Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios

Radiocommunication networks are one of the main support tools of agencies that carry out actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these communications technologies from narrowband to broadband and integrated to information technologies to have an effective action before society. Understanding that this problem includes, besides the technical aspects, issues related to the social context to which these systems are inserted, this study aims to construct scenarios, using several sources of information, that helps the managers of the PPDR agencies in the technological decisionmaking process of the Digital Transformation of Mission-Critical Communication considering Smart City scenarios, guided by the methods and approaches of Technological Assessment (TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários, utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de Avaliação Tecnológica (TA)

Techno-economic valuation of mobile communications scenarios

Valuation of large projects on new communications technologies is a challenging task. Major investments are required to spread out technology and services, the characteristics of which are still largely unknown. A balanced view is needed on capabilities of the technologies, market demand, and relevant value network actors and their economies. In this dissertation, comprehensive techno-economic modelling of these aspects will be introduced for valuation of selected business scenarios. The research framework is mobile data services and business architectures in the advent of new technologies, like UMTS (Universal Mobile Telecommunications System), WLAN (Wireless Local Area Network) and WiMAX (Worldwide Interoperability for Microwave Access). The techno-economic method in this context comprises the modelling of a large set of technology, market and other factors in relation to the business operations of the analysed market actors. The many uncertainties concerning future service innovations and market development set demands on scenario creation and parameter estimation. Traditional techno-economic investment project calculation is not enough. This study gives devices for strategic decision making by analysing three different technology transitions: The modelling of Western-European incumbent operator business starting from the early 2000's indicated that the UMTS deployment should be started without delay to maximise the long-term profits from the acquired licenses, contrary to looking for short-term investment payoffs that was prevalent after the telecommunications downturn. Results also show that the emerging WLAN technology would not become a substitute for UMTS, but the public WLAN will complement the UMTS based business architecture. Modelling of the upcoming mobile WiMAX in comparison to UMTS path indicated that the mobile WiMAX cannot challenge the UMTS, as the latter one offers a better business case for the key actors. In the last transition, techno-economic delta analysis was used to quantify the benefits from the fixed-mobile convergence. The main enhancements to the techno-economic method are first the extensive classification of advanced mobile services and related modelling of service diffusion, usage patterns, capacity requirements and revenues. The second contribution is to improve the analysis of service usage in relation to technology characteristics by integrating an end-user model that gives the demand and revenue potential of each service type, per user segment and utilised technology. A novelty is also the separation of network provisioning and service provisioning part of the business architecture into separate but interlinked models. The fourth contribution to the method is the application of real options method on large communications technology deployment projects, solving option modelling problems due to the complex dependencies of the project value on the investment timing. The introduced method starts from ordinary expected cash flow valuation, but adds to that the option value related to specific flexibility in the project

View on 5G Architecture: Version 2.0

The 5G Architecture Working Group as part of the 5GPPP Initiative is looking at capturing novel trends and key technological enablers for the realization of the 5G architecture. It also targets at presenting in a harmonized way the architectural concepts developed in various projects and initiatives (not limited to 5GPPP projects only) so as to provide a consolidated view on the technical directions for the architecture design in the 5G era. The first version of the white paper was released in July 2016, which captured novel trends and key technological enablers for the realization of the 5G architecture vision along with harmonized architectural concepts from 5GPPP Phase 1 projects and initiatives. Capitalizing on the architectural vision and framework set by the first version of the white paper, this Version 2.0 of the white paper presents the latest findings and analyses with a particular focus on the concept evaluations, and accordingly it presents the consolidated overall architecture design

Partilha de infraestruturas de telecomunicações

Mestrado em Engenharia Eletrónica e TelecomunicaçõesAs telecomunicações móveis têm enfrentado enormes desafios em todo o mundo, com especial ênfase nos países emergentes. A sua crescente importância para o crescimento das economias dos países tornam a sua presença essencial num mundo cada vez mais global e tecnológico. A partilha de infraestruturas de telecomunicações torna a implementação de comunicações móveis numa dada região ou país mais facilitada. No caso de Moçambique, que é dos países mais pobres do mundo, a partilha seria uma estratégia interessante de forma a permitir um rápido crescimento dos serviços de telecomunicações. Neste projeto, foi desenvolvida uma ferramenta que auxilia o estudo tecno-económico de cenários de partilha de infraestruturas de telecomunicações. Esta ferramenta permitiu assim criar cenários para a realidade Moçambicana. Esta dissertação pretende contribuir para o desenvolvimento da área das telecomunicações em mercados emergentes.Mobile telecommunications have been facing a vast number of challenges across the globe, with special emphasis on emerging countries. Their increasing importance for economic growth of countries make the presence of infrastructure essential in a progressively more global and technological world. Sharing telecommunication infrastructures can facilitate the implementation of mobile communications in a giving region or country. In the case of Mozambique, one of the poorest country of the world, a sharing strategy could potentially allow for a rapid expansion of telecommunication services. In this work project, a tool that supports the techno-economic study of scenarios of telecommunication infrastructure sharing was developed. Through this mechanism, scenarios that consider the Mozambican’s reality have been set up. This dissertation aims then to contribute to the development of the telecommunications sector in emerging markets

