Power conservation has become a severe issue in devices since battery capability advancement is not keeping pace with the swift development of other technologies such as processing technologies. This issue becomes critical when both the number of resource-intensive applications and the number of connected devices are rapidly growing. The former results in an increase in power consumption per device, and the latter causes an increase in the total power consumption of devices. Mobile edge computing (MEC) and low power wide area networks (LPWANs) are raised as two important research areas in wireless networks, which can assist devices to save power. On the one hand, devices are being considered as a platform to run resource-intensive applications while they have limited resources such as battery and processing capabilities. On the other hand, LPWANs raised as an important enabler for massive IoT (Internet of Things) to provide long-range and reliable connectivity for low power devices. The scope of this thesis spans over these two main research areas: (1) MEC, where devices can use radio resources to offload their processing tasks to the cloud to save energy. (2) LPWAN, with grant-free radio access where devices from different technology transmit their packets without any handshaking process. In particular, we consider a MEC network, where the processing resources are distributed in the proximity of the users. Hence, devices can save energy by transmitting the data to be processed to the edge cloud provided that the delay requirement is met and transmission power consumption is less than the local processing power consumption. This thesis addresses the question of whether to offload or not to minimize the uplink power consumption in a multi-cell multi-user MEC network. We consider the maximum acceptable delay as the QoS metric to be satisfied in our system. We formulate the problem as a mixed-integer nonlinear problem, which is converted into a convex form using D.C. approximation. To solve the converted optimization problem, we have proposed centralized and distributed algorithms for joint power allocation and channel assignment together with decision-making on job offloading. Our results show that there exists a region in which offloading can save power at mobile devices and increases the battery lifetime. Another focus of this thesis is on LPWANs, which are becoming more and more popular, due to the limited battery capacity and the ever-increasing need for durable battery lifetime for IoT networks. Most studies evaluate the system performance assuming single radio access technology deployment. In this thesis, we study the impact of coexisting competing radio access technologies on the system performance. We consider K technologies, defined by time and frequency activity factors, bandwidth, and power, which share a set of radio resources. Leveraging tools from stochastic geometry, we derive closed-form expressions for the successful transmission probability, expected battery lifetime, experienced delay, and expected number of retransmissions. Our analytical model, which is validated by simulation results, provides a tool to evaluate the coexistence scenarios and analyze how the introduction of a new coexisting technology may degrade the system performance in terms of success probability, delay, and battery lifetime. We further investigate the interplay between traffic load, the density of access points, and reliability/delay of communications, and examine the bounds beyond which, mean delay becomes infinite. / Antalet anslutna enheter till nätverk ökar. Det finns olika trender som mobil edgecomputing (MEC) och low power wide area-nätverk (LPWAN) som har blivit intressantai trådlösa nätverk. Därför står trådlösa nätverk inför nya utmaningar som ökadenergiförbrukning. I den här avhandlingen beaktar vi dessa två mobila nätverk. I MECavlastar mobila enheter sina bearbetningsuppgifter till centraliserad beräkningsresurser (”molnet”). I avhandlingensvarar vi på följande fråga: När det är energieffektivt att avlasta dessa beräkningsuppgifter till molnet?Vi föreslår två algoritmer för att bestämma den rätta tiden för överflyttning av beräkningsuppgifter till molnet.I LPWANs, antar vi att det finns ett mycket stort antal enheter av olika art som kommunicerar mednätverket. De använder s.k. ”Grant-free”-åtkomst för att ansluta till nätverket, där basstationerna inte ger explicita sändningstillstånd till enheterna. Denanalytiska modell som föreslås i avhandlingen utgör ett verktyg för att utvärdera sådana samexistensscenarier.Med verktygen kan vi analysera olika systems prestanda när det gäller framgångssannolikhet, fördröjning och batteriershållbarhetstid. / <p>QC 20200228</p> / SOOGreen

