Tesi: "Radio access networks, RAN"

1

Schmidt, Robert. "Slicing in heterogeneous software-defined radio access networks". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS525.

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Les réseaux 5G sont envisagés comme un changement de paradigme vers des réseaux orientés services. Dans cette thèse, nous étudions comment combiner efficacement le découpage en tranches et le SD-RAN afin de fournir le niveau requis de flexibilité et de programmabilité dans l'infrastructure RAN pour réaliser des réseaux multi-locataires orientés services. Premièrement, nous concevons une abstraction d'une station de base pour représenter les stations de base logiques et décrire un service de réseau virtualisé. Deuxièmement, nous proposons une nouvelle plateforme SD-RAN conforme aux normes, appelée FlexRIC, sous la forme d'un kit de développement logiciel (SDK). Troisièmement, nous fournissons une conception modulaire pour un cadre d'ordonnancement MAC tenant compte des tranches afin de gérer et de contrôler efficacement les ressources radio dans un environnement multiservice avec un support de qualité de service (QoS). Enfin, nous présentons une couche de virtualisation SD-RAN dynamique basée sur le SDK FlexRIC et le cadre d'ordonnancement MAC pour composer de manière flexible une infrastructure SD-RAN multiservice et fournir une programmabilité pour de multiples contrôleurs SD-RAN
5G networks are envisioned to be a paradigm shift towards service-oriented networks. In this thesis, we investigate how to efficiently combine slicing and SD-RAN to provide the required level of flexibility and programmability in the RAN infrastructure to realize service-oriented multi-tenant networks. First, we devise an abstraction of a base station to represent logical base stations and describe a virtualized network service. Second, we propose a novel standard-compliant SD-RAN platform, named FlexRIC, in the form of a software development kit (SDK). Third, we provide a modular design for a slice-aware MAC scheduling framework to efficiently manage and control the radio resources in a multi-service environment with quality-of-service (QoS) support. Finally, we present a dynamic SD-RAN virtualization layer based on the FlexRIC SDK and MAC scheduling framework to flexibly compose a multi-service SD-RAN infrastructure and provide programmability for multiple SD-RAN controllers

2

Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043/document.

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Cloud-Radio Access Network (C-RAN) est une architecture prometteuse pour faire face à l’augmentation exponentielle des demandes de trafic de données et surmonter les défis des réseaux de prochaine génération (5G). Le principe de base de CRAN consiste à diviser la station de base traditionnelle en deux entités : les unités de bande de base (BaseBand Unit, BBU) et les têtes radio distantes (Remote Radio Head, RRH) et à mettre en commun les BBUs de plusieurs stations dans des centres de données centralisés (pools de BBU). Ceci permet la réduction des coûts d’exploitation, l’amélioration de la capacité du réseau ainsi que des gains en termes d’utilisation des ressources. Pour atteindre ces objectifs, les opérateurs réseaux ont besoin d’investiguer de nouveaux algorithmes pour les problèmes d’allocation de ressources permettant ainsi de faciliter le déploiement de l’architecture C-RAN. La plupart de ces problèmes sont très complexes et donc très difficiles à résoudre. Par conséquent, nous utilisons l’optimisation combinatoire qui propose des outils puissants pour adresser ce type des problèmes.Un des principaux enjeux pour permettre le déploiement du C-RAN est de déterminer une affectation optimale des RRHs (antennes) aux centres de données centralisés (BBUs) en optimisant conjointement la latence sur le réseau de transmission fronthaul et la consommation des ressources. Nous modélisons ce problème à l’aide d’une formulation mathématique basée sur une approche de programmation linéaire en nombres entiers permettant de déterminer les stratégies optimales pour le problème d’affectation des ressources entre RRH-BBU et nous proposons également des heuristiques afin de pallier la difficulté au sens de la complexité algorithmique quand des instances larges du problème sont traitées, permettant ainsi le passage à l’échelle. Une affectation optimale des antennes aux BBUs réduit la latence de communication attendue et offre des gains en termes d’utilisation des ressources. Néanmoins, ces gains dépendent fortement de l’augmentation des niveaux d’interférence inter-cellulaire causés par la densité élevée des antennes déployées dans les réseaux C-RANs. Ainsi, nous proposons une formulation mathématique exacte basée sur les méthodes Branch-and-Cut qui consiste à consolider et ré-optimiser les rayons de couverture des antennes afin de minimiser les interférences inter-cellulaires et de garantir une couverture maximale du réseau conjointement. En plus de l’augmentation des niveaux d’interférence, la densité élevée des cellules dans le réseau CRAN augmente le nombre des fonctions BBUs ainsi que le trafic de données entre les antennes et les centres de données centralisés avec de fortes exigences en termes de latence sur le réseau fronthaul. Par conséquent, nous discutons dans la troisième partie de cette thèse comment placer d’une manière optimale les fonctions BBUs en considérant la solution split du 3GPP afin de trouver le meilleur compromis entre les avantages de la centralisation dans C-RAN et les forts besoins en latence et bande passante sur le réseau fronthaul. Nous proposons des algorithmes (exacts et heuristiques) issus de l’optimisation combinatoire afin de trouver rapidement des solutions optimales ou proches de l’optimum, même pour des instances larges du problèmes
Cloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes

3

Di, Cicco Nicola. "Scalable Algorithms for Cloud Radio Access Network (C-RAN) Optimization". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23755/.

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In the evolving scenario of 5G networks, resource allocation algorithms for the Cloud Radio Access Network (C-RAN) model have proven to be the key for managing ever increasing Capital Expenditure (CAPEX) and Operating Expenditure (OPEX) for mobile networks while ensuring high Quality of Service (QoS). In Chapter 1 a brief overview of the main elements of the C-RAN and of the methodologies that are employed in this work is provided. In Chapter 2, an exact scalable methodology for a static traffic scenario, based on lexicographic optimization, is proposed for the solution of a multi-objective optimization problem to achieve, among other goals, the minimization of the number of active nodes in the C-RAN while supporting reliability and meeting latency constraints. The optimal solution of the most relevant objectives for networks of several tens of nodes is obtained in few tens of seconds of computational time in the worst case. For the least relevant objective a heuristic is developed, providing near optimal solutions in few seconds of computing time. In Chapter 3, an optimization framework for dynamic C-RAN reconfiguration is developed. The objective is to maintain C-RAN cost optimization, while minimizing the cost of virtual network function migration. Significant savings in terms of migrations (above 82% for primary virtual BBU functions and above 75% for backup virtual BBU functions) can be obtained with respect to a static traffic scenario, with execution time of the optimization algorithm below 20 seconds in the worst cases, making its application feasible for dynamic scenarios. In Chapter 4, an alternative Column Generation model formulation is developed, and the quality of the computed lower bounds is evaluated. Further extensions from this baseline (e.g. Column Generation based heuristics, exact Branch&Price algorithms) are left as future work. In Chapter 5, the main results achieved in this work are summarized, and several possible extensions are proposed.

4

Thainesh, Joseph S. "Radio access network (RAN) signalling architecture for dense mobile network". Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/811126/.

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Small cells are becoming a promising solution for providing enhanced coverage and increasing system capacity in a large-scale small cell network. In such a network, the large number of small cells may cause mobility signalling overload on the core network (CN) due to frequent handovers, which impact the users Quality of Experience (QoE). This is one of the major challenges in dense small cell networks. Such a challenge has been considered, this thesis addresses this challenging task to design an effective signalling architecture in dense small cell networks. First, in order to reduce the signalling overhead incurred by path switching operations in the small cell network, a new mobility control function, termed the Small Cell Controller (SCC) is introduced to the existing base station (BS) on the Radio-Access-Network(RAN)-side. Based on the signalling architecture, a clustering optimisation algorithm is proposed in order to select the optimal SCC in a highly user density environment. Specifically, this algorithm is designed to select multiple optimal SCCs due to the growth in number of small cells in the large-scale environment. Finally, a scalable architecture for handling the control plane failures in heterogeneous networks is proposed. In that architecture, the proposed SCC scheme controls and manages the affected small cells in a clustered fashion during the macro cell fail-over period. Particularly, the proposed SCC scheme can be flexibly configured into a hybrid scenario. For operational reduction (reducing a number of direct S1 connections to the CN), better scalability (reducing a number of S1 bearers on the CN) and reduction of signalling load on the CN, the proposed radio access network (RAN) signalling architecture is a viable and preferable option for dense small cell networks. Besides, the proposed signalling architecture is evaluated through realistic simulation studies.

5

Duan, Jialong. "Coordination inside centralized radio access networks with limited fronthaul capacity". Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0052/document.

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Le réseau d'accès radio centralisé (C-RAN) peut fortement augmenter la capacité des réseaux mobiles. Cependant, la faisabilité de C-RAN est limitée par le débit considérable engendré sur les liaisons de transport, appelées également fronthaul. L'objectif de cette thèse est d'améliorer les performances de C-RAN tout en considérant les limitations du débit sur le frontaul, l'allocation de ressources et l'ordonnancement des utilisateurs.Nous étudions d'abord les séparations fonctionnelles possibles entre les têtes radios distantes (RRH) et les unités de traitement en bande de base (BBU) sur la liaison montante pour réduire le débit de transmission sur le fronthaul : certaines fonctions de couche basse sont déplacées du BBU vers les RRH. Nous fournissons une analyse quantitative des améliorations de performances ainsi obtenues.Nous nous concentrons ensuite sur la transmission coordonnée Multi-point (CoMP) sur le lien descendant. CoMP peut améliorer l'efficacité spectrale mais nécessite une coordination inter-cellule, ce qui est possible uniquement si une capacité fronthaul élevée est disponible. Nous comparons des stratégies de transmission avec et sans coordination inter-cellule. Les résultats de simulation montrent que CoMP doit être préféré pour les utilisateurs situés en bordure de cellule et lorsque la capacité du fronthaul est élevée. Nous en déduisons une stratégie hybride pour laquelle Les utilisateurs sont divisés en deux sous-ensembles en fonction de la puissance du signal. Les utilisateurs situés dans les zones centrales sont servis par un seul RRH avec une coordination simple et ceux en bordure de cellule sont servis en mode CoMP. Cette stratégie hybride constitue un bon compromis entre les débits offerts aux utilisateurs et les débits sur le fronthaul
Centralized/Cloud Radio Access Network (C-RAN) is a promising mobile network architecture, which can potentially increase the capacity of mobile networks while reducing operators¿ cost and energy consumption. However, the feasibility of C-RAN is limited by the large bit rate requirement in the fronthaul. The objective of this thesis is to improve C-RAN performance while considering fronthaul throughput reduction, fronthaul capacity allocation and users scheduling.We first investigate new functional split architectures between Remote Radio Heads (RRHs) and Baseband Units (BBU) on the uplink to reduce the transmission throughput in fronthaul. Some low layer functions are moved from the BBU to RRHs and a quantitative analysis is provided to illustrate the performance gains. We then focus on Coordinated Multi-point (CoMP) transmissions on the downlink. CoMP can improve spectral efficiency but needs tight coordination between different cells, which is facilitated by C-RAN only if high fronthaul capacity is available. We compare different transmission strategies without and with multi-cell coordination. Simulation results show that CoMP should be preferred for users located in cell edge areas and when fronthaul capacity is high. We propose a hybrid transmission strategy where users are divided into two parts based on statistical Channel State Informations (CSIs). The users located in cell center areas are served by one transmission point with simple coordinated scheduling and those located in cell edge areas are served with CoMP joint transmission. This proposed hybrid transmission strategy offers a good trade-off between users¿ transmission rates and fronthaul capacity cost

6

Sharara, Mahdi. "Resource Allocation in Future Radio Access Networks". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG024.

