serving cell’s downlink signal outage during mobility.Brunel University Londo

Localization and mobility management in heterogeneous wireless networks with network-assistance

The nowadays heterogeneous wireless network (HWN) is a collection of ubiquitous wireless networking elements (WNEs) that support diverse functional capabilities and networking purposes. In such a heterogeneous networking environment, localization and mobility management will play a key role for the seamless support of emerging applications, such as social networking, massive multiplayer online gaming, device-todevice (D2D) communications, smart metering, first-responder communications, and unsupervised navigation of communication-aware robotic nodes. Since most of the existing wireless networking technologies enable the WNEs to assess their current radio status and directly (or indirectly) estimate their relative distance and angle with respect to other WNEs of the same Radio Access Technology (RAT), the integration of such information from the ubiquitous WNEs arises as a natural solution for robustly handling localization between (not necessarily homogeneous) WNEs and mobility management of moving WNEs governed by resource-constrained operation. Under the viewpoint of investigating how the utilization of such spatial information can be used to enhance the performance of localization and mobility management in the nowadays HWN, in this work we focus and contribute in the following four research areas: i) localization and peer-discovery between non-homogeneous WNEs, ii) network-assisted D2D discovery in cellular networks, iii) energy-efficient handover (HO) decision in the macrocell – femtocell network, and iv) network-assisted vertical handover decision (VHO) for the integrated cellular and WLAN heterogeneous wireless network

Models and optimisation methods for interference coordination in self-organising cellular networks

A thesis submitted for the degree of Doctor of PhilosophyWe are at that moment of network evolution when we have realised that our telecommunication systems should mimic features of human kind, e.g., the ability to understand the medium and take advantage of its changes. Looking towards the future, the mobile industry envisions the use of fully automatised cells able to self-organise all their parameters and procedures. A fully self-organised network is the one that is able to avoid human involvement and react to the fluctuations of network, traffic and channel through the automatic/autonomous nature of its functioning. Nowadays, the mobile community is far from this fully self-organised kind of network, but they are taken the first steps to achieve this target in the near future. This thesis hopes to contribute to the automatisation of cellular networks, providing models and tools to understand the behaviour of these networks, and algorithms and optimisation approaches to enhance their performance. This work focuses on the next generation of cellular networks, in more detail, in the DownLink (DL) of Orthogonal Frequency Division Multiple Access (OFDMA) based networks. Within this type of cellular system, attention is paid to interference mitigation in self-organising macrocell scenarios and femtocell deployments. Moreover, this thesis investigates the interference issues that arise when these two cell types are jointly deployed, complementing each other in what is currently known as a two-tier network. This thesis also provides new practical approaches to the inter-cell interference problem in both macro cell and femtocell OFDMA systems as well as in two-tier networks by means of the design of a novel framework and the use of mathematical optimisation. Special attention is paid to the formulation of optimisation problems and the development of well-performing solving methods (accurate and fast)

Optimal and practical handover decision algorithms in heteregeneous marco-femto cellular networks

Driven by the smart tablet/phone revolution and the proliferation of bandwidth hungry applications such as cloud computing and streaming video, the demand for high data rate wireless communication is increasing tremendously. In order to meet the increasing demand from subscribers, wireless operators are in the process of augmenting their macrocell network with supplemental infrastructure such as microcells, distributed antennas and relays. An alternative with lower upfront costs is to improve indoor coverage and capacity by using end-consumer installed femtocells. A femtocell is a low power, short range (up to 100 meters coverage radius) cellular wireless access point (AP), functioning in service provider owned licensed spectrum. Due to the proximity of end users to the femtocell access points, APs are able to provide higher end-user QoE and better spatial reuse of limited spectrum. Femtocells are useful in offloading the macro-cellular network as well as reducing the operating and capital expenditure costs for operators. Femtocells coexist with legacy cellular networks consisting of macrocells. In this emerging combined architecture, large number of Femtocell Application Point (FAPs) is randomly deployed in the coverage area of macro BSs. However, several problems related to MM (mobility management) and RM (resource management) in this combined architecture still remain to be solved. The ad hoc deployment of FAPs and asymmetric radio communication and call processing capabilities between macrofemto networks are the primary causes of these problems. Uncoordinated deployment of FAPs providing indoor oriented wireless access service within the macro coverage may cause severe interference problems that need to be mitigated and handled by RM/MM schemes. The MM decisions should take into account the resource constraints and UE mobility in order to prevent unnecessary or undesirable handovers towards femtocells. Ignoring these factors in MM decisions may lead to low customer satisfaction due to mismanagement of handover events in the combined macro-femto network, delayed signaling traffic and unsatisfactory call/connection quality. In order to address all of the aforementioned issues, the handover decision problem in combined femto-macro networks has been formulated as a multi-objective non-linear optimization problem. Since there are no known analytical solution to this problem, an MDP (Markov Decision Process) based heuristic has been proposed as a practical and optimal HO (handover) decision making scheme. This heuristic has been updated and improved in an iterative manner and has also been supported by a dynamic SON (Self Organizing Networks) algorithms that is based on heuristic's components. The performance results show that the final version of MDP based heuristic has signi cantly superior performance in terms offloading the macro network, minimizing the undesirable network events (e.g. outage and admission rejection) when compared to state-of-art handover algorithms