The increasing demand for mobile data has placed significant strain on radio access networks (RANs), leading to a continuous need for increased network capacity. In keeping with that, a significant advancement in modern RANs is the ability to utilize several receivers and transmitters, to allow for beamforming. One way to increase the capacity of the network is therefore to optimize the resource allocation by preprocessing the transmitted signals, which involves several costly matrix multiplications (MMs). The aim of the project was to investigate the potential of accelerating Ericsson's RAN simulations by using AI based approximate matrix multiplication (AMM) algorithms. The main focus was on the multiply additionless (MADDNESS) algorithm, a product quantization technique that has achieved speedups of up to 100 times compared to exact MM, and 10 times faster than previous AMM methods. A complex matrix handling version of MADDNESS was implemented in Java and Python respectively, and its speed and accuracy were evaluated against Ericsson's current MM implementation. The proposed implementation did not beat the benchmark with respect to speed, instead resulting in a 4-10 times slowdown in runtime. However, this may largely be due to the fact that the used languages do not allow for complete control over memory resource allocation. As such, the implementations at hand do not incorporate all the crucial features of the algorithm. Particularly, the handicapped version does not fully leverage the vectorization potential, which is one of the key contributors to the speed of the algorithm. Consequently, further improvements are necessary before employing the techniques in an end-to-end implementation. / Den växande efterfrågan på mobildata har ökat belastningen på dagens radionätverk (RAN) och har medfört ett behov av att utvidga dess kapacitet. En betydande innovation inom RAN är beamforming, vilket är förmågan att fokusera digitala signaler mot mottagaren och på så vis öka singalstyrkan. En metod för att öka kapaciteten i ett nätverk är att optimera både kvaliteten av och resursallokeringen mellan nätverkets digitala kanaler, vilket medför tidskrävande matrismultiplikationer. Syftet med denna studie var att utforska om AI-baserade approximativa matrismultiplikationsalgoritmer har potentialen att accelerera Ericssons digitala tvilling-simuleringar. Studien fokuserade i huvudsak på produktkvantiseringsalgoritmen MADDNESS som påvisat potentialen att accelerera exakta matrismultiplikationer med en faktor 100, samt en faktor 10 snabbare än jämförbara approximativa metoder. En modifierad version av MADDNESS, som behandlar komplexa matriser, implementerades i Java samt Python, varefter precisionen och hastigheten utvärderades. Den föreslagna implementationen resulterade i en försämring med avseende på hastigheten med en faktor 4-10 jämfört med Ericssons nuvarande algoritmer. Den föreslagna implementationen saknar effektiv minnesallokering och misslyckas följaktligen att till fullo ta tillvara på vektoriseringspotentialen i MADDNESS. Detta indikerar att det är nödvändigt för ytterligare förbättringar innan algoritmen är användbar i den givna simuleringsmiljön.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.

Open Radio Access Networks (Open RANs) enable flexible cellular network deployments by adopting open-source software and white-box hardware to build reference architectures customizable to innovative target use cases. The Open Radio Access Network (O-RAN) Alliance defines specifications introducing new Radio Access Network (RAN) Intelligent Controller (RIC) functions that leverage open interfaces between disaggregated RAN elements to provide precise RAN control and monitoring capabilities using applications called xApps and rApps. Multiple xApps targeting novel use cases have been developed by the O-RAN Software Community (OSC) and incubated on the Near-Real-Time RIC (Near-RT RIC) platform. However, the Near-RT RIC has, so far, been demonstrated to support only a single xApp capable of controlling the RAN elements. This work studies the scalability of the OSC Near-RT RIC to support simultaneous control signaling by multiple xApps targeting the RAN element. We particularly analyze its internal message routing mechanism and experimentally expose the design limitations of the OSC Near-RT RIC in supporting simultaneous xApp control. To this end, we extend an existing open-source RAN slicing xApp and prototype a slice-aware User Equipment (UE) admission control xApp implementing the RAN Control E2 Service Model (E2SM) to demonstrate a multi-xApp control signaling use case and assess the control routing capability of the Near-RT RIC through an end-to-end O-RAN experiment using the OSC Near-RT RIC platform and an open-source Software Defined Radio (SDR) stack. We also propose and implement a tag-based message routing strategy for disambiguating multiple xApps to enable simultaneous xApp control. Our experimental results prove that our routing strategy ensures 100% delivery of control messages between multiple xApps and E2 Nodes while guaranteeing control scalability and xApp non-repudiation. Using the improved Near-RT RIC platform, we assess the security posture and resiliency of the OSC Near-RT RIC in the event of volumetric application layer Denial of Service (DoS) attacks exploiting the E2 interface and