Optimization of Mobility Parameters using Fuzzy Logic and Reinforcement Learning in Self-Organizing Networks

In this thesis, several optimization techniques for next-generation wireless networks are proposed to solve different problems in the field of Self-Organizing Networks and heterogeneous networks. The common basis of these problems is that network parameters are automatically tuned to deal with the specific problem. As the set of network parameters is extremely large, this work mainly focuses on parameters involved in mobility management. In addition, the proposed self-tuning schemes are based on Fuzzy Logic Controllers (FLC), whose potential lies in the capability to express the knowledge in a similar way to the human perception and reasoning. In addition, in those cases in which a mathematical approach has been required to optimize the behavior of the FLC, the selected solution has been Reinforcement Learning, since this methodology is especially appropriate for learning from interaction, which becomes essential in complex systems such as wireless networks. Taking this into account, firstly, a new Mobility Load Balancing (MLB) scheme is proposed to solve persistent congestion problems in next-generation wireless networks, in particular, due to an uneven spatial traffic distribution, which typically leads to an inefficient usage of resources. A key feature of the proposed algorithm is that not only the parameters are optimized, but also the parameter tuning strategy. Secondly, a novel MLB algorithm for enterprise femtocells scenarios is proposed. Such scenarios are characterized by the lack of a thorough deployment of these low-cost nodes, meaning that a more efficient use of radio resources can be achieved by applying effective MLB schemes. As in the previous problem, the optimization of the self-tuning process is also studied in this case. Thirdly, a new self-tuning algorithm for Mobility Robustness Optimization (MRO) is proposed. This study includes the impact of context factors such as the system load and user speed, as well as a proposal for coordination between the designed MLB and MRO functions. Fourthly, a novel self-tuning algorithm for Traffic Steering (TS) in heterogeneous networks is proposed. The main features of the proposed algorithm are the flexibility to support different operator policies and the adaptation capability to network variations. Finally, with the aim of validating the proposed techniques, a dynamic system-level simulator for Long-Term Evolution (LTE) networks has been designed

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

Cooperation strategies for inter-cell interference mitigation in OFDMA systems

Recently the use of modern cellular networks has drastically changed with the emerging Long Term Evolution Advanced (LTE-A) technology. Homogeneous networks which were initially designed for voice-centric and low data rates face unprecedented challenges for meeting the increasing traffic demands of high data-driven applications and their important quality of service requirements. Therefore, these networks are moving towards the so called Heterogeneous Networks (HetNets). HetNets represent a new paradigm for cellular networks as their nodes have different characteristics such as transmission power and radio frequency coverage area. Consequently, a HetNet shows completely different interference characteristics compared to homogeneous deployment and attention must be paid to these disparities when different tiers are collocated together. This is mostly due to the potential spectrum frequency reuse by the involved tiers in the HetNets. Hence, efficient inter-cell interference mitigation solutions in co-channel deployments of HetNets remain a challenge for both industry and academic researchers. This thesis focuses on LTE-A HetNet systems which are based on Orthogonal Frequency Division Multiplexing Access (OFDMA) modulation. Our aim is to investigate the aggressive interference issue that appears when different types of base stations are jointly deployed together and especially in two cases, namely Macro-Femtocells and Macro-Picocells co-existence. We propose new practical power adjustment solutions for managing inter-cell interference dynamically for both cases. In the first part dedicated to Femtocells and Macrocell coexistence, we design a MBS-assisted femtocell power adjustment strategy which takes into account femtocells users performance while mitigating the inter-cell interference on victim macrocell users. Further, we propose a new cooperative and context-aware interference mitigation method which is derived for realistic scenarios involving mobility of users and their varying locations. We proved numerically that the Femtocells are able to maintain their interference under a desirable threshold by adjusting their transmission power. Our strategies provide an efficient means for achieving the desired level of macrocell/femtocell throughput trade-off. In the second part of the studies where Picocells are deployed under the umbrella of the Macrocell, we paid a special attention and efforts to the interference management in the situation where Picocells are configured to set up a cell range expansion. We suggest a MBS-assisted collaborative scheme powered by an analytical model to predict the mobility of Macrocell users passing through the cell range expansion area of the picocell. Our goal is to adapt the muting ratio ruling the frequency resource partitioning between both tiers according to the mobility behavior of the range-expanded users, thereby providing an efficient trade-off between Macrocell and Picocell achievable throughputs.Récemment, l'utilisation des réseaux cellulaires a radicalement changé avec l’émergence de la quatrième génération (4G) de systèmes de télécommunications mobiles LTE/LTE-A (Long Term Evolution-Advanced). Les réseaux de générations précédentes (3G), initialement conçus pour le transport de la voix et les données à faible et moyen débits, ont du mal à faire face à l’augmentation accrue du trafic de données multimédia tout en répondant à leurs fortes exigences et contraintes en termes de qualité de service (QdS). Pour mieux répondre à ces besoins, les réseaux 4G ont introduit le paradigme des Réseaux Hétérogènes (HetNet).Les réseaux HetNet introduisent une nouvelle notion d’hétérogénéité pour les réseaux cellulaires en introduisant le concept des smalls cells (petites cellules) qui met en place des antennes à faible puissance d’émission. Ainsi, le réseau est composé de plusieurs couches (tiers) qui se chevauchent incluant la couverture traditionnelle macro-cellulaire, les pico-cellules, les femto-cellules, et les relais. Outre les améliorations des couvertures radio en environnements intérieurs, les smalls cells permettent d’augmenter la capacité du système par une meilleure utilisation du spectre et en rapprochant l’utilisateur de son point d’accès au réseau. Une des conséquences directes de cette densification cellulaire est l’interférence générée entre les différentes cellules des diverses couches quand ces dernières réutilisent les mêmes fréquences. Aussi, la définition de solutions efficaces de gestion des interférences dans ce type de systèmes constitue un de leurs défis majeurs. Cette thèse s’intéresse au problème de gestion des interférences dans les systèmes hétérogènes LTE-A. Notre objectif est d’apporter des solutions efficaces et originales au problème d’interférence dans ce contexte via des mécanismes d’ajustement de puissance des petites cellules. Nous avons pour cela distingués deux cas d’étude à savoir un déploiement à deux couches macro-femtocellules et macro-picocellules. Dans la première partie dédiée à un déploiement femtocellule et macrocellule, nous concevons une stratégie d'ajustement de puissance des femtocellules assisté par la macrocellule et qui prend en compte les performances des utilisateurs des femtocells tout en atténuant l'interférence causée aux utilisateurs des macrocellules sur leurs liens montants. Cette solution offre l’avantage de la prise en compte de paramètres contextuels locaux aux femtocellules (tels que le nombre d’utilisateurs en situation de outage) tout en considérant des scénarios de mobilité réalistes. Nous avons montré par simulation que les interférences sur les utilisateurs des macrocellules sont sensiblement réduites et que les femtocellules sont en mesure de dynamiquement ajuster leur puissance d'émission pour atteindre les objectifs fixés en termes d’équilibre entre performance des utilisateurs des macrocellules et celle de leurs propres utilisateurs. Dans la seconde partie de la thèse, nous considérons le déploiement de picocellules sous l'égide de la macrocellule. Nous nous sommes intéressés ici aux solutions d’extension de l’aire picocellulaire qui permettent une meilleure association utilisateur/cellule permettant de réduire l’interférence mais aussi offrir une meilleure efficacité spectrale. Nous proposons donc une approche basée sur un modèle de prédiction de la mobilité des utilisateurs qui permet de mieux ajuster la proportion de bande passante à partager entre la macrocellule et la picocellule en fonction de la durée de séjour estimée de ces utilisateurs ainsi que de leur demandes en bande passante. Notre solution a permis d’offrir un bon compromis entre les débits réalisables de la Macro et des picocellules