Digital Transformation in Norwegian Enterprises

This open access book presents a number of case studies on digital transformation in Norway, one of the fore-runners in the digital progress index established by the European Commission in 2020. They explore the process of adoption, diffusion and value generation from digital technologies, and how the use of different digital solutions has enabled Norwegian enterprises to digitally transform their operations and business models. The book starts with an introductory chapter summarizing a vast body of literature in order to synthesize what is already known about digital transformation before exploring the Norwegian context in more detail. Then a series of case studies from the private and public sector in Norway is presented. They document a process perspective which describes the sequence of events during and after adoption of digital solutions, as well as the types of business value that were realized. Through these single studies, the process of digital transformation is illustrated, a number of key findings highlighted, and eventually theoretical and practical recommendations based on these cases emphasized. The book closes with a brief overview of some emerging technologies, and comments on how they are likely to change different sectors. Digital transformation has been one of the priority areas for the Norwegian government over the past years and puts Norwegian enterprises upfront in adopting novel technologies and utilizing them for achieving organizational goals. This experience accumulated over the years makes the Norwegian context a particularly interesting one in understanding how private and public organizations make use of new digital solutions, what lessons can be learnt during the process, and what are some of the key success and failure factors. This way the book is written for practitioners who are currently involved in digital transformation projects in their organizations, researchers of information systems and management, as well as master students in degrees of informatics and technology management

Dynamic Approach to Competitive Intelligence: Case Studies of Large-Scale Swiss Telecom Firms

The research aim is to understand how the competitive intelligence (CI) process in large-scale Swiss telecom companies contributes to management decision-making. Studying CI activities of the Swiss large-scale telecom firms (Swisscom, Sunrise, Orange/Salt, Cablecom) in a dynamic European context offers useful insight into the critical challenges that service firms now face when developing intelligence in disruptive market contexts where aggressive competitive behaviour is evident. In considering CI theory, this study has reviewed perspectives drawn from research on the CI process, studies on knowledge management and work on systems thinking. In extending the predominant modular view of CI to include elements of systems thinking, this study has added to our academic understanding of CI at firm level. An Integrative CI Activities framework was developed that enables a more holistic perspective of CI to be adopted, taking account of operational, organisational and strategic perspectives. A diagram representing the range of CI analysis methodologies has also been generated, that differentiates between internal/external orientation and static/dynamic forms of CI analysis. Such frameworks can be used by CI researchers in other market contexts. The methodology for this study drew on a pragmatist philosophy, using a case study strategy that adopted mixed methods in data collection, including semi-structured depth interviews with top CI Analysts in each firm. Findings have shown differences in the scope of CI Activities that link to stages of CI development (developing, developed) and variation between headquarters-centred and firm-centred approaches to CI planning and implementation. The adoption of query based, flexible analysis approaches in firm-centred settings differ from more structured CI analysis techniques in headquarters-based firms. Evidence from this study suggests that networked communication, strong feedback mechanisms and the adoption of more flexible CI analyst roles link to more effective CI processes and to greater potential for direct CI contribution to decision-making. Key contributions emerge through the three lenses of analysis adopted (operational, organisational and strategic); in terms of operational CI processes, the study identifies a complex integrated system at work in firms that implement CI effectively. In studying the link between organisational structure and CI analysis, the study has mapped organisational support patterns and how they shape the CI process at firm level. With respect to the strategic lens, following a detailed worked study of predictive analysis in one case firm, findings have identified adaptiveness in CI design as essential to address disruptive market change. Managerial consideration include a need for a) greater flexibility in CI implementation at firm level to adapt to turbulent markets, b) acknowledgement of the importance of the CI analyst role further and c) more dynamic CI content to be generated by CI analysts