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Cette thèse considère l'allocation des ressources radio et de calcul dans les futurs réseaux d'accès radio et plus précisément dans les réseaux Cloud-RAN (Cloud-Radio Access Networks) ainsi que les réseaux Open-RAN (Open-Radio Access Networks). Dans ces architectures, le traitement en bande de base de plusieurs stations de base est centralisé et virtualisé. Cela permet une meilleure optimisation du réseau et une réduction des dépenses d'investissement et d'exploitation. Dans la première partie de cette thèse, nous considérons un schéma de coordination entre les ordonnanceurs radio et de calcul. Dans le cas où les ressources de calcul ne sont pas suffisantes, l'ordonnanceur de calcul envoie un retour d'information à l'ordonnanceur radio pour mettre à jour les paramètres radio. Bien que cela réduise le débit radio de l'utilisateur, il garantit que la trame sera traitée au niveau de l'ordonnanceur de calcul. Nous modélisons ce schéma de coordination à l'aide de la programmation linéaire en nombres entiers (ILP) avec comme objectifs de maximiser le débit total ainsi que la satisfaction des utilisateurs. Les résultats montrent la capacité de ce schéma de coordination à améliorer différents paramètres, notamment la réduction du gaspillage de puissance de transmission. Ensuite, nous proposons des heuristiques à faible complexité et nous les testons dans un environnement de services multiples avec des exigences différentes. Dans la deuxième partie de cette thèse, nous considérons l'allocation conjointe des ressources radio et de calcul. Les ressources radio et de calcul sont allouées conjointement dans le but de minimiser la consommation énergétique. Le problème est modélisé à l'aide de la programmation linéaire mixte en nombres entiers (MILP), et est ensuite comparé à un autre problème MILP ayant comme objectif de maximiser le débit total. Les résultats montrent que l'allocation conjointe des ressources radio et de calcul est plus efficace que l'allocation séquentielle pour minimiser la consommation énergétique. Enfin, nous proposons un algorithme basé sur la théorie de matching (matching theory) à faible complexité qui pourra être une alternative pour résoudre le problème MILP à haute complexité. Dans la dernière partie de cette thèse, nous étudions l'utilisation des outils de l'apprentissage machine (machine learning). Tout d'abord, nous considérons un modèle d'apprentissage profond (deep learning) qui vise à apprendre comment résoudre le problème de coordination ILP, mais en un temps beaucoup plus court. Ensuite, nous considérons un modèle d'apprentissage par renforcement (reinforcement learning) qui vise à allouer des ressources de calcul aux utilisateurs afin de maximiser le profit de l'opérateur
This dissertation considers radio and computing resource allocation in future radio access networks and more precisely Cloud Radio Access Network (Cloud-RAN) and Open Radio Access Network (Open-RAN). In these architectures, the baseband processing of multiple base stations is centralized and virtualized. This permits better network optimization and allows for saving capital expenditure and operational expenditure. In the first part, we consider a coordination scheme between radio and computing schedulers. In case the computing resources are not sufficient, the computing scheduler sends feedback to the radio scheduler to update the radio parameters. While this reduces the radio throughput of the user, it guarantees that the frame will be processed at the computing scheduler level. We model this coordination scheme using Integer Linear Programming (ILP) with the objectives of maximizing the total throughput and users' satisfaction. The results demonstrate the ability of this scheme to improve different parameters, including the reduction of wasted transmission power. Then, we propose low-complexity heuristics, and we test them in an environment of multiple services with different requirements. In the second part, we consider the joint radio and computing resource allocation. Radio and computing resources are jointly allocated with the aim of minimizing energy consumption. The problem is modeled as a Mixed Integer Linear Programming Problem (MILP) and is compared to another MILP problem that maximizes the total throughput. The results demonstrate the ability of joint allocation to minimize energy consumption in comparison with the sequential allocation. Finally, we propose a low-complexity matching game-based algorithm that can be an alternative for solving the high-complexity MILP problem. In the last part, we investigate the usage of machine learning tools. First, we consider a deep learning model that aims to learn how to solve the coordination ILP problem, but with a much shorter time. Then, we consider a reinforcement learning model that aims to allocate computing resources for users to maximize the operator's profit

7

Rabia, Tarek. "Virtualisation des fonctions d'un Cloud Radio Access Network(C-RAN)". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS009/document.

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La nouvelle génération de réseaux mobiles (5G) devrait faire face, durant les cinq prochaines années, à une importante croissance du volume de données, échangé entre plusieurs milliards d'objets et d'applications connectés. En outre, l'émergence de nouvelles technologies, telles que Internet of Things (IoT), conduite autonome et réalité augmentée, impose de plus fortes contraintes de performance et de qualité de service (QoS). Répondre aux besoins cités, tout en réduisant les dépenses d'investissement et d'exploitation (CAPEX/OPEX), sont les objectifs poursuivis par les opérateurs télécom, qui ont défini une nouvelle architecture d'accès radio, appelée Cloud Radio Access Network (C-RAN). Le principe du C-RAN est de centraliser, au sein d'un pool, les parties de traitement, BaseBand Unit (BBU), d'un RAN traditionnel. Les BBU sont alors dissociées de la station de base et de la partie radio, Remote Radio Unit (RRU). Ces deux parties restent néanmoins connectées à travers un réseau intermédiaire appelé Fronthaul (FH). Dans cette thèse, nous allons concevoir une nouvelle architecture C-RAN partiellement centralisée qui intègrera une plateforme de virtualisation basée sur un environnement Xen, nommée " Metamorphic Network " (MNet). A travers cette architecture, nous viserons à : i) mettre en place un pool, dans lequel des ressources physiques (processeurs, mémoire, ports réseaux, etc.) seront partagées entre des BBU virtualisées et d'autres applications, ii) établir un réseau FH ouvert aux fournisseurs de services et aux tierces parties, facilitant ainsi le déploiement des services au plus près des utilisateurs, pour une meilleure qualité d'expérience, iii) exploiter, à travers le FH, les infrastructures Ethernet existantes pour réduire les CAPEX/OPEX et enfin, iv) atteindre les performances réseau préconisées pour la 5G. Dans la première contribution, nous allons définir une nouvelle architecture Xen pour la plateforme MNet, intégrant le framework de packet processing, OpenDataPlane (ODP), au sein d’un domaine Xen privilégié, nommé « Driver Domain ». Notre objectif, à travers cette architecture, est d’accélérer le traitement des paquets de données transitant par MNet, en évitant la surutilisation, par ODP, des cœurs du processeur physique (CPU) de la plateforme. Pour cela, des cœurs CPU virtuels (vCPU) seront alloués dans le Driver Domain pour être exploités durant le traitement des paquets par ODP. Cette nouvelle plateforme MNet servira de base pour notre architecture C-RAN. Dans la seconde contribution, nous allons implémenter, au sein du FH, deux solutions réseau. La première solution, consistera à déployer le réseau de couche 2, Transparent Interconnection of Lots of Links (TRILL), pour connecter les différents éléments de notre architecture C-RAN. La seconde solution, consistera à déployer un réseau Software Defined Network (SDN), géré par le contrôleur distribué ONOS, qui sera virtualisé dans le pool BBU. Une comparaison des performances réseau sera réalisée entre ces deux solutions
Over the next five years, the new generation of mobile networks (5G) would face a significant growth of the data volume, exchanged between billions of connected objects and applications. Furthermore, the emergence of new technologies, such as Internet of Things (IoT), autonomous driving and augmented reality, imposes higher performance and quality of service (QoS) requirements. Meeting these requirements, while reducing the Capital and Operation Expenditures (CAPEX/OPEX), are the pursued goals of the mobile operators. Consequently, Telcos define a new radio access architecture, called Cloud Radio Access Network (C-RAN). The C-RAN principle is to centralize, within a pool, the processing unit of a radio interface, named BaseBand Unit (BBU). These two units are interconnected through a Fronthaul (FH) network. In this thesis, we design a new partially centralized C-RAN architecture that integrates a virtualization platform, based on a Xen environment, called Metamorphic Network (MNet). Through this architecture, we aim to: i) implement a pool in which physical resources (processors, memory, network ports, etc.) are shared between virtualized BBUs and other applications; ii) establish an open FH network that can be used by multiple operators, service providers and third parties to deploy their services and Apps closer to the users for a better Quality of Experience (QoE); iii) exploit, through the FH, the existing Ethernet infrastructures to reduce CAPEX/OPEX; and finally iv) provide the recommended network performance for the 5G. In the first contribution, we define a new Xen architecture for the MNet platform integrating the packet-processing framework, OpenDataPlane (ODP), within a privileged Xen domain, called Driver Domain (DD). This new architecture accelerates the data packet processing within MNet, while avoiding the physical CPUs overuse by ODP. Thus, virtual CPU cores (vCPU) are allocated within DD and are used by ODP to accelerate the packet processing. This new Xen architecture improves the MNet platform by 15%. In the second contribution, we implement two network solutions within the FH. The first solution consist of deploying a layer 2 network protocol, Transparent Interconnection of Lots of Links (TRILL), to connect multiple elements of our C-RAN architecture. The second solution consists of implementing a Software Defined Network (SDN) model managed by Open Network Operating System (ONOS), a distributed SDN controller that is which is virtualized within BBU pool. Moreover, a network performance comparison is performed between these two solutions

8

Rabia, Tarek. "Virtualisation des fonctions d'un Cloud Radio Access Network(C-RAN)". Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS009.pdf.

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Abstract (sommario):

La nouvelle génération de réseaux mobiles (5G) devrait faire face, durant les cinq prochaines années, à une importante croissance du volume de données, échangé entre plusieurs milliards d'objets et d'applications connectés. En outre, l'émergence de nouvelles technologies, telles que Internet of Things (IoT), conduite autonome et réalité augmentée, impose de plus fortes contraintes de performance et de qualité de service (QoS). Répondre aux besoins cités, tout en réduisant les dépenses d'investissement et d'exploitation (CAPEX/OPEX), sont les objectifs poursuivis par les opérateurs télécom, qui ont défini une nouvelle architecture d'accès radio, appelée Cloud Radio Access Network (C-RAN). Le principe du C-RAN est de centraliser, au sein d'un pool, les parties de traitement, BaseBand Unit (BBU), d'un RAN traditionnel. Les BBU sont alors dissociées de la station de base et de la partie radio, Remote Radio Unit (RRU). Ces deux parties restent néanmoins connectées à travers un réseau intermédiaire appelé Fronthaul (FH). Dans cette thèse, nous allons concevoir une nouvelle architecture C-RAN partiellement centralisée qui intègrera une plateforme de virtualisation basée sur un environnement Xen, nommée " Metamorphic Network " (MNet). A travers cette architecture, nous viserons à : i) mettre en place un pool, dans lequel des ressources physiques (processeurs, mémoire, ports réseaux, etc.) seront partagées entre des BBU virtualisées et d'autres applications, ii) établir un réseau FH ouvert aux fournisseurs de services et aux tierces parties, facilitant ainsi le déploiement des services au plus près des utilisateurs, pour une meilleure qualité d'expérience, iii) exploiter, à travers le FH, les infrastructures Ethernet existantes pour réduire les CAPEX/OPEX et enfin, iv) atteindre les performances réseau préconisées pour la 5G. Dans la première contribution, nous allons définir une nouvelle architecture Xen pour la plateforme MNet, intégrant le framework de packet processing, OpenDataPlane (ODP), au sein d’un domaine Xen privilégié, nommé « Driver Domain ». Notre objectif, à travers cette architecture, est d’accélérer le traitement des paquets de données transitant par MNet, en évitant la surutilisation, par ODP, des cœurs du processeur physique (CPU) de la plateforme. Pour cela, des cœurs CPU virtuels (vCPU) seront alloués dans le Driver Domain pour être exploités durant le traitement des paquets par ODP. Cette nouvelle plateforme MNet servira de base pour notre architecture C-RAN. Dans la seconde contribution, nous allons implémenter, au sein du FH, deux solutions réseau. La première solution, consistera à déployer le réseau de couche 2, Transparent Interconnection of Lots of Links (TRILL), pour connecter les différents éléments de notre architecture C-RAN. La seconde solution, consistera à déployer un réseau Software Defined Network (SDN), géré par le contrôleur distribué ONOS, qui sera virtualisé dans le pool BBU. Une comparaison des performances réseau sera réalisée entre ces deux solutions
Over the next five years, the new generation of mobile networks (5G) would face a significant growth of the data volume, exchanged between billions of connected objects and applications. Furthermore, the emergence of new technologies, such as Internet of Things (IoT), autonomous driving and augmented reality, imposes higher performance and quality of service (QoS) requirements. Meeting these requirements, while reducing the Capital and Operation Expenditures (CAPEX/OPEX), are the pursued goals of the mobile operators. Consequently, Telcos define a new radio access architecture, called Cloud Radio Access Network (C-RAN). The C-RAN principle is to centralize, within a pool, the processing unit of a radio interface, named BaseBand Unit (BBU). These two units are interconnected through a Fronthaul (FH) network. In this thesis, we design a new partially centralized C-RAN architecture that integrates a virtualization platform, based on a Xen environment, called Metamorphic Network (MNet). Through this architecture, we aim to: i) implement a pool in which physical resources (processors, memory, network ports, etc.) are shared between virtualized BBUs and other applications; ii) establish an open FH network that can be used by multiple operators, service providers and third parties to deploy their services and Apps closer to the users for a better Quality of Experience (QoE); iii) exploit, through the FH, the existing Ethernet infrastructures to reduce CAPEX/OPEX; and finally iv) provide the recommended network performance for the 5G. In the first contribution, we define a new Xen architecture for the MNet platform integrating the packet-processing framework, OpenDataPlane (ODP), within a privileged Xen domain, called Driver Domain (DD). This new architecture accelerates the data packet processing within MNet, while avoiding the physical CPUs overuse by ODP. Thus, virtual CPU cores (vCPU) are allocated within DD and are used by ODP to accelerate the packet processing. This new Xen architecture improves the MNet platform by 15%. In the second contribution, we implement two network solutions within the FH. The first solution consist of deploying a layer 2 network protocol, Transparent Interconnection of Lots of Links (TRILL), to connect multiple elements of our C-RAN architecture. The second solution consists of implementing a Software Defined Network (SDN) model managed by Open Network Operating System (ONOS), a distributed SDN controller that is which is virtualized within BBU pool. Moreover, a network performance comparison is performed between these two solutions

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Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms". Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043.

