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

A survey of self organisation in future cellular networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

Field-control, phase-transitions, and life's emergence

Instances of critical-like characteristics in living systems at each organizational level as well as the spontaneous emergence of computation (Langton), indicate the relevance of self-organized criticality (SOC). But extrapolating complex bio-systems to life's origins, brings up a paradox: how could simple organics--lacking the 'soft matter' response properties of today's bio-molecules--have dissipated energy from primordial reactions in a controlled manner for their 'ordering'? Nevertheless, a causal link of life's macroscopic irreversible dynamics to the microscopic reversible laws of statistical mechanics is indicated via the 'functional-takeover' of a soft magnetic scaffold by organics (c.f. Cairns-Smith's 'crystal-scaffold'). A field-controlled structure offers a mechanism for bootstrapping--bottom-up assembly with top-down control: its super-paramagnetic components obey reversible dynamics, but its dissipation of H-field energy for aggregation breaks time-reversal symmetry. The responsive adjustments of the controlled (host) mineral system to environmental changes would bring about mutual coupling between random organic sets supported by it; here the generation of long-range correlations within organic (guest) networks could include SOC-like mechanisms. And, such cooperative adjustments enable the selection of the functional configuration by altering the inorganic network's capacity to assist a spontaneous process. A non-equilibrium dynamics could now drive the kinetically-oriented system towards a series of phase-transitions with appropriate organic replacements 'taking-over' its functions.Comment: 54 pages, pdf fil

A new paradigm for SpeckNets:inspiration from fungal colonies

In this position paper, we propose the development of a new biologically inspired paradigm based on fungal colonies, for the application to pervasive adaptive systems. Fungal colonies have a number of properties that make them an excellent candidate for inspiration for engineered systems. Here we propose the application of such inspiration to a speckled computing platform. We argue that properties from fungal colonies map well to properties and requirements for controlling SpeckNets and suggest that an existing mathematical model of a fungal colony can developed into a new computational paradigm

Context-Aware Self-Healing for Small Cell Networks

These can be an invaluable source of information for the management of the network, in a way that we have denominated as context-aware SON, which is the approach proposed in this thesis. To develop this concept, the thesis follows a top-down approach. Firstly, the characteristics of the cellular deployments are assessed, especially for indoor small cell networks. In those scenarios, the need for context-aware SON is evaluated and considered indispensable. Secondly, a new cellular architecture is defined to integrate both context information and SON mechanisms in the management plane of the mobile network. Thus, the specifics of making context an integral part of cellular OAM/SON are defined. Also, the real-world implementation of the architecture is proposed. Thirdly, from the established general SON architecture, a logical self-healing framework is defined to support the context-aware healing mechanisms to be developed. Fourthly, different self-healing algorithms are defined depending on the failures to be managed and the conditions of the considered scenario. The mechanisms are based on probabilistic analysis, making use of both context and network data for detection and diagnosis of cellular issues. The conditions for the implementation of these methods are assessed. Their applicability is evaluated by means of simulators and testbed trials. The results show important improvements in performance and capabilities in comparison to previous methods, demonstrating the relevance of the proposed approach.The last years have seen a continuous increase in the use of mobile communications. To cope with the growing traffic, recently deployed technologies have deepened the adoption of small cells (low powered base stations) to serve areas with high demand or coverage issues, where macrocells can be both unsuccessful or inefficient. Also, new cellular and non-cellular technologies (e.g. WiFi) coexist with legacy ones, including also multiple deployment schemes (macrocell, small cells), in what is known as heterogeneous networks (HetNets). Due to the huge complexity of HetNets, their operation, administration and management (OAM) became increasingly difficult. To overcome this, the NGMN Alliance and the 3GPP defined the Self-Organizing Network (SON) paradigm, aiming to automate the OAM procedures to reduce their costs and increase the resulting performance. One key focus of SON is the self-healing of the network, covering the automatic detection of problems, the diagnosis of their causes, their compensation and their recovery. Until recently, SON mechanisms have been solely based on the analysis of alarms and performance indicators. However, on the one hand, this approach has become very limited given the complexity of the scenarios, and particularly in indoor cellular environments. Here, the deployment of small cells, their coexistence with multiple telecommunications systems and the nature of those environments (in terms of propagation, coverage overlapping, fast demand changes and users' mobility) introduce many challenges for classic SON. On the other hand, modern user equipment (e.g. smartphones), equipped with powerful processors, sensors and applications, generate a huge amount of context information. Context refers to those variables not directly associated with the telecommunication service, but with the terminals and their environment. This includes the user's position, applications, social data, etc