User-oriented mobility management in cellular wireless networks

2020 Spring.Includes bibliographical references.Mobility Management (MM) in wireless mobile networks is a vital process to keep an individual User Equipment (UE) connected while moving within the network coverage area—this is required to keep the network informed about the UE's mobility (i.e., location changes). The network must identify the exact serving cell of a specific UE for the purpose of data-packet delivery. The two MM procedures that are necessary to localize a specific UE and deliver data packets to that UE are known as Tracking Area Update (TAU) and Paging, which are burdensome not only to the network resources but also UE's battery—the UE and network always initiate the TAU and Paging, respectively. These two procedures are used in current Long Term Evolution (LTE) and its next generation (5G) networks despite the drawback that it consumes bandwidth and energy. Because of potentially very high-volume traffic and increasing density of high-mobility UEs, the TAU/Paging procedure incurs significant costs in terms of the signaling overhead and the power consumption in the battery-limited UE. This problem will become even worse in 5G, which is expected to accommodate exceptional services, such as supporting mission-critical systems (close-to-zero latency) and extending battery lifetime (10 times longer). This dissertation examines and discusses a variety of solution schemes for both the TAU and Paging, emphasizing a new key design to accommodate 5G use cases. However, ongoing efforts are still developing new schemes to provide seamless connections to the ever-increasing density of high-mobility UEs. In this context and toward achieving 5G use cases, we propose a novel solution to solve the MM issues, named gNB-based UE Mobility Tracking (gNB-based UeMT). This solution has four features aligned with achieving 5G goals. First, the mobile UE will no longer trigger the TAU to report their location changes, giving much more power savings with no signaling overhead. Instead, second, the network elements, gNBs, take over the responsibility of Tracking and Locating these UE, giving always-known UE locations. Third, our Paging procedure is markedly improved over the conventional one, providing very fast UE reachability with no Paging messages being sent simultaneously. Fourth, our solution guarantees lightweight signaling overhead with very low Paging delay; our simulation studies show that it achieves about 92% reduction in the corresponding signaling overhead. To realize these four features, this solution adds no implementation complexity. Instead, it exploits the already existing LTE/5G communication protocols, functions, and measurement reports. Our gNB-based UeMT solution by design has the potential to deal with mission-critical applications. In this context, we introduce a new approach for mission-critical and public-safety communications. Our approach aims at emergency situations (e.g., natural disasters) in which the mobile wireless network becomes dysfunctional, partially or completely. Specifically, this approach is intended to provide swift network recovery for Search-and-Rescue Operations (SAROs) to search for survivors after large-scale disasters, which we call UE-based SAROs. These SAROs are based on the fact that increasingly almost everyone carries wireless mobile devices (UEs), which serve as human-based wireless sensors on the ground. Our UE-based SAROs are aimed at accounting for limited UE battery power while providing critical information to first responders, as follows: 1) generate immediate crisis maps for the disaster-impacted areas, 2) provide vital information about where the majority of survivors are clustered/crowded, and 3) prioritize the impacted areas to identify regions that urgently need communication coverage. UE-based SAROs offer first responders a vital tool to prioritize and manage SAROs efficiently and effectively in a timely manner