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Cloud-Radio Access Network (C-RAN) est une architecture prometteuse pour faire face à l’augmentation exponentielle des demandes de trafic de données et surmonter les défis des réseaux de prochaine génération (5G). Le principe de base de CRAN consiste à diviser la station de base traditionnelle en deux entités : les unités de bande de base (BaseBand Unit, BBU) et les têtes radio distantes (Remote Radio Head, RRH) et à mettre en commun les BBUs de plusieurs stations dans des centres de données centralisés (pools de BBU). Ceci permet la réduction des coûts d’exploitation, l’amélioration de la capacité du réseau ainsi que des gains en termes d’utilisation des ressources. Pour atteindre ces objectifs, les opérateurs réseaux ont besoin d’investiguer de nouveaux algorithmes pour les problèmes d’allocation de ressources permettant ainsi de faciliter le déploiement de l’architecture C-RAN. La plupart de ces problèmes sont très complexes et donc très difficiles à résoudre. Par conséquent, nous utilisons l’optimisation combinatoire qui propose des outils puissants pour adresser ce type des problèmes.Un des principaux enjeux pour permettre le déploiement du C-RAN est de déterminer une affectation optimale des RRHs (antennes) aux centres de données centralisés (BBUs) en optimisant conjointement la latence sur le réseau de transmission fronthaul et la consommation des ressources. Nous modélisons ce problème à l’aide d’une formulation mathématique basée sur une approche de programmation linéaire en nombres entiers permettant de déterminer les stratégies optimales pour le problème d’affectation des ressources entre RRH-BBU et nous proposons également des heuristiques afin de pallier la difficulté au sens de la complexité algorithmique quand des instances larges du problème sont traitées, permettant ainsi le passage à l’échelle. Une affectation optimale des antennes aux BBUs réduit la latence de communication attendue et offre des gains en termes d’utilisation des ressources. Néanmoins, ces gains dépendent fortement de l’augmentation des niveaux d’interférence inter-cellulaire causés par la densité élevée des antennes déployées dans les réseaux C-RANs. Ainsi, nous proposons une formulation mathématique exacte basée sur les méthodes Branch-and-Cut qui consiste à consolider et ré-optimiser les rayons de couverture des antennes afin de minimiser les interférences inter-cellulaires et de garantir une couverture maximale du réseau conjointement. En plus de l’augmentation des niveaux d’interférence, la densité élevée des cellules dans le réseau CRAN augmente le nombre des fonctions BBUs ainsi que le trafic de données entre les antennes et les centres de données centralisés avec de fortes exigences en termes de latence sur le réseau fronthaul. Par conséquent, nous discutons dans la troisième partie de cette thèse comment placer d’une manière optimale les fonctions BBUs en considérant la solution split du 3GPP afin de trouver le meilleur compromis entre les avantages de la centralisation dans C-RAN et les forts besoins en latence et bande passante sur le réseau fronthaul. Nous proposons des algorithmes (exacts et heuristiques) issus de l’optimisation combinatoire afin de trouver rapidement des solutions optimales ou proches de l’optimum, même pour des instances larges du problèmes
Cloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes

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Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.

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La densification de réseau à l'aide de petites cellules massivement déployées sur les zones macro-cellules, représente une solution prometteuse pour les réseaux mobiles 5G avenir pour faire face à l'augmentation du trafic mobile. Afin de simplifier la gestion de l'hétérogène du réseau d'accès radio (Radio Access Network RAN) qui résulte du déploiement massif de petites cellules, des recherches récentes et des études industrielles ont favorisé la conception de nouvelles architectures de RAN centralisés appelés comme Cloud-RAN (C-RAN), ou RAN virtuel (V-RAN), en incorporant les avantages du cloud computing et Network Functions Virtualization (NFV). Le projet de DynaRoC vise l'élaboration d'un cadre théorique de l'orchestration de ressources pour les C-RAN et dériver les limites de performance fondamentaux ainsi que les arbitrages entre les différents paramètres du système, et la conception de mécanismes d'orchestration de ressources dynamiques sur la base des conclusions théoriques à atteindre un équilibre de performance souhaité, en tenant compte des différents défis de conception. Le doctorant va étudier les mécanismes d'optimisation des ressources novatrices pour favoriser le déploiement de C-RAN, améliorer leur performance exploitant la technologie Network Functions Virtualization
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology

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Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network". Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066549/document.

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Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RAN
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost

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Chang, Chia-Yu. "Cloudiﬁcation and Slicing in 5G Radio Access Network". Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS293.pdf.

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Au cours des dernières décennies, la croissance des statistiques d’utilisation de réseau exige une technologique évolutive. Une question naturelle surgit dans nos esprits: que sera la 5G? Pour répondre à cette question, l’architecture 5G doit être conçue avec un certain niveau de flexibilité via l’intégration des principes de softwarization et virtualisation. Le réseau peut être utilisé de manière efficace et indépendante via la création de plusieurs espaces séparées logiquement, appelés tranches de réseau. De plus, chaque réseau logique peut déployer ses fonctions de réseau dans un environnement de nuage avec la flexibilité d’exécution. À cette fin, l’objectif de cette thèse est d’étudier ces deux techniques: (a) C-RAN et (b) découpage de RAN. Dans la première partie, nous étudions C-RAN, dans lequel les stations de base monolithiques sont remplacées par (1) les éléments radio distribués et (2) les pools centralisés pour des unités de traitement en bande de base. Le concept C-RAN est toujours confronté à des exigences sévères en matière de capacité et de latence de l’interface fronthaul qui connecte l’unité de radio distante distribuée à l’unité de traitement en bande de base centralisée. Dans la deuxième partie, nous nous concentrons sur le découpage RAN non seulement pour permettre des différents niveaux d’isolation et de partage à chaque tranche de réseau, mais également pour customiser le plan de contrôle, le plan utilisateur et la logique de contrôle de réseau virtualisé. Par conséquent, nous proposons un environnement d’exécution flexible pour le système de slicing, nommé «RAN Runtime» pour héberger les instances de service sur chacun des modules RAN sous-jacents
Over the past few decades, the continuing growth of network statistics requires a constantly evolving technology. Therefore, a natural question arises in our minds: what will 5G be? To answer this question, the 5G architecture must be designed with a certain level of flexibility through the integration of softwarization and virtualization principles. Therefore, we can see that 5G will provide a paradigm shift beyond radio access technology in order to establish an agile and sophisticated communication system. The network can be used efficiently and independently by creating multiple logically separated spaces, called network slices. In addition, each logical network can deploy its network functions in a flexible cloud environment. To this end, the goal of this thesis is to study these two techniques: (a) Cloud-RAN and (b) RAN splitting. In the first part, our focus is on the C-RAN concept, in which monolithic base stations are replaced by (1) distributed radio elements and (2) centralized pools for baseband processing units. The C-RAN notion is still confronted with stringent capacity and latency requirements of the fronthaul interface that connects the distributed remote radio unit to the centralized baseband processing unit. In the second part, we focus on RAN cutting not only to allow different levels of isolation and sharing at each slice of network, but also to customize the control plane, user plane and control logic. Therefore, we provide a flexible runtime environment for the "RAN Runtime" slicing system to host service instances on each of the underlying RAN modules

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Javel, Aymeric de. "5G RAN : implémentation de la couche physique et découpage du réseau". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT031.

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Une des évolutions de la 4G à la 5G est l'hétérogénéité des terminaux qui accèdent au réseau. Ces terminaux vont des smartphones aux véhicules connectés en passant par les capteurs pour l'agriculture. Étant donné que les contraintes et les exigences associées aux différents types de terminaux sont hétérogènes, il n'est pas facile de multiplexer les services qui leur sont associés sur une seule infrastructure physique. Le slicing est la technologie qui permet à l'infrastructure physique de fournir plusieurs réseaux logiques (appelés slices) pour servir les différents terminaux et services associés : cette thèse étudie le slicing et sa mise en œuvre au niveau RAN. Une des principales questions soulevées par le slicing est l'allocation des ressources. En effet, de nombreux modèles existent pour l'allocation des ressources du RAN mais il manque des modèles qui prennent en compte les nouvelles contraintes impliquées par le slicing. La première contribution de cette thèse est de définir un nouveau modèle pour le slicing au niveau RAN. Ce modèle prend en compte différentes contraintes de slicing telles que la capacité, la densité des UEs, la latence et la fiabilité. L'homologie simpliciale est utilisée pour valider le respect des contraintes des slices. De plus, ce modèle est appliqué à l'optimisation de la puissance, qui est un aspect critique du déploiement du réseau. Le deuxième défi abordé dans ce travail est la supervision et le contrôle du réseau. En effet, certains verticaux ont des exigences de contrôle très élevées, et le réseau lui-même pourrait ne pas être en mesure de satisfaire pleinement ces contraintes. Par conséquent, nous introduisons une sonde qui peut extraire des données du réseau pour alimenter des outils de supervision pour le contrôle et le suivi du réseau. Cette sonde est conçue pour être résiliente aux cyber-attaques et est donc indépendante du réseau. La dernière contribution principale de cette thèse est l'introduction d'une couche physique 5G open-source appelée free5GRAN. La couche physique fournit toutes les procédures et algorithmes minimaux pour les communications entre le gNodeB et les UEs. La structure du projet est construite de manière à pouvoir facilement la modifier et mettre en place de nouvelles fonctionnalités. De plus, l'architecture logicielle est conçue de manière à ce que la couche physique soit modulaire et puisse être dérivée pour mettre en œuvre le split 7.2 de l'open-RAN
A critical evolution from 4G to 5G is the heterogeneity of the terminals that connect the network. Those terminals range from smartphones to connected vehicles and sensors for agriculture. Given that the constraints and requirements associated with the different kinds of terminals are heterogeneous, it is not trivial to multiplex the services associated with them on top of a single physical infrastructure. Network slicing is the technology that enables the physical infrastructure to provide multiple logical networks (called network slices) to serve the various devices and associated services: this thesis studies network slicing and its implementation at the RAN level.One main issue raised by network slicing is resource allocation. Indeed, many models exist for resource allocation of the RAN but we are missing models which take into account new constraints implied by network slicing. The first contribution of this thesis is to define a new model for network slicing at the RAN level. This model takes into account diverse slices constraints such as capacity, UEs density, latency, and reliability. Simplicial homology is used to validate slices constraints fulfillment. Furthermore, this model is applied to power optimization, which is a critical aspect of network deployment. The second challenge addressed in this work is the network's supervision and control. Indeed, some verticals have ultra-high control requirements, and the network itself might not be able to satisfy this constraint fully. Therefore, we introduce a probe that can extract data from the network to feed supervision tools for the network's monitoring and control. This probe is designed to be resilient to cyber-attacks and is thus independent of the network.The last main contribution of this thesis is the introduction of an open-source 5G physical layer called free5GRAN. The physical layer provides all the minimal procedures and algorithms for communications between the gNodeB and UEs. The project's structure is built so one can easily modify it and implement new features. Furthermore, the software architecture is designed so that the physical layer is modular and can be derived to implement the open-RAN split 7.2

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Andrioli, Leandro. "Elastic-RAN: Um modelo de elasticidade multinível com grão adaptativo para Cloud Radio Access Network". Universidade do Vale do Rio dos Sinos, 2018. http://www.repositorio.jesuita.org.br/handle/UNISINOS/7427.

