Adaptive RACH Congestion Management to Support M2M Communication in 4G LTE Networks

Machine to machine communication (M2M) or machine type communication (MTC) facilitates communication of two network enabled devices, without any human intervention, to take some intelligent decision based on the interaction of devices. Because of ubiquitous coverage and global connectivity, cellular networks are playing a major role in the deployment of M2M communications. Due to some unique characteristics of M2M communication, supporting M2M applications in cellular networks is very challenging. One of such challenge is congestion in radio access network (RAN) during RACH procedure. This is because of the fact that there are large numbers of M2M devices which access the radio network at the same time. As a solution, we propose an adaptive RACH congestion management function (ARC) which specifies congestion handling method to be used by all M2M devices based on the current congestion condition of the networ

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

5GAuRA. D3.3: RAN Analytics Mechanisms and Performance Benchmarking of Video, Time Critical, and Social Applications

5GAuRA deliverable D3.3.This is the final deliverable of Work Package 3 (WP3) of the 5GAuRA project, providing a report on the project’s developments on the topics of Radio Access Network (RAN) analytics and application performance benchmarking. The focus of this deliverable is to extend and deepen the methods and results provided in the 5GAuRA deliverable D3.2 in the context of specific use scenarios of video, time critical, and social applications. In this respect, four major topics of WP3 of 5GAuRA – namely edge-cloud enhanced RAN architecture, machine learning assisted Random Access Channel (RACH) approach, Multi-access Edge Computing (MEC) content caching, and active queue management – are put forward. Specifically, this document provides a detailed discussion on the service level agreement between tenant and service provider in the context of network slicing in Fifth Generation (5G) communication networks. Network slicing is considered as a key enabler to 5G communication system. Legacy telecommunication networks have been providing various services to all kinds of customers through a single network infrastructure. In contrast, by deploying network slicing, operators are now able to partition one network into individual slices, each with its own configuration and Quality of Service (QoS) requirements. There are many applications across industry that open new business opportunities with new business models. Every application instance requires an independent slice with its own network functions and features, whereby every single slice needs an individual Service Level Agreement (SLA). In D3.3, we propose a comprehensive end-to-end structure of SLA between the tenant and the service provider of sliced 5G network, which balances the interests of both sides. The proposed SLA defines reliability, availability, and performance of delivered telecommunication services in order to ensure that right information is delivered to the right destination at right time, safely and securely. We also discuss the metrics of slicebased network SLA such as throughput, penalty, cost, revenue, profit, and QoS related metrics, which are, in the view of 5GAuRA, critical features of the agreement.Peer ReviewedPostprint (published version

Signaling Congestion Control Mechanisms for Supporting Machine-To-Machine Communications in 4G LTE Cellular Networks

Typically, in Machine-to-Machine (M2M) communication system, an M2M device (sensor, meter, etc.) captures an event (pressure, inventory level, etc.), which is relayed through a communication network (wireless, wired or hybrid, cellular) to an application (software program), that translates the captured event into meaningful information without any human intervention. Based on this concept, several noble applications have been developed such as environment monitoring, smart grid, e-healthcare, and fleet management which will affect various aspects of our life

Adaptive access class barring for efficient mMTC

[EN] In massive machine-type communications (mMTC), an immense number of wireless devices communicate autonomously to provide users with ubiquitous access to information and services. The current 4G LTE-A cellular system and its Internet of Things (IoT) implementation, the narrowband IoT (NB-IoT), present appealing options for the interconnection of these wireless devices. However, severe congestion may arise whenever a massive number of highly-synchronized access requests occur. Consequently, access control schemes, such as the access class barring (ACB), have become a major research topic. In the latter, the precise selection of the barring parameters in a real-time fashion is needed to maximize performance, but is hindered by numerous characteristics and limitations of the current cellular systems. In this paper, we present a novel ACB configuration (ACBC) scheme that can be directly implemented at the cellular base stations. In our ACBC scheme, we calculate the ratio of idle to total available resources, which then serves as the input to an adaptive filtering algorithm. The main objective of the latter is to enhance the selection of the barring parameters by reducing the effect of the inherent randomness of the system. Results show that our ACBC scheme greatly enhances the performance of the system during periods of high congestion. In addition, the increase in the access delay during periods of light traffic load is minimal.This research has been supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R and Grant TEC2015-71932-REDT. The research of I. Leyva-Mayorga was partially funded by grant 383936 CONACYT-GEM 2014.Leyva-Mayorga, I.; Rodríguez-Hernández, MA.; Pla, V.; Martínez Bauset, J.; Tello-Oquendo, L. (2019). Adaptive access class barring for efficient mMTC. Computer Networks. 149:252-264. https://doi.org/10.1016/j.comnet.2018.12.003S25226414