Comunicações veiculares híbridas

Vehicle Communications is a promising research field, with a great potential for the development of new applications capable of improving road safety, traffic efficiency, as well as passenger comfort and infotainment. Vehicle communication technologies can be short-range, such as ETSI ITS-G5 or the 5G PC5 sidelink channel, or long-range, using the cellular network (LTE or 5G). However, none of the technologies alone can support the expected variety of applications for a large number of vehicles, nor all the temporal and spatial requirements of connected and autonomous vehicles. Thus, it is proposed the collaborative or hybrid use of short-range communications, with lower latency, and of long-range technologies, potentially with higher latency, but integrating aggregated data of wider geographic scope. In this context, this work presents a hybrid vehicle communications model, capable of providing connectivity through two Radio Access Technologies (RAT), namely, ETSI ITS-G5 and LTE, to increase the probability of message delivery and, consequently, achieving a more robust, efficient and secure vehicle communication system. The implementation of short-range communication channels is done using Raw Packet Sockets, while the cellular connection is established using the Advanced Messaging Queuing Protocol (AMQP) protocol. The main contribution of this dissertation focuses on the design, implementation and evaluation of a Hybrid Routing Sublayer, capable of isolating messages that are formed/decoded from transmission/reception processes. This layer is, therefore, capable of managing traffic coming/destined to the application layer of intelligent transport systems (ITS), adapting and passing ITS messages between the highest layers of the protocol stack and the available radio access technologies. The Hybrid Routing Sublayer also reduces the financial costs due to the use of cellular communications and increases the efficiency of the use of the available electromagnetic spectrum, by introducing a cellular link controller using a Beacon Detector, which takes informed decisions related to the need to connect to a cellular network, according to different scenarios. The experimental results prove that hybrid vehicular communications meet the requirements of cooperative intelligent transport systems, by taking advantage of the benefits of both communication technologies. When evaluated independently, the ITS-G5 technology has obvious advantages in terms of latency over the LTE technology, while the LTE technology performs better than ITS-G5, in terms of throughput and reliability.As Comunicações Veiculares são um campo de pesquisa promissor, com um grande potencial de desenvolvimento de novas aplicações capazes de melhorar a segurança nas estradas, a eficiência do tráfego, bem com o conforto e entretenimento dos passageiros. As tecnologias de comunicação veícular podem ser de curto alcance, como por exemplo ETSI ITS-G5 ou o canal PC5 do 5G, ou de longo alcance, recorrendo à rede celular (LTE ou 5G). No entanto, nenhuma das tecnologias por si só, consegue suportar a variedade expectável de aplicações para um número de veículos elevado nem tampouco todos os requisitos temporais e espaciais dos veículos conectados e autónomos. Assim, é proposto o uso colaborativo ou híbrido de comunicações de curto alcance, com latências menores, e de tecnologias de longo alcance, potencialmente com maiores latências, mas integrando dados agregados de maior abrangência geográfica. Neste contexto, este trabalho apresenta um modelo de comunicações veiculares híbrido, capaz de fornecer conectividade por meio de duas Tecnologias de Acesso por Rádio (RAT), a saber, ETSI ITS-G5 e LTE, para aumentar a probabilidade de entrega de mensagens e, consequentemente, alcançar um sistema de comunicação veicular mais robusto, eficiente e seguro. A implementação de canais de comunicação de curto alcance é feita usando Raw Packet Sockets, enquanto que a ligação celular é estabelecida usando o protocolo Advanced Messaging Queuing Protocol (AMQP). A contribuição principal desta dissertação foca-se no projeto, implementação e avaliação de uma sub camada hibrída de encaminhamento, capaz de isolar mensagens que se formam/descodificam a partir de processos de transmissão/receção. Esta camadada é, portanto, capaz de gerir o tráfego proveniente/destinado à camada de aplicação de sistemas inteligentes de transportes (ITS) adaptando e passando mensagens ITS entre as camadas mais altas da pilha protocolar e as tecnologias de acesso rádio disponíveis. A sub camada hibrída de encaminhamento também potencia uma redução dos custos financeiros devidos ao uso de comunicações celulares e aumenta a eficiência do uso do espectro electromagnético disponível, ao introduzir um múdulo controlador da ligação celular, utilizando um Beacon Detector, que toma decisões informadas relacionadas com a necessidade de uma conexão a uma rede celular, de acordo com diferentes cenários. Os resultados experimentais comprovam que as comunicações veículares híbridas cumprem os requisitos dos sistemas cooperativos de transporte inteligentes, ao tirarem partido das vantagens de ambas tecnologias de comunicação. Quando avaliadas de forma independente, constata-se que que a tecnologia ITS-G5 tem vantagens evidentes em termos de latência sobre a tecnologia LTE, enquanto que a tecnologia LTE tem melhor desempenho que a LTE, ai nível de débito e fiabilidade.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Next-Generation Self-Organizing Networks through a Machine Learning Approach