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Até o ano de 2020, espera-se que a área de cobertura das redes de celulares aumente em 10 vezes, com mais de 50 bilhões de dispositivos conectados, suportando 100 vezes mais equipamentos de usuários e elevando a capacidade da taxa de dados em 1000 vezes. Tal circunstância gerará um aumento massivo no tráfego de dados, fomentando o desenvolvimento da 5G e fazendo com que a indústria e as iniciativas científicas passem a voltar seus esforços para atender a essa demanda. Ganha força, então, as pesquisas relacionadas a Cloud Radio Access Networks (C-RANs), uma arquitetura que consolida as base stations (BSs) para um ponto centralizado na nuvem, mudando a ideia de atuar com recursos fixos e limitados, na medida em que se beneficia de uma das características chave da Computação em Nuvem: a elasticidade de recursos. Um dos grandes desafios na arquitetura C-RAN reside na complexidade em orquestrar todos esses recursos computacionais de forma que o processamento das requisições seja realizado com alto desempenho e com o menor custo de infraestrutura possível. Diante de todo esse contexto, a presente dissertação busca desenvolver o modelo Elastic-RAN, propondo um conceito de elasticidade multinível não bloqueante, com orquestração automática de recursos através da coordenação de BBU Pools e seus BBUs, junto a um mecanismo de grão elástico adaptativo. A elasticidade multinível não bloqueante permite controlar o nível de BBU Pool (máquina física), haja vista o alto volume de tráfego e a distância máxima sugerida entre as antenas e os pools, e o nível de BBU (máquina virtual), em razão do alto processamento de CPU e memória necessária para as requisições, de modo a não penalizar os processamentos correntes. O mecanismo de grão elástico adaptativo permite provisionar e mapear os recursos sob demanda e em tempo de execução, considerando o uso corrente dos recursos, para que cada ação elástica seja executada com um grão próximo das necessidades correntes de processamento. O modelo Elastic-RAN foi avaliado por intermédio de experimentos que simularam diferentes perfis de cargas, os quais são executados em uma aplicação intensiva de CPU e de tráfego na rede, explorando a transferência de streamings e processando decodificação de blocos. Como resultados, foi possível constatar que o Elastic-RAN pode atingir ganhos que vão de 4% a 26%, em relação aos custos de execução, quando comparado à abordagem de elasticidade tradicional. Além disso, obteve melhor eficiência para todos os perfis de carga e reduziu em até 55% a quantidade de operações elásticas necessárias. Outrossim, frente a abordagem sem elasticidade, os ganhos de custos foram ainda superiores, ficando entre 51% e 70%.
It is expected that, by 2020, cell phone networks will have been increased 10 times their coverage area, with more than 50 billion connected devices, supporting 100 times more user equipment and increasing data rate capacity by 1000 times. This will lead to a massive increase in data traffic, fostering the development of 5G and making industry and scientific initiatives turn their efforts to meet this demand. In this scenario, Cloud Radio Access Networks (C-RANs) based researches, an architecture that consolidates base stations (BSs) to a cloud-centric point, are gaining momentum, changing the idea of fixed and limited resources, as it benefits from one of the key features of Cloud Computing: resource elasticity. One of the major challenges in C-RAN architecture lies in the high complexity of orchestrating all of these computational resources in order to perform the requests processing with high performance and the lowest possible infrastructure cost. Considering this context, the present dissertation seeks to develop the Elastic-RAN model, proposing a multilevel non-blocking elasticity concept, with automatic orchestration of resources through the coordination of BBU Pools and their BBUs, with an adaptive elastic grain mechanism. The multilevel non-blocking elasticity allows it control the level of BBU Pool (physical machine), given the high volume of traffic and the suggested maximum distance between antennas and pools, and the level of BBU (virtual machine), due to the high CPU processing and memory required for the requests, so as not to penalize the current processing. The adaptive elastic grain mechanism allows the provisioning and mapping of resources on demand and at runtime, considering the current use of resources, so that each elastic action is performed with a grain close to the current processing needs. The Elastic-RAN model was evaluated through experiments that simulated different load profiles, which are executed in an intensive CPU and network traffic application, exploiting the transfer of streamings and processing block decoding. As a result, it was possible to observe that Elastic-RAN may achieve gains ranging from 4 % to 26 %, in relation to execution costs, when compared to the traditional elasticity approach. In addition, it achieved better efficiency for all load profiles and reduced by 55 % the amount of elastic operations required. Also, given the non-elasticity approach, cost gains were even higher, going from 51 % to 70 %.

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Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks". Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.

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La densification de réseau à l'aide de petites cellules massivement déployées sur les zones macro-cellules, représente une solution prometteuse pour les réseaux mobiles 5G avenir pour faire face à l'augmentation du trafic mobile. Afin de simplifier la gestion de l'hétérogène du réseau d'accès radio (Radio Access Network RAN) qui résulte du déploiement massif de petites cellules, des recherches récentes et des études industrielles ont favorisé la conception de nouvelles architectures de RAN centralisés appelés comme Cloud-RAN (C-RAN), ou RAN virtuel (V-RAN), en incorporant les avantages du cloud computing et Network Functions Virtualization (NFV). Le projet de DynaRoC vise l'élaboration d'un cadre théorique de l'orchestration de ressources pour les C-RAN et dériver les limites de performance fondamentaux ainsi que les arbitrages entre les différents paramètres du système, et la conception de mécanismes d'orchestration de ressources dynamiques sur la base des conclusions théoriques à atteindre un équilibre de performance souhaité, en tenant compte des différents défis de conception. Le doctorant va étudier les mécanismes d'optimisation des ressources novatrices pour favoriser le déploiement de C-RAN, améliorer leur performance exploitant la technologie Network Functions Virtualization
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology

16

Khan, Muhammad. "A self-optimised cloud radio access network for emerging 5G architectures". Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/16050.

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Network densification has become a dominant theme for capacity enhancement in cellular networks. However, it increases the operational complexity and expenditure for mobile network operators. Consequently, the essential features of Self-Organising Networks (SON) are considered to ensure the economic viability of the emerging cellular networks. This thesis focuses on quantifying the benefits of self-organisation in Cloud Radio Access Network (C-RAN) by proposing a flexible, energy efficient, and capacity optimised system. The Base Band Unit (BBU) and Remote Radio Head (RRH) map is formulated as an optimisation problem. A self-optimised C-RAN (SOCRAN) is proposed which hosts Genetic Algorithm (GA) and Discrete-Particle-Swarm-Optimisation algorithm (DPSO), developed for optimisation. Computational results based on different network scenarios demonstrate that DPSO delivers excellent performances for the key performance indicators compared to GA. The percentage of blocked users is reduced from 10.523% to 0.409% in a medium sized network scenario and 5.394% to 0.56% in a vast network scenario. Furthermore, an efficient resource utilisation scheme is proposed based on the concept of Cell Differentiation and Integration (CDI). The two-stage CDI scheme semi-statically scales the number of BBUs and RRHs to serve an offered load and dynamically defines the optimum BBU-RRH mapping to avoid unbalanced network scenarios. Computational results demonstrate significant throughput improvement in a CDI-enabled C-RAN compared to a fixed C-RAN, i.e., an average throughput increase of 45.53% and an average blocked users decrease of 23.149% is experienced. A power model is proposed to estimate the overall power consumption of C-RAN. Approximately 16% power reduction is calculated in a CDI-enabled C-RAN when compared to a fixed C-RAN, both serving the same geographical area. Moreover, a Divide-and-Sort load balancing scheme is proposed and compared to the SOCRAN scheme. Results show excellent performances by the Divide-and-Sort algorithm in small networks when compared to SOCRAN and K-mean clustering algorithm.

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Costa, Felipe Rabuske. "Nuoxus - um modelo de caching proativo de conteúdo multimídia para Fog Radio Access Networks (F-RANs)". Universidade do Vale do Rio dos Sinos, 2018. http://www.repositorio.jesuita.org.br/handle/UNISINOS/7053.

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Estima-se que até o ano de 2020, cerca de 50 bilhões de dispositivos móveis estarão conectados a redes sem fio e que 78% de todo o tráfego de dados gerado por esse tipo de dispositivos será conteúdo multimídia. Essas estimativas fomentam o desenvolvimento da quinta geração de redes móveis (5G). Uma das arquiteturas mais recentemente proposta, chamada de Fog Radio Access Networks (F-RAN), dá aos componentes localizados na borda da rede poder de processamento e armazenamento endereçados às atividades da rede. Um dos principais problemas dessa arquitetura é o intenso tráfego de dados no seu canal de comunicação centralizado chamado fronthaul, utilizado para conectar as antenas (F-APs) à rede externa. Dado esse contexto, esse trabalho apresenta o Nuoxus, um modelo de caching de conteúdo multimídia voltado para F-RANs que visa amenizar esse problema. Ao armazenar esse tipo de conteúdo nos nós de rede mais próximos ao usuário, o número de acessos concorrentes ao fronthaul é reduzido, sendo esse um dos fatores agravantes na latência de comunicação na rede. O Nuoxus pode ser executado em qualquer nó da rede que possua capacidade de armazenamento e processamento, ficando responsável por gerenciar o caching de conteúdo desse nó. Sua política de substituição de conteúdo utiliza a similaridade de requisições entre os nós filhos e o restante da rede como um fator para definir a relevância de armazenar o conteúdo requisitado em cache. Além disso, utilizando esse mesmo processo, o Nuoxus sugere, de forma proativa, aos demais nós filhos que apresentam um alto grau de similaridade que façam o caching desse conteúdo, visando um possível futuro acesso. A análise do estado da arte demonstra que até o momento não existe nenhum outro trabalho que explore o histórico de requisições para fazer caching de conteúdo em arquiteturas multicamadas para redes sem fio de forma proativa e sem utilizar algum componente centralizado para fazer coordenação e predição de caching. A fim de comprovar a eficiência do modelo, foi desenvolvido um protótipo utilizando o simulador ns-3. Os resultados obtidos demostram que a utilização do Nuoxus foi capaz de reduzir a latência de rede em cerca de 29.75%. Além disso, quando comparado com outras estratégias de caching, o número de acesso à cache dos componentes de rede aumentou em 53.16% em relação à estratégia que obteve o segundo melhor resultado.
It is estimated that by the year 2020, about 50 billion mobile devices will be connected to wireless networks and 78% of the data traffic of this kind of device will be multimedia content. These estimates foster the development of the 5th generation of mobile networks (5G). One of the most recently proposed architectures, named Fog Radio Access Networks or F-RAN, gives the components located at the edge of the network the processing power and storage capacity to address network activities. One of the main problems of this architecture is the intense data traffic in its centralized component named fronthaul, which is used to connect the antennas (FAPs) to the external network. Given this context, we propose Nuoxus, a multimedia content caching model for F-RANs that aims to mitigate this problem. By storing the content in the nodes closest to the user, the number of concurrent accesses to the fronthaul is reduced, which decreases the communication latency of the network. Nuoxus can run on any network node that has storage and processing capacity, becoming the responsible for managing the cache of that node. Its content replacement policy uses the similarity of requests between the child nodes and the rest of the network as a factor to decide the relevance of storing the requested content in the cache. Furthermore, by using this same process, Nuoxus proactively suggests to the child nodes whose degree of similarity is high to perform the caching of the content, assuming they will access the content at a future time. The State-of-the-art analysis shows that there is no other work that explores the history of requests to cache content in multi-layer architectures for wireless networks in a proactive manner, without using some centralized component to do coordination and prediction of caching. To demonstrate the efficiency of the model, a prototype was developed using the ns 3 simulator. The results obtained demonstrate that the use of Nuoxus reduced network latency in 29.75%. In addition, when compared to other caching strategies, the cache hit increased by 53.16% when compared to the strategy that obtained the second-best result.

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Shinde, Swapnil Sadashiv. "Radio Access Network Function Placement Algorithms in an Edge Computing Enabled C-RAN with Heterogeneous Slices Demands". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20063/.

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Network slicing provides a scalable and flexible solution for resource allocation with performance guaranty and isolation from other services in the 5G architecture. 5G has to handle several active use cases with different requirements. The single solution to satisfy all the extreme requirements requires overspecifies and high-cost network architecture. Further, to fulfill the diverse requirements, each service will require different resources from a radio access network (RAN), edge, and central offices of 5G architecture and hence various deployment options. Network function virtualization allocates radio access network (RAN) functions in different nodes. URLLC services require function placement nearer to the ran to fulfill the lower latency requirement while eMBB require cloud access for implementation. Therefore arbitrary allocation of network function for different services is not possible. We aim to developed algorithms to find service-based placement for RAN functions in a multitenant environment with heterogeneous demands. We considered three generic classes of slices of eMBB, URLLC, mMTC. Every slice is characterized by some specific requirements, while the nodes and the links are resources constrained. The function placement problem corresponds to minimize the overall cost of allocating the different functions to the different nodes organized in layers for respecting the requirements of the given slices. Specifically, we proposed three algorithms based on the normalized preference associated with each slice on different layers of RAN architecture. The maximum preference algorithm places the functions on the most preferred position defined in the preference matrix. On the other hand, the proposed modified preference algorithm provides solutions by keeping track of the availability of computational resources and latency requirements of different services. We also used the Exhaustive Search Method for solving a function allocation problem.

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Alimi, Isiaka Ajewale. "Optimization of optical fronthaul for cloud computing radio access networks (CC-RANs)". Doctoral thesis, Universidade de Aveiro, 2018. http://hdl.handle.net/10773/23761.