On reliable and energy efficient massive wireless communications: the road to 5G

La quinta generación de redes móviles (5G) se encuentra a la vuelta de la esquina. Se espera provea de beneficios extraordinarios a la población y que resuelva la mayoría de los problemas de las redes 4G actuales. El éxito de 5G, cuya primera fase de estandarización ha sido completada, depende de tres pilares: comunicaciones tipo-máquina masivas, banda ancha móvil mejorada y comunicaciones ultra fiables y de baja latencia (mMTC, eMBB y URLLC, respectivamente). En esta tesis nos enfocamos en el primer pilar de 5G, mMTC, pero también proveemos una solución para lograr eMBB en escenarios de distribución masiva de contenidos. Específicamente, las principales contribuciones son en las áreas de: 1) soporte eficiente de mMTC en redes celulares; 2) acceso aleatorio para el reporte de eventos en redes inalámbricas de sensores (WSNs); y 3) cooperación para la distribución masiva de contenidos en redes celulares. En el apartado de mMTC en redes celulares, esta tesis provee un análisis profundo del desempeño del procedimiento de acceso aleatorio, que es la forma mediante la cual los dispositivos móviles acceden a la red. Estos análisis fueron inicialmente llevados a cabo por simulaciones y, posteriormente, por medio de un modelo analítico. Ambos modelos fueron desarrollados específicamente para este propósito e incluyen uno de los esquemas de control de acceso más prometedores: access class barring (ACB). Nuestro modelo es uno de los más precisos que se pueden encontrar en la literatura y el único que incorpora el esquema de ACB. Los resultados obtenidos por medio de este modelo y por simulación son claros: los accesos altamente sincronizados que ocurren en aplicaciones de mMTC pueden causar congestión severa en el canal de acceso. Por otro lado, también son claros en que esta congestión se puede prevenir con una adecuada configuración del ACB. Sin embargo, los parámetros de configuración del ACB deben ser continuamente adaptados a la intensidad de accesos para poder obtener un desempeño óptimo. En la tesis se propone una solución práctica a este problema en la forma de un esquema de configuración automática para el ACB; lo llamamos ACBC. Los resultados muestran que nuestro esquema puede lograr un desempeño muy cercano al óptimo sin importar la intensidad de los accesos. Asimismo, puede ser directamente implementado en redes celulares para soportar el tráfico mMTC, ya que ha sido diseñado teniendo en cuenta los estándares del 3GPP. Además de los análisis descritos anteriormente para redes celulares, se realiza un análisis general para aplicaciones de contadores inteligentes. Es decir, estudiamos un escenario de mMTC desde la perspectiva de las WSNs. Específicamente, desarrollamos un modelo híbrido para el análisis de desempeño y la optimización de protocolos de WSNs de acceso aleatorio y basados en cluster. Los resultados muestran la utilidad de escuchar el medio inalámbrico para minimizar el número de transmisiones y también de modificar las probabilidades de transmisión después de una colisión. En lo que respecta a eMBB, nos enfocamos en un escenario de distribución masiva de contenidos, en el que un mismo contenido es enviado de forma simultánea a un gran número de usuarios móviles. Este escenario es problemático, ya que las estaciones base de la red celular no cuentan con mecanismos eficientes de multicast o broadcast. Por lo tanto, la solución que se adopta comúnmente es la de replicar e contenido para cada uno de los usuarios que lo soliciten; está claro que esto es altamente ineficiente. Para resolver este problema, proponemos el uso de esquemas de network coding y de arquitecturas cooperativas llamadas nubes móviles. En concreto, desarrollamos un protocolo para la distribución masiva de contenidos, junto con un modelo analítico para su optimización. Los resultados demuestran que el modelo propuesto es simple y preciso, y que el protocolo puede reducir el conLa cinquena generació de xarxes mòbils (5G) es troba molt a la vora. S'espera que proveïsca de beneficis extraordinaris a la població i que resolga la majoria dels problemes de les xarxes 4G actuals. L'èxit de 5G, per a la qual ja ha sigut completada la primera fase del qual d'estandardització, depén de tres pilars: comunicacions tipus-màquina massives, banda ampla mòbil millorada, i comunicacions ultra fiables i de baixa latència (mMTC, eMBB i URLLC, respectivament, per les seues sigles en anglés). En aquesta tesi ens enfoquem en el primer pilar de 5G, mMTC, però també proveïm una solució per a aconseguir eMBB en escenaris de distribució massiva de continguts. Específicament, les principals contribucions són en les àrees de: 1) suport eficient de mMTC en xarxes cel·lulars; 2) accés aleatori per al report d'esdeveniments en xarxes sense fils de sensors (WSNs); i 3) cooperació per a la distribució massiva de continguts en xarxes cel·lulars. En l'apartat de mMTC en xarxes cel·lulars, aquesta tesi realitza una anàlisi profunda de l'acompliment del procediment d'accés aleatori, que és la forma mitjançant la qual els dispositius mòbils accedeixen a la xarxa. Aquestes anàlisis van ser inicialment dutes per mitjà de simulacions i, posteriorment, per mitjà d'un model analític. Els models van ser desenvolupats específicament per a aquest propòsit i inclouen un dels esquemes de control d'accés més prometedors: el access class barring (ACB). El nostre model és un dels més precisos que es poden trobar i l'únic que incorpora l'esquema d'ACB. Els resultats obtinguts per mitjà d'aquest model i per simulació són clars: els accessos altament sincronitzats que ocorren en aplicacions de mMTC poden causar congestió severa en el canal d'accés. D'altra banda, també són clars en què aquesta congestió es pot previndre amb una adequada configuració de l'ACB. No obstant això, els paràmetres de configuració de l'ACB han de ser contínuament adaptats a la intensitat d'accessos per a poder obtindre unes prestacions