Fecha de lectura de Tesis Doctoral: 17 Diciembre 2018.Para reducir los costes de gestión de las redes celulares, que, con el tiempo, aumentaban en complejidad, surgió el concepto de las redes autoorganizadas, o self-organizing networks (SON). Es decir, la automatización de las tareas de gestión de una red celular para disminuir los costes de infraestructura (CAPEX) y de operación (OPEX). Las tareas de las SON se dividen en tres categorías: autoconfiguración, autooptimización y autocuración. El objetivo de esta tesis es la mejora de las funciones SON a través del desarrollo y uso de herramientas de aprendizaje automático (machine learning, ML) para la gestión de la red. Por un lado, se aborda la autocuración a través de la propuesta de una novedosa herramienta para una diagnosis automática (RCA), consistente en la combinación de múltiples sistemas RCA independientes para el desarrollo de un sistema compuesto de RCA mejorado. A su vez, para aumentar la precisión de las herramientas de RCA mientras se reducen tanto el CAPEX como el OPEX, en esta tesis se proponen y evalúan herramientas de ML de reducción de dimensionalidad en combinación con herramientas de RCA. Por otro lado, en esta tesis se estudian las funcionalidades multienlace dentro de la autooptimización y se proponen técnicas para su gestión automática. En el campo de las comunicaciones mejoradas de banda ancha, se propone una herramienta para la gestión de portadoras radio, que permite la implementación de políticas del operador, mientras que, en el campo de las comunicaciones vehiculares de baja latencia, se propone un mecanismo multicamino para la redirección del tráfico a través de múltiples interfaces radio. Muchos de los métodos propuestos en esta tesis se han evaluado usando datos provenientes de redes celulares reales, lo que ha permitido demostrar su validez en entornos realistas, así como su capacidad para ser desplegados en redes móviles actuales y futuras

Context-aware Self-Optimization in Small-Cell Networks

Most mobile communications take place at indoor environments, especially in commercial and corporate scenarios. These places normally present coverage and capacity issues due to the poor signal quality, which degrade the end-user Quality of Experience (QoE). In these cases, mobile operators are offering small cells to overcome the indoor issues, being femtocells the main deployed base stations. Femtocell networks provide significant benefits to mobile operators and their clients. However, the massive integration and the particularities of femtocells, make the maintenance of these infrastructures a challenge for engineers. In this sense, Self-Organizing Networks (SON) techniques play an important role. These techniques are a key feature to intelligently automate network operation, administration and management procedures. SON mechanisms are based on the analysis of the mobile network alarms, counters and indicators. In parallel, electronics, sensors and software applications evolve rapidly and are everywhere. Thanks to this, valuable context information can be gathered, which properly managed can improve SON techniques performance. Within possible context data, one of the most active topics is the indoor positioning due to the immediate interest on indoor location-based services (LBS). At indoor commercial and corporate environments, user densities and traffic vary in spatial and temporal domain. These situations lead to degrade cellular network performance, being temporary traffic fluctuations and focused congestions one of the most common issues. Load balancing techniques, which have been identified as a use case in self-optimization paradigm for Long Term Evolution (LTE), can alleviate these congestion problems. This use case has been widely studied in macrocellular networks and outdoor scenarios. However, the particularities of femtocells, the characteristics of indoor scenarios and the influence of users’ mobility pattern justify the development of new solutions. The goal of this PhD thesis is to design and develop novel and automatic solutions for temporary traffic fluctuations and focused network congestion issues in commercial and corporate femtocell environments. For that purpose, the implementation of an efficient management architecture to integrate context data into the mobile network and SON mechanisms is required. Afterwards, an accurate indoor positioning system is developed, as a possible inexpensive solution for context-aware SON. Finally, advanced self-optimization methods to shift users from overloaded cells to other cells with spare resources are designed. These methods tune femtocell configuration parameters based on network information, such as ratio of active users, and context information, such as users’ position. All these methods are evaluated in both a dynamic LTE system-level simulator and in a field-trial