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Doutoramento conjunto (MAP-Tele) em Engenharia Eletrotécnica/Telecomunicações
A proliferação de diversos tipos de dispositivos moveis, aplicações e serviços com grande necessidade de largura de banda têm contribuído para o aumento de ligações de banda larga e ao aumento do volume de trafego das redes de telecomunicações moveis. Este aumento exponencial tem posto uma enorme pressão nos mobile operadores de redes móveis (MNOs). Um dos aspetos principais deste recente desenvolvimento, é a necessidade que as redes têm de oferecer baixa complexidade nas ligações, como também baixo consumo energético, muito baixa latência e ao mesmo tempo uma grande capacidade por baixo usto. De maneira a resolver estas questões, os MNOs têm focado a sua atenção na redes de acesso por rádio em nuvem (C-RAN) principalmente devido aos seus benefícios em termos de otimização de performance e relação qualidade preço. O standard para a distribuição de sinais sem fios por um fronthaul C-RAN é o common public radio interface (CPRI). No entanto, ligações óticas baseadas em interfaces CPRI necessitam de uma grande largura de banda. Estes requerimentos podem também ser atingidos com uma implementação em ligação free space optical (FSO) que é um sistema ótico que usa comunicação sem fios. O FSO tem sido uma alternativa muito apelativa aos sistemas de comunicação rádio (RF) pois combinam a flexibilidade e mobilidade das redes RF ao mesmo tempo que permitem a elevada largura de banda permitida pelo sistema ótico. No entanto, as ligações FSO são suscetíveis a alterações atmosféricas que podem prejudicar o desempenho do sistema de comunicação. Estas limitações têm evitado o FSO de ser tornar uma excelente solução para o fronthaul. Uma caracterização precisa do canal e tecnologias mais avançadas são então necessárias para uma implementação pratica de ligações FSO. Nesta tese, vamos estudar uma implementação eficiente para fronthaul baseada em tecnologia á rádio-sobre-FSO (RoFSO). Propomos expressões em forma fechada para mitigação das perdas de propagação e para a estimação da capacidade do canal de maneira a aliviar a complexidade do sistema de comunicação. Simulações numéricas são também apresentadas para formatos de modulação adaptativas. São também considerados esquemas como um sistema hibrido RF/FSO e tecnologias de transmissão apoiadas por retransmissores que ajudam a alivar os requerimentos impostos por um backhaul/fronthaul de C-RAN. Os modelos propostos não só reduzem o esforço computacional, como também têm outros méritos, tais como, uma elevada precisão na estimação do canal e desempenho, baixo requisitos na capacidade de memória e uma rápida e estável operação comparativamente com o estado da arte em sistemas analíticos (PON)-FSO. Este sistema é implementado num recetor em tempo real que é emulado através de uma field-programmable gate array (FPGA) comercial. Permitindo assim um sistema aberto, interoperabilidade, portabilidade e também obedecer a standards de software aberto. Os esquemas híbridos têm a habilidade de suportar diferentes aplicações, serviços e múltiplos operadores a partilharem a mesma infraestrutura de fibra ótica.
The proliferation of different mobile devices, bandwidth-intensive applications and services contribute to the increase in the broadband connections and the volume of traffic on the mobile networks. This exponential growth has put considerable pressure on the mobile network operators (MNOs). In principal, there is a need for networks that not only offer low-complexity, low-energy consumption, and extremely low-latency but also high-capacity at relatively low cost. In order to address the demand, MNOs have given significant attention to the cloud radio access network (C-RAN) due to its beneficial features in terms of performance optimization and cost-effectiveness. The de facto standard for distributing wireless signal over the C-RAN fronthaul is the common public radio interface (CPRI). However, optical links based on CPRI interfaces requires large bandwidth. Also, the aforementioned requirements can be realized with the implementation of free space optical (FSO) link, which is an optical wireless system. The FSO is an appealing alternative to the radio frequency (RF) communication system that combines the flexibility and mobility offered by the RF networks with the high-data rates provided by the optical systems. However, the FSO links are susceptible to atmospheric impairments which eventually hinder the system performance. Consequently, these limitations prevent FSO from being an efficient standalone fronthaul solution. So, precise channel characterizations and advanced technologies are required for practical FSO link deployment and operation. In this thesis, we study an efficient fronthaul implementation that is based on radio-on-FSO (RoFSO) technologies. We propose closedform expressions for fading-mitigation and for the estimation of channel capacity so as to alleviate the system complexity. Numerical simulations are presented for adaptive modulation scheme using advanced modulation formats. We also consider schemes like hybrid RF/FSO and relay-assisted transmission technologies that can help in alleviating the stringent requirements by the C-RAN backhaul/fronthaul. The propose models not only reduce the computational requirements/efforts, but also have a number of diverse merits such as high-accuracy, low-memory requirements, fast and stable operation compared to the current state-of-the-art analytical based approaches. In addition to the FSO channel characterization, we present a proof-of-concept experiment in which we study the transmission capabilities of a hybrid passive optical network (PON)-FSO system. This is implemented with the real-time receiver that is emulated by a commercial field-programmable gate array (FPGA). This helps in facilitating an open system and hence enables interoperability, portability, and open software standards. The hybrid schemes have the ability to support different applications, services, and multiple operators over a shared optical fiber infrastructure.

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Lyazidi, Mohammed Yazid. "Dynamic resource allocation and network optimization in the Cloud Radio Access Network". Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066549.

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Le Cloud Radio Access Network (C-RAN) est une future direction dans les réseaux de communications sans fils pour déployer des systèmes cellulaires 4G et renforcer la migration des opérateurs vers la nouvelle génération 5G. En comparaison avec l'architecture traditionnelle des stations de base distribuées, l'architecture C-RAN apporte un lot d'avantages à l'opérateur: meilleure utilisation des ressources radio, flexibilité du réseau, minimisation de la puissance consommée et amenuisement des coûts de déploiement. Dans cette thèse, nous adressons le problème d'allocation dynamique des ressources et minimisation de la puissance des communications à liaison descendante dans le C-RAN. Notre recherche vise à allouer les ressources radio à des flux dynamiques d'utilisateurs, tout en trouvant les meilleures combinaisons entre points d'accès et unités de calculs, pour satisfaire la demande de trafic. Il s'agit en outre, d'un problème d'optimisation non linéaire et NP-difficile, comprenant plusieurs contraintes relatives aux demandes de ressources des utilisateurs, gestion d'interférences, capacités fixes des unités de calcul dans le Cloud et des liaisons de transport ainsi que la limitation de la puissance transmise maximale. Afin de surmonter la complexité inhérente à cette problématique du C-RAN, nous présentons différentes approches pour l'allocation dynamique des ressources en trois principales contributions. Les résultats de nos simulations prouvent l'efficacité de nos méthodes, comparé à celles existantes dans la littérature, en termes de taux de débit de satisfaction, nombre d'antennes actives, puissance consommée dans le Cloud, résilience et coût opérationnel du C-RAN
Cloud Radio Access Network (C-RAN) is a future direction in wireless communications for deploying cellular radio access subsystems in current 4G and next-generation 5G networks. In the C-RAN architecture, BaseBand Units (BBUs) are located in a pool of virtual base stations, which are connected via a high-bandwidth low latency fronthaul network to Radio Remote Heads (RRHs). In comparison to standalone clusters of distributed radio base stations, C-RAN architecture provides significant benefits in terms of centralized resource pooling, network flexibility and cost savings. In this thesis, we address the problem of dynamic resource allocation and power minimization in downlink communications for C-RAN. Our research aims to allocate baseband resources to dynamic flows of mobile users, while properly assigning RRHs to BBUs to accommodate the traffic and network demands. This is a non-linear NP-hard optimization problem, which encompasses many constraints such as mobile users' resources demands, interference management, BBU pool and fronthaul links capacities, as well as maximum transmission power limitation. To overcome the high complexity involved in this problem, we present several approaches for resource allocation strategies and tackle this issue in three stages. Obtained results prove the efficiency of our proposed strategies in terms of throughput satisfaction rate, number of active RRHs, BBU pool processing power, resiliency, and operational budget cost

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Celebi, Hasari. "Location awareness in cognitive radio networks". [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002562.

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Kalalas, Charalampos. "Cellular networks for smart grid communication". Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/620760.

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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 D2

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Matoussi, Salma. "User-Centric Slicing with Functional Splits in 5G Cloud-RAN". Electronic Thesis or Diss., Sorbonne université, 2021. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2021SORUS004.pdf.

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Le réseau d’accès radio (RAN) 5G vise à faire évoluer de nouvelles technologies couvrant l’infrastructure Cloud, les techniques de virtualisation et le réseau défini par logiciel (SDN). Des solutions avancées sont introduites pour répartir les fonctions du réseau d’accès radio entre des emplacements centralisés et distribués (découpage fonctionnel) afin d’améliorer la flexibilité du RAN. Cependant, l’une des préoccupations majeures est d’allouer efficacement les ressources RAN, tout en prenant en compte les exigences hétérogènes des services 5G. Dans cette thèse, nous abordons la problématique du provisionnement des ressources Cloud RAN centré sur l’utilisateur (appelé tranche d’utilisateurs ). Nous adoptons un déploiement flexible du découpage fonctionnel. Notre recherche vise à répondre conjointement aux besoins des utilisateurs finaux, tout en minimisant le coût de déploiement. Pour surmonter la grande complexité impliquée, nous proposons d’abord une nouvelle implémentation d’une architecture Cloud RAN, permettant le déploiement à la demande des ressources, désignée par AgilRAN. Deuxièmement, nous considérons le sous-problème de placement des fonctions de réseau et proposons une nouvelle stratégie de sélection de découpage fonctionnel centrée sur l’utilisateur nommée SPLIT-HPSO. Troisièmement, nous intégrons l’allocation des ressources radio. Pour ce faire, nous proposons une nouvelle heuristique appelée E2E-USA. Dans la quatrième étape, nous envisageons une approche basée sur l’apprentissage en profondeur pour proposer un schéma d’allocation temps réel des tranches d’utilisateurs, appelé DL-USA. Les résultats obtenus prouvent l’efficacité de nos stratégies proposées
5G Radio Access Network (RAN) aims to evolve new technologies spanning the Cloud infrastructure, virtualization techniques and Software Defined Network capabilities. Advanced solutions are introduced to split the RAN functions between centralized and distributed locations to improve the RAN flexibility. However, one of the major concerns is to efficiently allocate RAN resources, while supporting heterogeneous 5G service requirements. In this thesis, we address the problematic of the user-centric RAN slice provisioning, within a Cloud RAN infrastructure enabling flexible functional splits. Our research aims to jointly meet the end users’ requirements, while minimizing the deployment cost. The problem is NP-hard. To overcome the great complexity involved, we propose a number of heuristic provisioning strategies and we tackle the problem on four stages. First, we propose a new implementation of a cost efficient C-RAN architecture, enabling on-demand deployment of RAN resources, denoted by AgilRAN. Second, we consider the network function placement sub-problem and propound a new scalable user-centric functional split selection strategy named SPLIT-HPSO. Third, we integrate the radio resource allocation scheme in the functional split selection optimization approach. To do so, we propose a new heuristic based on Swarm Particle Optimization and Dijkstra approaches, so called E2E-USA. In the fourth stage, we consider a deep learning based approach for user-centric RAN Slice Allocation scheme, so called DL-USA, to operate in real-time. The results obtained prove the efficiency of our proposed strategies

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D'Oro, Salvatore. "User-Centric resource allocation through a power-efficient jamming-proof RAN on top of a multi-tenant backhaul". Doctoral thesis, Università di Catania, 2016. http://hdl.handle.net/10761/3856.

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The exponential growth in the number of communicating devices and the increasing demand for better and high-performance communications have made allocation of network resources an issue of extreme importance. The problem is further exacerbated if we consider that, while the number of deployed devices is massive, the amount of network resources is still limited. In this thesis, we aim at providing a holistic approach for resource allocation in modern telecommunication networks. Specifically, we consider a network consisting of a backhaul interconnecting a Radio Access Network (RAN) that provides mobile users with wireless access to a Core Network (CN). The CN allows access to the Internet and enables end-to-end communications by routing users data and calls. We take both energy and security aspects into account, by proposing a power-efficient and jamming-proof resource allocation scheme for the RAN. Furthermore, we consider the relevant and emerging case where the backhaul is shared among different tenants. Accordingly, we exploit Software Defined Networks (SDNs) and Network Function Virtualization (NFV) paradigms to provide dynamic and flexible network and service management in the multi-tenant backhaul and CN, respectively. We formulate the resource allocation problem through both centralized and distributed approaches, we discuss the existence and uniqueness of efficient resource allocation solutions and we provide distributed privacy-preserving algorithms that provably converge allow to the optimal resource allocation policy by exploiting only local or shared information.

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Olsson, Joel, e Junior Asante. "5G Simulation Framework". Thesis, Linköpings universitet, Kommunikationssystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-149484.