òptimes. En la tesi es proposa una solució pràctica a aquest problema en la forma d'un esquema de configuració automàtica per a l'ACB; l'anomenem ACBC. Els resultats mostren que el nostre esquema pot aconseguir un acompliment molt proper a l'òptim sense importar la intensitat dels accessos. Així mateix, pot ser directament implementat en xarxes cel·lulars per a suportar el trànsit mMTC, ja que ha sigut dissenyat tenint en compte els estàndards del 3GPP. A més de les anàlisis descrites anteriorment per a xarxes cel·lulars, es realitza una anàlisi general per a aplicacions de comptadors intel·ligents. És a dir, estudiem un escenari de mMTC des de la perspectiva de les WSNs. Específicament, desenvolupem un model híbrid per a l'anàlisi de prestacions i l'optimització de protocols de WSNs d'accés aleatori i basats en clúster. Els resultats mostren la utilitat d'escoltar el mitjà sense fil per a minimitzar el nombre de transmissions i també de modificar les probabilitats de transmissió després d'una col·lisió. Pel que fa a eMBB, ens enfoquem en un escenari de distribució massiva de continguts, en el qual un mateix contingut és enviat de forma simultània a un gran nombre d'usuaris mòbils. Aquest escenari és problemàtic, ja que les estacions base de la xarxa cel·lular no compten amb mecanismes eficients de multicast o broadcast. Per tant, la solució que s'adopta comunament és la de replicar el contingut per a cadascun dels usuaris que ho sol·liciten; és clar que això és altament ineficient. Per a resoldre aquest problema, proposem l'ús d'esquemes de network coding i d'arquitectures cooperatives anomenades núvols mòbils. En concret, desenvolupem un protocol per a realitzar la distribució massiva de continguts de forma eficient, juntament amb un model analític per a la seua optimització. Els resultats demostren que el model proposat és simple i precísThe 5th generation (5G) of mobile networks is just around the corner. It is expected to bring extraordinary benefits to the population and to solve the majority of the problems of current 4th generation (4G) systems. The success of 5G, whose first phase of standardization has concluded, relies in three pillars that correspond to its main use cases: massive machine-type communication (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communication (URLLC). This thesis mainly focuses on the first pillar of 5G: mMTC, but also provides a solution for the eMBB in massive content delivery scenarios. Specifically, its main contributions are in the areas of: 1) efficient support of mMTC in cellular networks; 2) random access (RA) event-reporting in wireless sensor networks (WSNs); and 3) cooperative massive content delivery in cellular networks. Regarding mMTC in cellular networks, this thesis provides a thorough performance analysis of the RA procedure (RAP), used by the mobile devices to switch from idle to connected mode. These analyses were first conducted by simulation and then by an analytical model; both of these were developed with this specific purpose and include one of the most promising access control schemes: the access class barring (ACB). To the best of our knowledge, this is one of the most accurate analytical models reported in the literature and the only one that incorporates the ACB scheme. Our results clearly show that the highly-synchronized accesses that occur in mMTC applications can lead to severe congestion. On the other hand, it is also clear that congestion can be prevented with an adequate configuration of the ACB scheme. However, the configuration parameters of the ACB scheme must be continuously adapted to the intensity of access attempts if an optimal performance is to be obtained. We developed a practical solution to this problem in the form of a scheme to automatically configure the ACB; we call it access class barring configuration (ACBC) scheme. The results show that our ACBC scheme leads to a near-optimal performance regardless of the intensity of access attempts. Furthermore, it can be directly implemented in 3rd Generation Partnership Project (3GPP) cellular systems to efficiently handle mMTC because it has been designed to comply with the 3GPP standards. In addition to the analyses described above for cellular networks, a general analysis for smart metering applications is performed. That is, we study an mMTC scenario from the perspective of event detection and reporting WSNs. Specifically, we provide a hybrid model for the performance analysis and optimization of cluster-based RA WSN protocols. Results showcase the utility of overhearing to minimize the number of packet transmissions, but also of the adaptation of transmission parameters after a collision occurs. Building on this, we are able to provide some guidelines that can drastically increase the performance of a wide range of RA protocols and systems in event reporting applications. Regarding eMBB, we focus on a massive content delivery scenario in which the exact same content is transmitted to a large number of mobile users simultaneously. Such a scenario may arise, for example, with video streaming services that offer a particularly popular content. This is a problematic scenario because cellular base stations have no efficient multicast or broadcast mechanisms. Hence, the traditional solution is to replicate the content for each requesting user, which is highly inefficient. To solve this problem, we propose the use of network coding (NC) schemes in combination with cooperative architectures named mobile clouds (MCs). Specifically, we develop a protocol for efficient massive content delivery, along with the analytical model for its optimization. Results show the proposed model is simple and accurate, and the protocol can lead to energy savings of up to 37 percent when compared to the traditional approach.Leyva Mayorga, I. (2018). On reliable and energy efficient massive wireless communications: the road to 5G [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/115484TESI