Contribution to the modelling and evaluation of radio network slicing solutions in 5G

Network slicing is a key feature of 5G architecture that allows the partitioning of the network into multiple logical networks, known as network slices, where each of them is customised according to the specific needs of a service or application. Thus, network slicing allows the materialisation of multi-tenant networks, in which a common network infrastructure is shared among multiple communication providers, acting as tenants and each of them using a different network slice. The support of multi-tenancy through slicing in the Radio Access Network (RAN), known as RAN slicing, is particularly challenging because it involves the configuration and operation of multiple and diverse RAN behaviours over the common pool of radio resources available at each of the RAN nodes. Moreover, this configuration needs to be performed in such a way that the specific requirements of each tenant are satisfied and, at the same time, the available radio resources are efficiently used. Therefore, new functionalities that allow the deployment of RAN slices are needed to be introduced at different levels, ranging from Radio Resource Management (RRM) functionalities that incorporate RAN slicing parameters to functionalities that support the lifecycle management of RAN slices. This thesis has addressed this need by proposing, developing and assessing diverse solutions for the support RAN slicing, which has allowed evaluating the capacities, requirements and limitations of network slicing in the RAN from diverse perspectives. Specifically, this thesis is firstly focused on the analytical assessment of RRM functionalities that support multi-tenant and multi-services scenarios, where services are defined according to their 5G QoS requirements. This assessment is conducted through the Markov modelling of admission control policies and the statistical modelling of the resourc allocation, both supporting multiple tenants and multiple services. Secondly, the thesis addresses the problem of slice admission control by proposing a methodology for the estimation of the radio resources required by a RAN slice based on data analytics. This methodology supports the decision on the admission or rejection of new RAN slice creation requests. Thirdly, the thesis explores the potential of artificial intelligence, and specifically, of Deep Reinforcement Learning (DRL) to deal with the capacity sharing problem in RAN slicing scenarios. To this end, a DRL-based capacity sharing solution that distributes the available capacity of a multi-cell scenario among multiple tenants is proposed and assessed. The solution consists in a Multi-Agent Reinforcement Learning (MARL) approach based on Deep Q-Network. Finally, this thesis discuses diverse implementation aspects of the DRL-based capacity sharing solution, including considerations on its compatibility with the standards, the impact of the training on the achieved performance, as well as the tools and technologies required for the deployment of the solution in the real network environment.El Network Slicing és una tecnologia clau de l’arquitectura del 5G que permet dividir la xarxa en múltiples xarxes lògiques, conegudes com a network slices, on cada una es configura d’acord a les necessitats d’un servei o aplicació específic. Així, el network slicing permet la materialització de les xarxes amb múltiples inquilins, on una infraestructura de xarxa comuna es comparteix entre diferents proveïdors de comunicacions, que actuen com a inquilins i utilitzen network slices diferents. El suport de múltiples inquilins mitjançant l’ús del network slicing a la xarxa d’accés ràdio (RAN), que es coneix com a RAN slicing, és un gran repte tecnològic, ja que comporta la configuració i operació de múltiples i diversos comportaments sobre els recursos ràdio disponibles a cadascun dels nodes de la xarxa d’accés. A més a més, aquesta configuració s’ha de portar a terme de forma que els requisits específics de cada inquilí es satisfacin i, al mateix temps, els recursos ràdio disponibles s’utilitzin eficientment. Per tant, és necessari introduir noves funcionalitats a diferents nivells que permetin el desplegament de les RAN slices, des de funcionalitats relacionades amb la gestió dels recursos ràdio (RRM) que incorporin paràmetres per al RAN slicing a funcionalitats que proporcionin suport a la gestió del cicle de vida de les RAN slices. Aquesta tesi ha adreçat aquesta necessitat proposant, desenvolupant i avaluant diverses solucions pel suport del RAN slicing, que han permès analitzar les capacitats, requisits i limitacions del RAN slicing des de diferents perspectives. Específicament, aquesta tesi es centra, en primer lloc, en realitzar una anàlisi de les funcionalitats de RRM que suporten escenaris amb múltiples inquilins i múltiples serveis, on els serveis es defineixen