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From the first generation, 1G, to the fourth generation, 4G, the development and technological advancements in telecommunications network systems have been remarkable. Faster and better connections have opened up for new markets, ideas and possibilities, to that extent that there now is a demand that surpasses the supply. Despite all these advancements made in the mobile communications field most of the concept of how the technology works and its infrastructure has remained the same. This however, is about to change with the introduction of the fifth generation (5G) mobile communication. With the introduction of 5G much of the technology introduced will be different from that of previous generations. This change extends to include the entire infrastructure of the mobile communications system. With these major changes, many of the tools available today for telecommunications network evaluation do not really suffice to include the 5G network standard. For this reason, there is a need to develop a new kind of tool that will be able to include the changes brought by this new network standard. In this thesis a simulation framework adapted for the next generation telecommunication standard 5G is set to be developed. This framework should include many of the characteristics that set 5G aside from previous generations.

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Salhab, Nazih. "Resource provisioning and dynamic optimization of Network Slices in an SDN/NFV environment". Thesis, Paris Est, 2020. http://www.theses.fr/2020PESC2019.

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Pour offrir le haut débit mobile amélioré, les communications massives et critiques pour l'Internet des objets, la cinquième génération (5G) des réseaux mobiles est déployée à nos jours, en se basant sur plusieurs catalyseurs: le réseau d'accès radio nuagique (C-RAN), les réseaux programmables (SDN), et la virtualisation des fonctions réseaux (NFV). Le C-RAN décompose la nouvelle génération Node-B (gNB) en: i) tête radio distante (RRH), ii) unité digitale (DU), et iii) unité centrale (CU), appelée aussi unité cloud ou collaborative. Les DU et CU implémentent la base bande (BBU) tout en utilisant les huit options du split du front-haul pour une performance affinée. La RRH implémente la circuiterie extérieure pour la radio. Le SDN permet la programmation du comportement du réseau en découplant le plan de contrôle du plan utilisateur tout en centralisant la gestion des flux en un nœud de contrôle dédié. La NFV, d'autre part, utilise les technologies de virtualisation pour lancer les fonctions réseaux virtualisées (FRV) sur des serveurs conventionnels du marché. SDN et NFV permettent la partition du C-RAN, réseaux de transport et cœur en tant que tranches définies comme des réseaux virtuels et isolés de bout en bout conçus pour couvrir des exigences spécifiques aux différentes cas d’utilisations. L'objectif principal de cette thèse est de développer des algorithmes de provisionnement des ressources (unité de traitement centrale (CPU), mémoire, énergie, et spectre) pour la 5G, tout en garantissant un emplacement optimal des FRV dans une infrastructure nuagique. Pour achever ce but ultime, on adresse l'optimisation des ressources et d'infrastructure dans les trois domaines des réseaux mobiles: le cœur de réseau 5G (5GC), le C-RAN et les contrôleurs SDN. En tant qu’une première contribution, nous formulons la décharge du 5GC en tant qu'une optimisation sous contraintes ciblant plusieurs objectifs (coût de virtualisation, puissance de traitement, et charge du réseau) pour faire les décisions optimales et avec la plus faible latence. On optimise l'utilisation de l'infrastructure réseau en termes de capacité de traitement, consommation d'énergie et de débit, tout en respectant les exigences par tranche (latence, fiabilité, et capacité, etc.). Sachant que l'infrastructure est assujettie à des évènements fréquents tels que l'arrivée et le départ des utilisateurs/dispositifs, les changements continuels du réseau (reconfigurations, et défauts inévitables), nous proposons l'optimisation dynamique moyennant la technique de Branch, Cut and Price (BCP), en discutant les effets de ces objectifs sur plusieurs métriques. Notre 2ème contribution consiste à optimiser le C-RAN par un regroupement dynamique des RRH aux BBU (DU, CU). D’une part, nous proposons ce regroupement pour optimiser le débit en down-link. D’autre part, nous proposons la prédiction du power Head-room (PHR), sur le lien hertzien pour optimiser le débit en up-link. Dans notre troisième contribution, nous adressons l'orchestration des tranches réseaux 5G à travers le contrôleur C-RAN défini par logiciel en utilisant des approches de ML pour: la classification des exigences de performance, la prédiction des ratios de tranchage, le contrôle d'admission, le séquencement, et la gestion adaptative des ressources. En se basant sur des évaluations exhaustives moyennant notre prototype 5G basé sur OpenAirInterface, et en utilisant une pile de performance intégrée, nous montrons que nos propositions dépassent les stratégies connexes en termes de rapidité d'optimisation, des coûts de virtualisation et de débit
To address the enhanced mobile broadband, massive and critical communications for the Internet of things, Fifth Generation (5G) of mobile communications is being deployed, nowadays, relying on multiple enablers, namely: Cloud Radio Access Network (C-RAN), Software-Defined Networking (SDN) and Network Function Virtualization (NFV).C-RAN decomposes the new generation Node-B into: i) Remote Radio Head (RRH), ii) Digital Unit (DU), and iii) Central Unit (CU), also known as Cloud or Collaborative Unit.DUs and CUs are the two blocks that implement the former 4G Baseband Unit (BBU) while leveraging eight options of functional splits of the front-haul for a fine-tuned performance. The RRH implements the radio frequency outdoor circuitry. SDN allows programming network's behavior by decoupling the control plane from the user plane and centralizing the flow management in a dedicated controller node. NFV, on the other hand, uses virtualization technology to run Virtualized Network Functions (VNFs) on commodity servers. SDN and NFV allow the partitioning of the C-RAN, transport and core networks as network slices defined as isolated and virtual end-to-end networks tailored to fulfill diverse requirements requested by a particular application. The main objective of this thesis is to develop resource-provisioning algorithms (Central Processing Unit (CPU), memory, energy, and spectrum) for 5G networks while guaranteeing optimal provisioning of VNFs for a cloud-based infrastructure. To achieve this ultimate goal, we address the optimization of both resources and infrastructure within three network domains: 5G Core Network (5GC), C-RAN and the SDN controllers. We, first formulate the 5GC offloading problem as a constrained-optimization to meet multiple objectives (virtualization cost, processing power and network load) by making optimal decisions with minimum latency. We optimize the usage of the network infrastructure in terms of computing capabilities, power consumption, and bitrate, while meeting the needs per slice (latency, reliability, efficiency, etc.). Knowing that the infrastructure is subject to frequent and massive events such as the arrival/departure of users/devices, continuous network evolution (reconfigurations, and inevitable failures), we propose a dynamic optimization using Branch, Cut and Price, while discussing objectives effects on multiple metrics.Our second contribution consists of optimizing the C-RAN by proposing a dynamic mapping of RRHs to BBUs (DUs and CUs). On first hand, we propose clustering the RRHs in an aim to optimize the downlink throughput. On second hand, we propose the prediction of the Power Headroom (PHR), to optimize the throughput on the uplink.We formulate our RRHs clustering problem as k-dimensional multiple Knapsacks and the prediction of PHR using different Machine Learning (ML) approaches to minimize the interference and maximize the throughput.Finally, we address the orchestration of 5G network slices through the software defined C-RAN controller using ML-based approaches, for all of: classification of performance requirements, forecasting of slicing ratios, admission controlling, scheduling and adaptive resource management.Based on extensive evaluations conducted in our 5G experimental prototype based on OpenAirInterface, and using an integrated performance management stack, we show that our proposals outperform the prominent related strategies in terms of optimization speed, computing cost, and achieved throughput

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Geoghegan, Mark. "Challenges of Implementing an iNET Transceiver for the Radio Access Network Standard (RANS)". International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595621.

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Montenegro, Manuel David Fonseca. "Capacity forecasting for radio access networks". Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/15782.

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Mestrado em Engenharia Eletrónica e Telecomunicações
The mobile networks market (focus of this work) strategy is based on the consolidation of the installed structure and the optimization of the already existent resources. The increasingly competition and aggression of this market requires, to the mobile operators, a continuous maintenance and update of the networks in order to obtain the minimum number of fails and provide the best experience for its subscribers. In this context, this dissertation presents a study aiming to assist the mobile operators improving future network modifications. In overview, this dissertation compares several forecasting methods (mostly based on time series analysis) capable of support mobile operators with their network planning. Moreover, it presents several network indicators about the more common bottlenecks.
A estratégia comum dos operadores no mercado das redes móveis (área onde este trabalho se debruça) passa por uma consolidação da sua rede base já instalada e pela otimização dos recursos já existentes. A crescente competitividade e agressividade deste mercado obrigam a que os operadores mantenham a sua rede atualizada e com o menor número de falhas possível, com a finalidade de oferecer a melhor experiência aos seus utilizadores. Neste contexto, esta dissertação apresenta um estudo que auxilia os operadores a aperfeiçoar futuras alterações na sua rede. De um modo geral, esta dissertação compara alguns métodos de previsão (baseados maioritariamente na análise de séries temporais) capazes de assistir os operadores no planeamento da sua rede e ainda apresenta alguns indicadores de rede onde as limitações de desempenho são mais frequentes.

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Clancy, Thomas Charles. "Dynamic spectrum access in cognitive radio networks". College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3511.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Bian, Kaigui. "Medium Access Control in Cognitive Radio Networks". Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/37591.

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Cognitive radio (CR) is seen as one of the enabling technologies for realizing a new regulatory spectrum management paradigm, viz. opportunistic spectrum sharing (OSS). In the OSS paradigm, unlicensed users (a.k.a. secondary users) opportunistically operate in fallow licensed spectrum on a non-interference basis to licensed users (a.k.a. incumbent or primary users). Incumbent users have absolute priority in licensed bands, and secondary users must vacate the channel where incumbent user signals are detected. A CR network is composed of secondary users equipped with CRs and it can coexist with incumbent users in licensed bands under the OSS paradigm. The coexistence between incumbent users and secondary users is referred to as incumbent coexistence, and the coexistence between CR networks of the same type is referred to as self-coexistence. In this dissertation, we address three coexistence-related problems at the medium access control (MAC) layer in CR networks: (1) the rendezvous (control channel) establishment problem, (2) the channel assignment problem in an ad hoc CR network, and (3) the spectrum sharing problem between infrastructure-based CR networks, i.e., the 802.22 wireless regional area networks (WRANs). Existing MAC layer protocols in conventional wireless networks fail to adequately address the key issues concerning incumbent and self coexistence that emerge in CR networks. To solve the rendezvous establishment problem, we present a systematic approach, based on quorum systems, for designing channel hopping protocols that ensure a pair of CRs to "rendezvous" within an upper-bounded time over a common channel that is free of incumbent user signals. In a single radio interface, ad hoc CR network, we propose a distributed channel assignment scheme that assigns channels at the granularity of "segments" for minimizing the channel switching overhead. By taking into account the coexistence requirements, we propose an inter-network spectrum sharing protocol that enables the sharing of vacant TV white space among coexisting WRANs. Our analytical and simulation results show that these proposed schemes can effectively address the aforementioned MAC layer coexistence problems in CR networks.
Ph. D.

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Peesapati, Saivenkata Krishna Gowtam. "Energy Efficiency of 5G Radio Access Networks". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289433.