the E2 Application Protocol (E2AP). We design a DoS attack agent capable of orchestrating a signaling storm attack and a high-intensity resource exhaustion DoS attack on the Near-RT RIC platform components. Additionally, we develop a latency monitoring xApp solution to detect application layer signaling storm attacks. The experimental results indicate that signaling storm attacks targeting the E2 Terminator on the Near-RT RIC cause control loop violations over the E2 interface affecting service delivery and optimization for benign E2 Nodes. We also observe that a high-intensity E2 Setup DoS attack results in unbridled memory resource consumption leading to service interruption and application crash. Our results also show that the E2 interface at the Near-RT RIC is vulnerable to volumetric application layer DoS attacks, and robust monitoring, load-balancing, and DoS mitigation strategies must be incorporated to guarantee resiliency and high reliability of the Near-RT RIC. / Master of Science / Telecommunication networks need sophisticated controllers to support novel use cases and applications. Cellular base stations can be managed and optimized for better user experience through an intelligent radio controller called the Near-Real-Time Radio Access Network (RAN) Intelligent Controller (RIC) (Near-RT RIC), defined by the Open Radio Access Network (O-RAN) Alliance. This controller supports simultaneous connections to multiple base stations through the E2 interface and allows simple radio applications called xApps to control the behavior of those base stations. In this research work, we study the performance and behavior of the Near-RT RIC when a malicious or compromised base station tries to overwhelm the controller through a Denial of Service (DoS) attack. We develop a solution to determine the application layer communication delay between the controller and the base station to detect potential attacks trying to compromise the functionality and availability of the controller. To implement this solution, we also upgrade the controller to support multiple radio applications to interact and control one or more base stations simultaneously. Through the developed solution, we prove that the O-RAN Software Community (OSC) Near-RT RIC is highly vulnerable to DoS attacks from malicious base stations targeting the controller over the E2 interface.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increases energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices causes a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.

Driven by the surging need for seamless connectivity, research in the wireless communication area has dramatically evolved over the years to meet the increasing demand for data rate and seamless coverage. Such evolvement concurs with a notable increase in data traffic and the widespread of data-hungry devices, thereby inflicting stringent requirements on terrestrial networks. Despite the tremendous advances achieved through the past generations of wireless systems, almost half of the world's population remains unconnected, leading to an accentuated digital divide problem. Therefore, this work invigorates a new connectivity solution that integrates aerial and terrestrial communications with a high-altitude platform station (HAPS) to promote a sustainable connectivity landscape. The connectivity solution adopted in this thesis specifically integrates terrestrial base stations with hot-air balloons under the framework of a cloud-enabled HAPS via a data-sharing fronthauling strategy. The aerial (hot-air balloons) and terrestrial base stations, grouped into disjoint clusters, coordinate their mutual transmission to serve aerial (i.e., drones) and terrestrial users. This work studies the downlink communication from the cloud-enabled HAPS to the aerial and terrestrial users under practical system considerations, namely the limited transmit power and the limited-capacity fronthaul link, per-base station. To this end, the first part of the thesis devises a specific optimization problem that maximizes the network sum-rate while accounting for system design constraints to determine the user association strategy, i.e., user to terrestrial clusters or user to air clusters, and the associated beamforming vectors. The second part of the thesis, then, designs a different resource allocations optimization problem that accounts for the fairness among the users, thus adopting a proportionally fair scheduling scheme to assign users on frequency tones to maximize the log of the long-term average rate. On this account, the work solves a handful of non-convex intricate optimization problems using techniques from optimization theory, namely, fractional programming and $\ell_0$-norm approximation. The work consequently outlines the gains realized by providing on-demand coverage in crowded and unserved areas. Moreover, the thesis illustrates the benefits of coordinating the operations of aerial and terrestrial base stations for interference management, load-balancing, and fairness measures.