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)

D5.2 - Evaluation of Selected Measurement-based Techniques

Deliverable D5.2 del projecte FARAMIRPreprin

Improving Frequency Reuse and Cochannel Interference Coordination in 4G HetNets

This report describes my M.A.Sc. thesis research work. The emerging 4th generation (4G) mobile systems and networks (so called 4G HetNets) are designed as multilayered cellular topology with a number of asymmetrically located, asymmetrically powered, self-organizing, and user-operated indoor small cell (e.g., pico/femto cells and WLANs) with a variety of cell architectures that are overlaid by a large cell (macro cell) with some or all interfering wireless links. These designs of 4G HetNets bring new challenges such as increased dynamics of user mobility and data traffic trespassing over the multi-layered cell boundaries. Traditional approaches of radio resource allocation and inter-cell (cochannel) interference management that are mostly centralized and static in the network core and are carried out pre-hand by the operator in 3G and lower cellular technologies, are liable to increased signaling overhead, latencies, complexities, and scalability issues and, thus, are not viable in case of 4G HetNets. In this thesis a comprehensive research study is carried out on improving the radio resource sharing and inter-cell interference management in 4G HetNets. The solution strategy exploits dynamic and adaptive channel allocation approaches such as dynamic and opportunistic spectrum access (DSA, OSA) techniques, through exploiting the spatiotemporal diversities among transmissions in orthogonal frequency division multiple access (OFDMA) based medium access in 4G HetNets. In this regards, a novel framework named as Hybrid Radio Resource Sharing (HRRS) is introduced. HRRS comprises of these two functional modules: Cognitive Radio Resource Sharing (CRRS) and Proactive Link Adaptation (PLA) scheme. A dynamic switching algorithm enables CRRS and PLA modules to adaptively invoke according to whether orthogonal channelization is to be carried out exploiting the interweave channel allocation (ICA) approach or non-orthogonal channelization is to be carried out exploiting the underlay channel allocation (UCA) approach respectively when relevant conditions regarding the traffic demand and radio resource availability are met. Benefits of CRRS scheme are identified through simulative analysis in comparison to the legacy cochannel and dedicated channel deployments of femto cells respectively. The case study and numerical analysis for PLA scheme is carried out to understand the dynamics of threshold interference ranges as function of transmit powers of MBS and FBS, relative ranges of radio entities, and QoS requirement of services with the value realization of PLA scheme.1 yea