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The roll-out of the fifth-generation (5G) wireless networks alongside existing generations and characterized by a dense deployment of base stations (BSs) to serve an ever-increasing number of users and services leads to a drastic increase in the overall network energy consumption (EC). It can lead to an unprecedented rise in operational expenditure (OPEX) for the network operators and an increased global carbon footprint. The present-day networks are dimensioned according to the peak traffic demands, and hence are under-utilized due to the daily traffic variations. Therefore, to save energy, BSs can be put into sleep with different levels following the daily load variations. Selection of the right sleep level at the right instant is important to adapt the availability of the resources to the traffic load to maximize the energy savings without degrading the performance of the network. Previous studies focused on the selection of sleep modes (SMs) to maximize energy saving or the sleep duration given configuration and network resources. However, adaptive BS configuration together with SMs have not been investigated. In this thesis, the goal is to consider the design of the wireless network resources to cover an area with a given traffic demand in combination with sleep mode management. To achieve this, a novel EC model is proposed to capture the activity time of a 5G BS in a multi-cell environment. The activity factor of a BS is defined as the fraction of time the BS is transmitting over a fixed period and is dependent on the amount of BS resources. The new model captures the variation in power consumption by configuring three BS resources: 1) the active array size, 2) the bandwidth, and 3) the spatial multiplexing factor. We then implement a Q-learning algorithm to adapt these resources following the traffic demand and also the selection of sleep levels. Our results show that the difference in the average daily EC of BSs considered can be as high as 60% depending on the deployment area. Furthermore, the EC of a BS can be reduced by 57% during the low traffic hours by having deeper sleep levels as compared to the baseline scenario with no sleep modes. Implementing the resource adaptation algorithm further reduces the average EC of the BS by up to 20% as compared to the case without resource adaptation. However, the EE gain obtained by the algorithm depends on its convergence, which varies with the distribution of the users in the cell, the peak traffic demand, and the BS resources available. Our results show that by combining resource adaptation with deep sleep levels, one can obtain significant energy savings under variable traffic load. However, to ensure the reliability of the results obtained, we emphasize the need to guarantee the convergence of the algorithm before its use for resource adaptation.
Under de senaste åren har intresset för energieffektivitet (EE) av mobila kommunikationssystem ökat på grund av den ökande energiförbrukningen (EF). Med femte generationens mobilsystem, vilket kännetecknas av mer komplexa och kraftfulla basstationer (BS) för att betjäna ett ständigt ökande antal användare och tjänster, riskerar nätverkets totala EF att öka ytterligare. Detta kan leda till en markant ökning av operativa utgifter (OPEX) för nätoperatörerna och ett ökat globalt koldioxidavtryck. Många studier har visat att dagens nätverk ofta är överdimensionerade och att radioresurserna är underutnyttjade på grund av variationerna i det dagliga trafikbehovet. Genom att anpassa BS radioresurser efter trafikbehovet kan man säkerställa att man uppfyller användarkraven samtidigt som man minskar den totala EF. I denna studie föreslås en aktivitetsbaserad metod för att utvärdera EF för en BS. Aktivitetsfaktorn för en BS definieras som den bråkdel av tiden som BS är aktiv (sänder data) under en fast period och är beroende av mängden radioresurser. För att kvantifiera EF för en BS föreslås en ny modell som beräknar in effekt till BS som funktion av utstrålad effekt från BS. Den nya modellen fångar variationen i energiförbrukning med tre huvudsakliga radioresurser som är: 1) antal sändarantenner 2) bandbredd och 3) den spatiella multiplexingfaktorn (antal användare som schemaläggs samtidigt). Därefter implementeras en Q- inlärningsalgoritm för att anpassa dessa resurser efter det upplevda trafikbehovet och vilolägen som BS kan växla till när den är inaktiv. Ett viloläge innebär att viss hårdvara i BS stängs av. Resultatet visar att man genom att identifiera rätt typ av BS utifrån lokala trafikförhållanden kan få energibesparingar så höga som 60%. Vidare kan EF för en BS reduceras med 57% under den tid av dygnet då trafiken är som lägst genom att ha djupare vilolägen jämfört med basscenariot utan vilolägen. Genom att implementera Q-inlärningsalgoritmen som anpassar tillgängliga radioresurser till trafikbehovet minskar den genomsnittliga EF för BS ytterligare med upp till 20%. Vinsten i EE som erhålls av algoritmen beror dock till stor del på dess konvergens, som varierar med fördelningen av användarna i cellen, topptrafikbehovet och BS tillgängliga radioresurser. Resultatet visar att genom att kombinera resursanpassning med vilolägen kan man få betydande energibesparingar under varierande trafikbelastning. För att säkerställa tillförlitligheten av de erhållna resultaten betonas emellertid behovet av att garantera konvergensen av algoritmen innan den används för resursanpassning.

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Piao, Guihua. "Radio resource management for integrated services in multi-radio access networks". Kassel Kassel Univ. Press, 2006. http://www.uni-kassel.de/hrz/db4/extern/dbupress/publik/abstract.php?978-3-89958-269-7.

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Piao, Guihua. "Radio resource management for integrated services in multi-radio access networks". Kassel Kassel Univ. Press, 2007. http://d-nb.info/986595012/34.

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Abbood, Abdul Nasser Abdul Jabbar. "Optimised radio over fibre links for next generation radio access networks". Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/17019.

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Optical fibre has become the dominant theme of transmission in long haul, high data rate communication systems due to its tremendous bandwidth and low loss. Radio over Fibre (RoF) technology facilitates the seamless integration between wireless and optical communication systems and found to be the most promising solution to meet the exponential bandwidth demands expected for the upcoming years. However, the main bit-rate/distance limitation in RoF systems is the chromatic dispersion. In this thesis, the two generations of RoF technologies, namely Analogue RoF (ARoF) and Digital RoF (DRoF) are investigated. The overall aim of this research is to optimise the optical bandwidth utilisation of these two approaches for a typical transmission of the fronthaul link proposed in the next generation Centralised Radio Access Network (C-RAN). Consequently, a number of physical layer design scenarios for the optimised transmission of the Radio Frequency (RF) signals over a Standards Single Mode Fibre (SSMF) are demonstrated. Firstly, for an ARoF transmission, where the analogue RF signals are transported over SSMF using an optical carrier, a bidirectional link transmitting four Downlink/Uplink channels in a chromatic dispersion limited scenario is designed. Simulation results have shown a clear constellation diagram of a 2.5 Gb/s RF signal transmission over 120 km fibre length. Secondly, a DRoF system with reduced optical bandwidth occupancy is proposed. This system employs an optical Duobinary transmission to the digitised RF signal at the transmitter side to reduce its spectrum and to address the chromatic dispersion effect, simultaneously. Simulation results demonstrate the capability of the proposed system to maintain high-quality transmission of the digitised signals over 70 km of fibre distance without dispersion compensation requirements. Finally, an advanced DRoF transmission link based on integrating digital Optical Single Sideband (OSSB) transmission with Duobinary encoding scheme is designed. Simulation results have clearly verified system's robustness against transmission impairments and have better performances in terms of the obtained BER and EVM with respect to the 3GPP standardised values. Moreover, the results show that both transmission distance and power budget are furtherly improved in comparison with two other digital transmission scenarios.

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Subramani, Siva Kupanna. "Seamless spectrum access in distributed cognitive radio networks". Thesis, University of Bristol, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.508100.

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El, Helou Melhem. "Radio Access Technology Selection in Heterogeneous Wireless Networks". Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S086/document.

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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

37

Hu, Wendong. "Medium access control protocols for cognitive radio based dynamics spectrum access networks". Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1580792591&sid=28&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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38

Al, Noor Mazin. "Green radio communication networks applying radio-over-fibre technology for wireless access". Thesis, Middlesex University, 2012. http://eprints.mdx.ac.uk/8995/.

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Abstract (sommario):

Wireless communication increasingly is becoming the first choice link to enter into the global information society. It is an essential part of broadband communication networks, due to its capacity to cover the end-user domain, outdoors or indoors. The use of mobile phones and broadband has already exceeded the one of the fixed telephones and has caused tremendous changes in peoples life, as not only to be recognised in the current political overthrows. The all-around presence of wireless communication links combined with functions that support mobility will make a roaming person-bound communication network possible in the near future. This idea of a personal network, in which a user has his own communication environment available everywhere, necessitates immense numbers of radio access points to maintain the wireless links and support mobility. The progress towards “all-around wireless” needs budget and easily maintainable radio access points, with simplified signal processing and consolidation of the radio network functions in a central station. The RF energy consumption in mobile base stations is one of the main problems in the wireless communication system, which has led to the worldwide research in so called green communication, which offers an environmentally friendly and cost-effective solution. In order to extend networks and mobility support, the simplification of antenna stations and broadband communication capacity becomes an increasingly urgent demand, also the extension of the wireless signal transmission distance to consolidate the signal processing in a centralised site. Radio-over-Fibre technology (RoF) was considered and found to be the most promising solution to achieve effective delivery of wireless and baseband signals, also to reduce RF energy consumption. The overall aim of this research project was to simulate the transmission of wireless and baseband RF signals via fibre for a long distance in high quality, consuming a low-power budget. Therefore, this thesis demonstrated a green radio communication network and the advantage of transmitting signals via fibre rather than via air. The contributions of this research work were described in the follows: Firstly, a comparison of the power consumption in WiMAX via air and fibre is presented. As shown in the simulation results, the power budget for the transmission of 64 QAM WiMAX IEEE 802.16-2005 via air for a distance of 5km lies at -189.67 dB, whereas for the transmission via RoF for a distance of 140km, the power consumption ranges at 65dB. Through the deployment of a triple symmetrical compensator technique, consisting of SMF, DCF and FBG, the transmission distance of the 54 Mbps WiMAX signal can be increased to 410km without increasing the power budget of 65dB. An amendment of the triple compensator technique to SMF, DCF and CFBG allows a 120Mbps WiMAX signal transmission with a clear RF spectrum of 3.5 GHz and constellation diagram over a fibre length of 792km using a power budget of 192dB. Secondly, the thesis demonstrates a simulation setup for the deployment of more than one wireless system, namely 64 QAM WiMAX IEEE 802.16-2005 and LTE, for a data bit rate of 1Gbps via Wavelength Division Multiplexing (WDM) RoF over a transmission distance of 1800km. The RoF system includes two triple symmetrical compensator techniques - DCF, SMF, and CFBG - to obtain a large bandwidth, power budget of 393.6dB and a high signal quality for the long transmission distance. Finally, the thesis proposed a high data bit rate and energy efficient simulation architecture, applying a passive optical component for a transmission span up to 600km. A Gigabit Optical Passive Network (GPON) based on RoF downlink 2.5 Gbps and uplink 1.25Gbps is employed to carry LTE and WiMAX, also 18 digital channels by utilising Coarse Wavelength Division Multiplexing (CWDM). The setup achieved high data speed, a low-power budget of 151.2dB, and an increased service length of up to 600km.

39

Turyagyenda, Charles. "Energy efficient radio resource management for future mobile cellular radio access networks". Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/6247/.

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Historically mobile Radio Access Networks (RANs) were optimised initially to maximise coverage and subsequently to improve capacity, user data rates and quality of service. However, the recent exponential growth in the volume of transmitted data coupled with the ever increasing energy costs has highlighted the need to optimise futuristic RANs from an energy efficiency perspective. This research study postulated the utilisation of radio resource management approaches to improve the energy efficiency of modern RANs, with a particular emphasis on the radio frequency energy performance. The research study yielded the following major outcomes. First, there was notable positive correlation between user channel quality improvements and the energy efficiency of RANs. Second, channel quality aware packet schedulers were more energy efficient than channel quality ignorant packet schedulers. Third, energy aware scheduling metrics coupled with power control algorithms can be utilised to optimise and refine the energy efficiency performance of the rate adaptive frequency domain packet scheduling. Fourth, the dynamic temporal and spatial traffic load characteristics, in the radio access network, present energy saving opportunities through collaborative and cooperative Inter-Cell Interference (ICI) management among neighbouring base stations. While the results presented in this thesis pertain to radio frequency and/or radio head energy consumption, the improved energy efficiency could be leveraged by increasing the inter site distance between base stations subsequently reducing the density of base stations in any given geographical area thus reducing the energy consumption of the RANs as a whole. The benefits of energy efficient RANs are twofold, i.e. reduction in the amount of CO2 emission and lower operating expenditure (OPEX).

40

Bolívar, Díaz Nicolás. "Medium access control messaging scheme for cognitive radio networks". Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/84098.

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Cognitive Radio (CR) is one possible option for mitigating the inefficient wireless spectrum distribution that occurs as a result of fixed spectrum allocation. The use of Dynamic Spectrum Access capabilities will potentially enable secondary users to utilize available and unoccupied frequency slots (channels) whenever the licensed users for those channels are absent. In Cognitive Radio Networks (CRNs), whenever users access the spectrum in an opportunistic manner, control messaging is a crucial issue to ensure that secondary users, i.e. Cognitive Radio Users (CRUs), do not interfere with the licensed users, i.e. Primary Users. In CRNs, where not all CRUs share the same set of channels, i.e. CRUs with Heterogeneous Frequency Devices (HFD), a set of channels must be chosen with care to allow all CRUs in the network to be able to transmit and receive control information. The thesis considers how Control Messaging Schemes (CMSs) can be used within CRNs and proposes a novel CMS for a CRN supporting HFDs. The thesis starts by classifying the CMSs; generating a new taxonomy and identifying the main characteristics for an efficient CRN with HFD. Then, different mathematical approaches for choosing the set of channels used for control information are presented. Next, a CMS for a CRN with HFDs model based upon the aforementioned characteristics and calculating the minimum number of channels for transmitting control information is proposed. Finally the thesis concludes with a number of CMS being presented and evaluated in terms of their impact upon transmission efficiency.

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Herlich, Matthias [Verfasser]. "Reducing energy consumption of radio access networks / Matthias Herlich". Paderborn : Universitätsbibliothek, 2014. http://d-nb.info/1048130053/34.

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42

Boulos, Karen. "BBU-RRH Association Optimization in Cloud-Radio Access Networks". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS209/document.