Mobile communication technology has become crucial in shaping the way modern society functions. The evolution of cellular networks has created an increasingly interconnected world, supporting various heterogeneous infrastructures. With the rollout of 5G, cellular networks are not only expected to support social and communication transformations, but also techno-economic growth for various industry, private and enterprise users. The approach of standardizing 5G Radio Access Network (RAN) architecture has been different from previous generations as it calls for more virtualized and software-based approaches that are flexible and open. The concept of Open RAN is a movement for open interfaces between the disaggregation of software and hardware of the RAN. Traditionally, the RAN market has been dominated by a handful of incumbent vendors deploying purpose-built RAN solutions. However, Open RAN enables an ecosystem that invites multiple-vendor solutions and creates a completely different market dynamic. This thesis explored the competitive conditions for incumbent and small vendors in the Open RAN ecosystem. This was also answered within the context of scale economies of vendors and implications of enterprise solutions in Open RAN. The study applied an exploratory and inductive approach where the researcher analyzed literature, as well as conducted interviews with several industry experts. The conclusions of the study suggests that incumbent vendors will lose shares in the RAN market as they will have to compete with smaller vendors that try to establish themselves. It was also suggested that the current immature state of Open RAN is not suitable for mission-critical deployments, but is instead a more viable option for software-based enterprise solutions. Further, it is suggested that dynamic relationships between incumbents and smaller vendors is necessary in order to drive the development of Open RAN. / Mobil kommunikationsteknik har blivit avgörande för utformandet av det moderna samhället. Utvecklingen av cellulära nätverk har skapat en alltmer sammankopplad värld som stödjer olika heterogena infrastrukturer. Med utbyggnaden av 5G förväntas cellulära nätverk inte bara stödja sociala och kommunikationstransformeringar, utan även tekno-ekonomisk tillväxt för olika industri-, privat- och företagsanvändare. Tillvägagångssättet att standardisera 5G radioåtkomstnätverk (RAN) arkitektur har varit annorlunda än tidigare generationer eftersom det kräver mer virtualiserade och mjukvarubaserade metoder som är flexibla och öppna. Konceptet bakom öppna RAN (Open RAN) är en rörelse för öppna gränssnitt mellan uppdelningen av mjukvara och hårdvara i RAN. Traditionellt har RAN-marknaden dominerats av ett fåtal etablerade leverantörer som implementerar specialbyggda RAN-lösningar. Open RAN möjliggör dock ett ekosystem som öppnar upp för multileverantör lösningar och skapar en helt annan marknadsdynamik. Den här uppsatsen undersökte konkurrensvillkoren för etablerade och små leverantörer i Open RAN-ekosystemet. Detta besvarades också inom ramen för skalfördelar för leverantörer och implikationer av företagslösningar i Open RAN. Studien tillämpade ett explorativt och induktivt tillvägagångssätt där forskaren analyserade litteratur, samt genomförde intervjuer med flera branschexperter. Slutsatserna av studien tyder på att etablerade leverantörer kommer att förlora andelar på RAN-marknaden eftersom de kommer att behöva konkurrera med mindre leverantörer som försöker etablera sig. Det föreslogs också att det nuvarande omogna tillståndet för Open RAN inte är lämpligt för kritiska RAN-lösningar, istället är det ett mer genomförbart alternativ för mjukvarubaserade företagslösningar. Vidare föreslås det att dynamiska relationer mellan etablerade och mindre leverantörer är nödvändiga för att driva utvecklingen av Open RAN.

Cette thèse aborde de façon systémique l’analyse de la situation des TICs en Afrique Centrale, elle identifie les problématiques liées à l’accès universel et étudie les politiques d’harmonisation des TICs. Cette analyse conduit alors à proposer une cartographie cible intégrée permettant de réduire la fracture numérique. Non seulement les différentes technologies optiques et radio large bande sont mises à contribution mais décrites en vue de relater les notions de base permettant d’appréhender les avantages et inconvénients de chaque technologie. Ceci a permis par la suite de proposer une démarche méthodologique de modélisation de l’indicateur d’accès au service universel couplée à une stratégie d’optimisation révélant, d’une part le gap technologique à combler et d’autre part, prédisant le niveau d’accès technologique à atteindre en fonction des politiques d’investissement du Fonds de Service Universel. Aussi, outre la proposition de cette démarche de modélisation cette thèse apporte une autre contribution en développant un modèle d’architecture réseau basé sur les technologies radio et en proposant une méthodologie consistant à intégrer les différents paramètres impliqués dans le choix des technologies à déployer en vue de l’accès au service universel. De plus, elle se projette dans l’évolution future de la technologie en offrant une ouverture sur les technologies hybrides. / This thesis deals systematically with the analysis of the situation of ICTs in Central Africa, it identifies the problems related to universal access and studies ICTs harmonization policies. This analysis then enables the proposal of an integrated target mapping to reduce the digital divide. Not only the different optical and radio broadband technologies are used but described to relate the basic concepts allowing to apprehend the advantages and disadvantages of each technology. This allowed us to propose a methodological approach to modeling the universal access and service indicator coupled with an optimization strategy revealing, on the one hand, the technological gap to be filled and on the other hand, predicting the access level based on technologies to achieve in accordance with the investment policies of the Universal Service Fund. Besides the proposal of this modeling approach, other contributions of this thesis is developing a network model architecture based on radio technologies and proposing a methodology consisting of integrating the various parameters involved in the choice of technologies to be deployed for access and universal service. In addition, it is projected into the future evolution of solutions that leads to hybrid technologies.