Prioritised Random Access Channel Protocols for Delay Critical M2M Communication over Cellular Networks

With the ever-increasing technological evolution, the current and future generation communication systems are geared towards accommodating Machine to Machine (M2M) communication as a necessary prerequisite for Internet of Things (IoT). Machine Type Communication (MTC) can sustain many promising applications through connecting a huge number of devices into one network. As current studies indicate, the number of devices is escalating at a high rate. Consequently, the network becomes congested because of its lower capacity, when the massive number of devices attempts simultaneous connection through the Random Access Channel (RACH). This results in RACH resource shortage, which can lead to high collision probability and massive access delay. Hence, it is critical to upgrade conventional Random Access (RA) techniques to support a massive number of Machine Type Communication (MTC) devices including Delay-Critical (DC) MTC. This thesis approaches to tackle this problem by modeling and optimising the access throughput and access delay performance of massive random access of M2M communications in Long-Term Evolution (LTE) networks. This thesis investigates the performance of different random access schemes in different scenarios. The study begins with the design and inspection of a group based 2-step Slotted-Aloha RACH (SA-RACH) scheme considering the coexistence of Human-to-Human (H2H) and M2M communication, the latter of which is categorised as: Delay-Critical user equipments (DC-UEs) and Non-Delay-Critical user equipments (NDC-UEs). Next, a novel RACH scheme termed the Priority-based Dynamic RACH (PD-RACH) model is proposed which utilises a coded preamble based collision probability model. Finally, being a key enabler of IoT, Machine Learning, i.e. a Q-learning based approach has been adopted, and a learning assisted Prioritised RACH scheme has been developed and investigated to prioritise a specific user group. In this work, the performance analysis of these novel RACH schemes show promising results compared to that of conventional RACH