d’acord amb els seus requisits de 5G QoS. Aquesta anàlisi es porta a terme mitjançant la caracterització de polítiques de control d’admissió amb un model de Markov i el modelat estadístic de l’assignació de recursos, ambdós suportant múltiples inquilins i múltiples serveis. En segon lloc, la tesi aborda el problema del control d’admissió de network slices proposant una metodologia per l¿estimació dels recursos requerits per una RAN slice, que es basa en la anàlisi de dades. Aquesta metodologia dona suport a la decisió sobre l’admissió o rebuig de noves sol·licituds de creació de RAN slices. En tercer lloc, la tesi explora el potencial de la intel·ligència artificial, concretament, de les tècniques de Deep Reinforcement Learning (DRL) per a tractar el problema de la compartició de capacitat en escenaris amb RAN slicing. Amb aquest objectiu, es proposa i s’avalua una solució de compartició de capacitat basada en DRL que distribueix la capacitat disponible en un escenari multicel·lular entre múltiples inquilins. Aquesta solució es planteja com una solución de Multi-Agent Reinforcement Learning (MARL) basat en Deep Q-Network. Finalment, aquesta tesi tracta diversos aspectes relacionats amb la implementació de la solució de compartició de capacitat basada en DRL, incloent-hi consideracions sobre la compatibilitat de la solució amb els estàndards, l’impacte de l’entrenament de la solució al seu comportament i rendiment, així com les eines i tecnologies necessàries per al desplegament de la solució en un entorn de xarxa real.El Network Slicing es una tecnología clave de la arquitectura del 5G que permite dividir la red en múltiples redes lógicas, conocidas como network slices, que se configuran de acuerdo a las necesidades de servicios y aplicaciones específicas. Así, el network slicing permite la materialización de las redes con múltiples inquilinos, donde una infraestructura de red común se comparte entre diferentes proveedores de comunicaciones, que actúan como inquilinos y que usan network slices diferentes. El soporte de múltiples inquilinos mediante el uso del network slicing en la red de acceso radio (RAN), que se conoce como RAN slicing, es un gran reto tecnológico, ya que comporta la configuración y operación de múltiples y diversos comportamientos sobre los recursos radio disponibles en cada uno de los nodos de la red de acceso. Además, esta configuración debe realizarse de tal manera que los requisitos específicos de cada inquilino se satisfagan y, al mismo tiempo, los recursos radio disponibles se utilicen eficazmente. Por lo tanto, es necesario introducir nuevas funcionalidades a diferentes niveles que permitan el despliegue de las RAN slices, desde funcionalidades relacionadas con la gestión de recursos radio (RRM) que incorporen parámetros para el RAN slicing a funcionalidades que proporcionen soporte a la gestión del ciclo de vida de las RAN slices. Esta tesis ha abordado esta necesidad proponiendo, desarrollando y evaluando diversas soluciones para el soporte del RAN slicing, lo que ha permitido analizar las capacidades, requisitos y limitaciones del RAN slicing desde diversas perspectivas. Específicamente, esta tesis se centra, en primer lugar, en realizar un análisis de funcionalidades de RRM que soportan escenarios con múltiples inquilinos y múltiples servicios, donde los servicios se definen según sus requisitos de 5G QoS. Este análisis se lleva a cabo mediante la caracterización de políticas de control de admisión mediante un modelo de Markov y el modelado a nivel estadístico de la asignación de recursos, ambos soportando múltiples inquilinos y múltiples servicios. En segundo lugar, la tesis aborda el problema del control de admisión de network slices proponiendo una metodología para la estimación de los recursos radio requeridos por una RAN slice que se basa en análisis de datos. Esta metodología da soporte a la decisión sobre la admisión o el rechazo de nuevas solicitudes de creación de RAN slice. En tercer lugar, la tesis explora el potencial de la inteligencia artificial, y en concreto, de las técnicas de Deep Reinforcement Learning (DRL) para tratar el problema de compartición de capacidad en escenarios de RAN slicing. Para ello, se propone y evalúa una solución de compartición de capacidad basada en DRL que distribuye la capacidad disponible de un escenario multicelular entre múltiples inquilinos. Esta solución se plantea como una solución de Multi-Agent Reinforcement Learning (MARL) basado en Deep Q-Network. Finalmente, en esta tesis se tratan diversos aspectos relacionados con la implementación de la solución de reparto de capacidad basada en DRL, incluyendo consideraciones sobre su compatibilidad con los estándares, el impacto del entrenamiento en el comportamiento y rendimiento conseguido, así como las herramientas y tecnologías necesarias para su despliegue en un entorno de red real.Postprint (published version