Pour faire face à la croissance rapide du trafic mobile, différentes technologies d'accès radio (par exemple, HSPA, LTE, WiFi, et WiMAX) sont intégrées et gérées conjointement. Dans ce contexte, la sélection de TAR est une fonction clé pour améliorer les performances du réseau et l'expérience de l'utilisateur. Elle consiste à décider quelle TAR est la plus appropriée aux mobiles. Quand l'intelligence est poussée à la périphérie du réseau, les mobiles décident de manière autonome de leur meilleur TAR. Ils cherchent à maximiser égoïstement leur utilité. Toutefois, puisque les mobiles ne disposent d'aucune information sur les conditions de charge du réseau, leurs décisions peuvent conduire à une inefficacité de la performance. En outre, déléguer les décisions au réseau optimise la performance globale, mais au prix d'une augmentation de la complexité du réseau, des charges de signalisation et de traitement. Dans cette thèse, au lieu de favoriser une de ces deux approches décisionnelles, nous proposons un cadre de décision hybride: le réseau fournit des informations pour les mobiles pour mieux décider de leur TAR. Plus précisément, les utilisateurs mobiles choisissent leur TAR en fonction de leurs besoins et préférences individuelles, ainsi que des paramètres de coût monétaire et de QoS signalés par le réseau. En ajustant convenablement les informations du réseau, les décisions des utilisateurs répondent globalement aux objectifs de l'opérateur. Nous introduisons d'abord notre cadre de décision hybride. Afin de maximiser l'expérience de l'utilisateur, nous présentons une méthode de décision multicritère (MDMC) basée sur la satisfaction. Outre leurs conditions radio, les utilisateurs mobiles tiennent compte des paramètres de coût et de QoS, signalées par le réseau, pour évaluer les TAR disponibles. En comparaison avec les solutions existantes, notre algorithme répond aux besoins de l'utilisateur (par exemple, les demandes en débit, la tolérance de coût, la classe de trafic), et évite les décisions inadéquates. Une attention particulière est ensuite portée au réseau pour s'assurer qu'il diffuse des informations décisionnelles appropriées, afin de mieux exploiter ses ressources radio alors que les mobiles maximisent leur propre utilité. Nous présentons deux méthodes heuristiques pour dériver dynamiquement quoi signaler aux mobiles. Puisque les paramètres de QoS sont modulées en fonction des conditions de charge, l'exploitation des ressources radio s'est avérée efficace. Aussi, nous nous concentrons sur l'optimisation de l'information du réseau. La dérivation des paramètres de QoS est formulée comme un processus de décision semi-markovien, et les stratégies optimales sont calculées en utilisant l'algorithme de Policy Iteration. En outre, et puisque les paramètres du réseau ne peuvent pas être facilement obtenues, une approche par apprentissage par renforcement est introduite pour dériver quoi signaler aux mobiles. / To cope with the rapid growth of mobile broadband traffic, various radio access technologies (e.g., HSPA, LTE, WiFi, and WiMAX) are being integrated and jointly managed. Radio Access Technology (RAT) selection, devoted to decide to what RAT mobiles should connect, is a key functionality to improve network performance and user experience. When intelligence is pushed to the network edge, mobiles make autonomous decisions regarding selection of their most appropriate RAT. They aim to selfishly maximize their utility. However, because mobiles have no information on network load conditions, their decisions may lead to performance inefficiency. Moreover, delegating decisions to the network optimizes overall performance, but at the cost of increased network complexity, signaling, and processing load. In this thesis, instead of favoring either of these decision-making approaches, we propose a hybrid decision framework: the network provides information for the mobiles to make robust RAT selections. More precisely, mobile users select their RAT depending on their individual needs and preferences, as well as on the monetary cost and QoS parameters signaled by the network. By appropriately tuning network information, user decisions are globally expected to meet operator objectives, avoiding undesirable network states. We first introduce our hybrid decision framework. Decision makings, on the network and user sides, are investigated. To maximize user experience, we present a satisfaction-based Multi-Criteria Decision-Making (MCDM) method. In addition to their radio conditions, mobile users consider the cost and QoS parameters, signaled