Persistent Overload Control for Backlogged Machine to Machine Communications in Long Term Evolution Advanced Networks

Machine to Machine (M2M) has become one of the most attractive technologies in wireless communications. Despite this, Long Term Evolution Advanced (LTE-A) suffered the severe issues in machines initiating random access for all of the Base Stations (BTS). Therefore, this paper investigated the previous/existing methods and come out with the P-persistent scheme. The scheme is proposed with backlogged M2M devices that use to control Radio Access Network (RAN) overload in LTE-A network. The performance of the proposed scheme is evaluated through MATLAB based simulation. Through the evaluation, it can be seen that the M2M devices arrivals follow Beta distribution use for calculating the throughput and probabilities of collision, success and idle for M2M devices. The first case when P has a high value and the second case P have low value, this result show that in first case the success probability of M2M device is high about 73% limited number of M2M devices and have lower collision probability but in the other case M2M devices have lower success probability about 26% with high collision probability

Cellular networks for smart grid communication

The next-generation electric power system, known as smart grid, relies on a robust and reliable underlying communication infrastructure to improve the efficiency of electricity distribution. Cellular networks, e.g., LTE/LTE-A systems, appear as a promising technology to facilitate the smart grid evolution. Their inherent performance characteristics and well-established ecosystem could potentially unlock unprecedented use cases, enabling real-time and autonomous distribution grid operations. However, cellular technology was not originally intended for smart grid communication, associated with highly-reliable message exchange and massive device connectivity requirements. The fundamental differences between smart grid and human-type communication challenge the classical design of cellular networks and introduce important research questions that have not been sufficiently addressed so far. Motivated by these challenges, this doctoral thesis investigates novel radio access network (RAN) design principles and performance analysis for the seamless integration of smart grid traffic in future cellular networks. Specifically, we focus on addressing the fundamental RAN problems of network scalability in massive smart grid deployments and radio resource management for smart grid and human-type traffic. The main objective of the thesis lies on the design, analysis and performance evaluation of RAN mechanisms that would render cellular networks the key enabler for emerging smart grid applications. The first part of the thesis addresses the radio access limitations in LTE-based networks for reliable and scalable smart grid communication. We first identify the congestion problem in LTE random access that arises in large-scale smart grid deployments. To overcome this, a novel random access mechanism is proposed that can efficiently support real-time distribution automation services with negligible impact on the background traffic. Motivated by the stringent reliability requirements of various smart grid operations, we then develop an analytical model of the LTE random access procedure that allows us to assess the performance of event-based monitoring traffic under various load conditions and network configurations. We further extend our analysis to include the relation between the cell size and the availability of orthogonal random access resources and we identify an additional challenge for reliable smart grid connectivity. To this end, we devise an interference- and load-aware cell planning mechanism that enhances reliability in substation automation services. Finally, we couple the problem of state estimation in wide-area monitoring systems with the reliability challenges in information acquisition. Using our developed analytical framework, we quantify the impact of imperfect communication reliability in the state estimation accuracy and we provide useful insights for the design of reliability-aware state estimators. The second part of the thesis builds on the previous one and focuses on the RAN problem of resource scheduling and sharing for smart grid and human-type traffic. We introduce a novel scheduler that achieves low latency for distribution automation traffic while resource allocation is performed in a way that keeps the degradation of cellular users at a minimum level. In addition, we investigate the benefits of