by the network, to evaluate serving RATs. In comparison with existing MCDM solutions, our algorithm meets user needs (e.g., traffic class, throughput demand, cost tolerance), avoiding inadequate decisions. A particular attention is then addressed to the network to make sure it broadcasts suitable decisional information, so as to better exploit its radio resources while mobiles maximize their own utility. We present two heuristic methods to dynamically derive what to signal to mobiles. While QoS parameters are modulated as a function of the load conditions, radio resources are shown to be efficiently exploited. Moreover, we focus on optimizing network information. Deriving QoS parameters is formulated as a semi-Markov decision process, and optimal policies are computed using the Policy Iteration algorithm. Also, and since network parameters may not be easily obtained, a reinforcement learning approach is introduced to derive what to signal to mobiles. The performances of optimal, learning-based, and heuristic policies are analyzed. When thresholds are pertinently set, our heuristic method provides performance very close to the optimal solution. Moreover, although lower performances are observed, our learning-based algorithm has the crucial advantage of requiring no prior parameterization.

Currently, the IPv4 protocol is heavily used by institutions, companies and individuals, but every day there is a higher number of devices connected to the network such as home appliances, mobile phones or tablets. Each machine or device needs to have its own IP address to communicate with other machines connected to Internet. This implies the need for multiple IP addresses for a single user and the current protocol begins to show some deficiencies due to IPv4 address space exhaustion. Therefore, for several years experts have been working on an IP protocol update: the IPv6 128-bit version can address up to about 340 quadrillion system devices concurrently. With IPv6, today, every person on the planet could have millions of devices simultaneously connected to the Internet. The choice of the IP protocol version affects the performance of the UMTS mobile network and the browsers as well. The aim of the project is to measure how the IPv6 protocol performs compared to the previous IPv4 protocol. It is expected that the IPv6 protocol generates a smaller amount of signalling and less time is required to fully load a web page. We have analysed some KPIs (IP data, signalling, web load time and battery) in lab environment using Smartphones, to observe the behaviour of both, the network and the device.  The main conclusion of the thesis is that IPv6 really behaves as expected and generates savings in signalling, although the IP data generated is larger due to the size of the headers. However, there is still much work as only the most important webpages and the applications with a high level of market penetration operate well over the IPv6 protocol. / Cada día existe un mayor número de dispositivos conectados a la red, tales como electrodomésticos, teléfonos móviles inteligentes o tabletas, por lo que la red debe evolucionar constantemente y ser capaz de proveer servicio a todos los usuarios. Cada equipo necesita tener su propia dirección IP para comunicarse con otras máquinas conectadas a Internet, por lo que es necesario tener un gran número de direcciones IP y la versión del protocolo actual comienza a mostrar algunas deficiencias (debido fundamentalmente al agotamiento del espacio de direccionamiento IPv4 y algunas funciones de seguridad que han quedado obsoletas). Desde hace varios años, los expertos están trabajando en una actualización del protocolo IP: la versión seis (llamada IPv6) que utiliza 128 bits para el direccionamiento pudiendo administrar simultáneamente hasta unos 340 trillones de dispositivos al mismo tiempo. La elección de la versión del protocolo IP afecta al comportamiento de la red móvil, ya que los expertos todavía están optimizando y realizando cambios en la arquitectura de red y en los dispositivos para soportar el protocolo IPv6. El objetivo del proyecto consiste en comparar y evaluar las diferentes versiones del protocolo IP utilizado, en gran medida, para acceder a la red de internet. La principal conclusión del proyecto es que IPv6 realmente se comporta como se espera y genera ahorros en la señalización, aunque los datos IP generados son mayores. Sin embargo, aún queda mucho trabajo por hacer, ya que sólo las páginas más importantes y las aplicaciones más utilizadas por los usuarios funcionan bien sobre el protocolo IPv6.