Device-to-Device (D2D) transmission mode for event-based message exchange in substation automation scenarios. We design a joint mode selection and resource allocation mechanism which results in higher data rates with respect to the conventional transmission mode via the base station. An orthogonal resource partition scheme between cellular and D2D links is further proposed to prevent the underutilization of the scarce cellular spectrum. The research findings of this thesis aim to deliver novel solutions to important RAN performance issues that arise when cellular networks support smart grid communication.Las redes celulares, p.e., los sistemas LTE/LTE-A, aparecen como una tecnología prometedora para facilitar la evolución de la próxima generación del sistema eléctrico de potencia, conocido como smart grid (SG). Sin embargo, la tecnología celular no fue pensada originalmente para las comunicaciones en la SG, asociadas con el intercambio fiable de mensajes y con requisitos de conectividad de un número masivo de dispositivos. Las diferencias fundamentales entre las comunicaciones en la SG y la comunicación de tipo humano desafían el diseño clásico de las redes celulares e introducen importantes cuestiones de investigación que hasta ahora no se han abordado suficientemente. Motivada por estos retos, esta tesis doctoral investiga los principios de diseño y analiza el rendimiento de una nueva red de acceso radio (RAN) que permita una integración perfecta del tráfico de la SG en las redes celulares futuras. Nos centramos en los problemas fundamentales de escalabilidad de la RAN en despliegues de SG masivos, y en la gestión de los recursos radio para la integración del tráfico de la SG con el tráfico de tipo humano. El objetivo principal de la tesis consiste en el diseño, el análisis y la evaluación del rendimiento de los mecanismos de las RAN que convertirán a las redes celulares en el elemento clave para las aplicaciones emergentes de las SGs. La primera parte de la tesis aborda las limitaciones del acceso radio en redes LTE para la comunicación fiable y escalable en SGs. En primer lugar, identificamos el problema de congestión en el acceso aleatorio de LTE que aparece en los despliegues de SGs a gran escala. Para superar este problema, se propone un nuevo mecanismo de acceso aleatorio que permite soportar de forma eficiente los servicios de automatización de la distribución eléctrica en tiempo real, con un impacto insignificante en el tráfico de fondo. Motivados por los estrictos requisitos de fiabilidad de las diversas operaciones en la SG, desarrollamos un modelo analítico del procedimiento de acceso aleatorio de LTE que nos permite evaluar el rendimiento del tráfico de monitorización de la red eléctrica basado en eventos bajo diversas condiciones de carga y configuraciones de red. Además, ampliamos nuestro análisis para incluir la relación entre el tamaño de celda y la disponibilidad de recursos de acceso aleatorio ortogonales, e identificamos un reto adicional para la conectividad fiable en la SG. Con este fin, diseñamos un mecanismo de planificación celular que tiene en cuenta las interferencias y la carga de la red, y que mejora la fiabilidad en los servicios de automatización de las subestaciones eléctricas. Finalmente, combinamos el problema de la estimación de estado en sistemas de monitorización de redes eléctricas de área amplia con los retos de fiabilidad en la adquisición de la información. Utilizando el modelo analítico desarrollado, cuantificamos el impacto de la baja fiabilidad en las comunicaciones sobre la precisión de la estimación de estado. La segunda parte de la tesis se centra en el problema de scheduling y compartición de recursos en la RAN para el tráfico de SG y el tráfico de tipo humano. Presentamos un nuevo scheduler que proporciona baja latencia para el tráfico de automatización de la distribución eléctrica, mientras que la asignación de recursos se realiza de un modo que mantiene la degradación de los usuarios celulares en un nivel mínimo. Además, investigamos los beneficios del modo de transmisión Device-to-Device (D2D) en el intercambio de mensajes basados en eventos en escenarios de automatización de subestaciones eléctricas. Diseñamos un mecanismo conjunto de asignación de recursos y selección de modo que da como resultado tasas de datos más elevadas con respecto al modo de transmisión convencional a través de la estación base. Finalmente, se propone un esquema de partición de recursos ortogonales entre enlaces celulares y D2Postprint (published version

Efficient support of the upcoming massive number of IoT devices

National audienc