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De nos jours, la demande en trafic mobile a considérablement augmenté. Face à cette croissance, plusieurs propositions font l'objet d'étude pour remédier à un tel défi. L’architecture des réseaux d’accès de type Cloud (C-RAN) est l’une des propositions pour faire face à cette demande croissante, et constitue une solution candidate potentielle pour les réseaux futurs 5G. L'architecture C-RAN dissocie deux éléments principaux de la station de base: La BBU ou ``Baseband Unit", qui constitue une unité intelligente pour le traitement des données en bande de base, et le RRH ou ``Remote Radio Head", constituant en une antenne passive pour fournir l'accès aux utilisateurs (UEs). Grâce à l’architecture C-RAN, les BBUs sont centralement regroupées, alors que les RRHs sont distribués sur plusieurs sites. Plusieurs avantages sont ainsi dérivés, tels que le gain en multiplexage statistique, l’efficacité d’utilisation des ressources, et l’économie de puissance. Contrairement à l’architecture conventionnelle où chaque RRH est exclusivement associé à une BBU, dans l’architecture C-RAN, plusieurs RRHs sont regroupés en une seule BBU lorsque les conditions de charge sont faibles. Ceci présente plusieurs avantages, tel que l’amélioration en efficacité énergétique et la minimisation en consommation de puissance. Dans cette thèse, nous adressons le problème d’optimisation des associations BBU-RRH. Nous nous intéressons à l’optimisation des regroupements des RRHs aux BBUs en tenant compte de critères multiples. Plusieurs contraintes sont ainsi envisagées, tel que la réduction de la consommation d'énergie sous garantie de Qualité de Service (QoS) minimale. En outre, la prise en compte du changement du niveau d’interférence en activant/désactivant les BBUs est primordiale pour l’amélioration de l’efficacité spectrale. En plus, décider dynamiquement de la réassociation des RRHs aux BBUs sous des conditions de charges variables représente un défi, vu que les UEs connectés aux RRHs changeant leurs associations font face à des ``handovers" (HOs)
The demand on mobile traffic has been largely increasing nowadays. Facing such growth, several propositions are being studied to cope with this challenge. Cloud-Radio Access Networks Architecture (C-RAN) is one of the proposed solutions to address the increased demand, and is a potential candidate for future 5G networks. The C-RAN architecture dissociates two main elements composing the base station: The Baseband Unit (BBU), consisting in an intelligent element to perform baseband tasks functionalities, and the Remote Radio Head (RRH), that consists in a passive antenna element to provide access for serviced User Equipments (UEs). In C-RAN architecture, the BBUs migrate to a Cloud data center, while RRHs remain distributed across multiple sites. Several advantages are derived, such as statistical multiplexing gain, efficiency in resource utilization and power saving. Contrarily to conventional architecture, where each RRH is associated to one BBU, in C-RAN architecture, multiple RRHs can be embraced by one single BBU when network load conditions are low, bringing along several benefits, such as enhanced energy efficiency, and power consumption minimization. In this thesis, the BBU-RRH association optimization problem is addressed. Our aim is to optimize the BBU-RRH association schemes, taking into consideration several criteria. The problem presents many constraints: For example, achieving minimized power consumption while guaranteeing a minimum level of Quality of Service (QoS) is a challenging task. Further, taking into account the interference level variation while turning ON/OFF BBUs is paramount to achieve enhanced spectral efficiency. Moreover, deciding how to re-associate RRHs to BBUs under dynamic load conditions is also a challenge, since connected UEs face handovers (HOs) when RRHs change their associations

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Harutyunyan, Davit. "Flexible functional split in the 5g radio access networks". Doctoral thesis, University of Trento, 2019. http://eprints-phd.biblio.unitn.it/3606/2/Davit_Harutyunyan_thesis_final.pdf.

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Recent developments in mobile networks towards the fifth generation (5G) communication technology have been mainly driven by an explosive increase in mobile traffic demand and emerging vertical applications with their diverse Quality–of–Service (QoS) requirements, which current mobile networks are likely to fall short of satisfying. New technological cost–efficient solutions are, therefore, required to boost the network capacity and advance its capabilities in order to support the QoS requirements of, for example, enhanced mobile broadband services and the ones requiring ultra–reliable low latency communication. Network densification is known to be as one of the promising approaches aiming to increase the network capacity. This is achieved thanks to aggressive frequency reuse at small cells. Nonetheless, this entails performance degradation especially for cell–edge users due to a high Inter–cell Interference (ICI) level. Cloud Radio Access Network (C–RAN) architecture has been proposed as an efficient way to address the aforementioned challenges, tackle some of the problems persistent in the present–day mobile networks (e.g., inefficient use of frequency bands, high power consumption) and, by employing virtualization techniques, facilitate the network management while paving a way for new business opportunities for mobile virtual network operators. The main idea behind C–RAN is to decouple the radio unit of a base station, referred as a Decentralized Unit (DU) from the baseband processing unit, referred as a Centralized Unit (CU) and virtualize the latter in a centralized location, referred as a CU pool. Then, by executing so–called "functional split" in the RAN protocol stack between the CU and the DU, identify the RAN functionalities that are to be performed at the DU and the CU pool. Depending on the selected functional split (i.e., the resource centralization level), the bandwidth and latency requirements vary in the fronthaul network, which is the one interconnecting the DU with the CU pool. This results in a different level of resource centralization benefits. Thus, an inherent trade–off exists between resource centralization benefits and fronthaul requirements in the C–RAN architecture. C–RAN, although provides numerous advantages, raises a series of challenges one of which, depending on the functional split option, is a huge fronthaul bandwidth requirement. Optical fiber, thanks to its high bandwidth and low latency characteristics, is perceived to be the most capable fronthauling option; nevertheless, it requires a huge investment. Fortunately, recent advancement in the MillimeterWave (mmWave) wireless technology allows for multi–Gbps transmission over the distance of one kilometer, therefore, making it a good candidate for the fronthaul network in an ultra–dense small cell deployment scenario. In this doctoral dissertation, we first study the trade–offs between different functional splits, considering the mmWave technology in the fronthaul network. Specifically, we formulate and solve a Virtual Network Embedding (VNE) problem that aims at minimizing the fronthaul bandwidth utilization along with the number of active mmWave interfaces, and therefore, also minimizing the power consumption in the fronthaul network for different functional split scenarios. We then carry out a relative comparison between themmWave and optical fiber fronthauling technologies in terms of their deployment cost in order to ascertain when it would be economically more efficient to employ mmWave fronthaul instead of optical fiber. Different functional splits enable theMobile Network Operators (MNOs) to harvest different level of resource centralization benefits and pose diverse fronthaul requirements. There is no one–fits–all functional split that can be adopted in C–RAN to cope with all of its challenges since each split is more appropriate to be employed in a specific scenario in comparison with the others. Thus, another problem is to select the optimal functional split for each small cell in the network. This is a non–trivial task since there are a number of parameters to be taken into account in order to make such a choice. To this end, we developed a set of algorithms that dynamically select an optimal split option for each small cell considering ICI level as the main criterion. The dynamic functional selection approach is motivated by the argument that a single static functional split is not a viable option especially in the long run. The proposed algorithms provide MNOs with various options to select between promptness, solution optimality, and scalability. After having thoroughly analyzed the C–RAN architecture along with the pros and cons of different functional split options, the main objective for MNOs, who already own mobile network infrastructures and want to migrate to the C–RAN architecture, would be to accomplish such a migration with minimal investments. We developed an algorithm that aims at reducing the required investments by reusing the available infrastructure in the most efficient way. To quantify the economic benefit in terms of Total Cost of Ownership (TCO) savings, a case study is carried out considering a small cluster of an operational Long Term Evolution Advanced (LTE–A) network in the simulation and the proposed infrastructure–aware C–RAN migration algorithm is compared with its infrastructure–unaware counterpart. We also evaluate the multiplexing gain provided by the C–RAN in a specific functional split case and draw a comparison with the one achievable in traditional LTE networks.

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Foukas, Xenofon. "Towards a programmable and virtualized mobile radio access network architecture". Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31406.

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Emerging 5G mobile networks are envisioned to become multi-service environments, enabling the dynamic deployment of services with a diverse set of performance requirements, accommodating the needs of mobile network operators, verticals and over-the-top service providers. The Radio Access Network (RAN) part of mobile networks is expected to play a very significant role towards this evolution. Unfortunately, such a vision cannot be efficiently supported by the conventional RAN architecture, which adopts a fixed and rigid design. For the network to evolve, flexibility in the creation, management and control of the RAN components is of paramount importance. The key elements that can allow us to attain this flexibility are the programmability and the virtualization of the network functions. While in the case of the mobile core, these issues have been extensively studied due to the advent of technologies like Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) and the similarities that the core shares with other wired networks like data centers, research in the domain of the RAN is still in its infancy. The contributions made in this thesis significantly advance the state of the art in the domain of RAN programmability and virtualization in three dimensions. First, we design and implement a software-defined RAN (SD-RAN) platform called FlexRAN, that provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. Second, we leverage the capabilities of the FlexRAN platform to design and implement Orion, which is a novel RAN slicing system that enables the dynamic on-the-fly virtualization of base stations, the flexible customization of slices to meet their respective service needs and which can be used in an end-to-end network slicing setting. Third, we focus on the use case of multi-tenancy in a neutral-host indoors small-cell environment, where we design Iris, a system that builds on the capabilities of FlexRAN and Orion and introduces a dynamic pricing mechanism for the efficient and flexible allocation of shared spectrum to the tenants. A number of additional use cases that highlight the benefits of the developed systems are also presented. The lessons learned through this research are summarized and a discussion is made on interesting topics for future work in this domain. The prototype systems presented in this thesis have been made publicly available and are being used by various research groups worldwide in the context of 5G research.

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Chen, Xiang. "Coherent Radio Over Fiber Links for Broadband Wireless Access Networks". Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/36129.

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The ever-increasing demand for high date rate is beyond what is provided by the present wireless and wired access networks. Radio-over-fiber (RoF) technology which can provide broadband wireless access has been considered the most practical and efficient solution. In recent years, RoF with coherent detection has been shown to have better performance than that with direct detection in terms of receiver sensitivity and spectral efficiency. However, RoF with coherent detection suffers from phase noise introduced from both the transmitter and local oscillator (LO) laser sources, which degrades the performance significantly. This study is focused on coherent RoF links for broadband wireless access networks. The thesis consists of four parts. In the first part, a new approach to cancel the phase noise and the unstable frequency difference introduced from the transmitter and LO laser sources based on digital signal processing (DSP) in an RoF link with coherent detection is presented. The proposed schemes rival the RoF link with direct detection in complexity while maintaining a high receiver sensitivity. In addition, a high spectral efficiency coherent RoF link with phase noise cancellation, which can detect both intensity- and phase- modulated signals carried by the same optical carrier, is studied and demonstrated. In the second part, to achieve full-duplex transmission and increase the capacity of an RoF link, radio over wavelength division multiplexing passive optical network (WDM-PON) is studied. To eliminate the requirements of light sources and wavelength management at the optical network units (ONUs), which reduces the cost and eases the installation for a radio over WDM-PON system, a new approach to reuse the downstream wavelength at the ONU with coherent detection and DSP at the optical line terminal (OLT) is investigated. The performance in terms of error vector magnitude (EVM) and bit rate error (BER) is evaluated for both downlink and uplink. In the scheme, the coherent detection improves the receiver sensitivity for the uplink and compensate for the degraded data transmission performance due to the utilization of a wavelength-reused downstream optical signal. Furthermore, since the future internet traffic will become highly symmetric, a symmetrical radio over a colorless WDM passive optical network (PON) with wavelength reuse based on polarization multiplexing and coherent detection is proposed and studied. In the third part, a coherent RoF link based on optical single sideband with no optical carrier (OSSB) modulation with low-cost free-running laser sources for ultra-dense wavelength division multiplexing passive optical networks (UDWDM-PONs) is studied. In a UDWDM-RoF-PON, the channel spacing is very small, thus a WDM filter may not be able to de-multiplex the ultra-dense channels. However, through coherent detection, the channel separation can be realized by using electrical filters at the output of the coherent receiver. In addition, to utilize the spectrum in each channel more efficiently, OSSB modulation is employed. In the proposed scheme, an RoF signal based OSSB modulation with coherent detection is experimentally demonstrated. The channel spacing can be as narrow as 3 GHz. Finally, for 5th generation wireless systems (5G), multi-input and multi-output (MIMO) is a key technology which can multiple the capacity. To seamlessly integrate MIMO into RoF links, it is required that an RoF link can transmit multiple wireless signals over a single wavelength. To enable 4 × 4 MIMO, in the fourth part, an RoF link to transmit four wireless signals with an identical microwave center frequency without using frequency-division multiplexing (FDM) over a single optical wavelength based on optical independent sideband (OISB) modulation and optical orthogonal modulation incorporating optical coherent detection and digital signal processing (DSP) is studied. To increase the spectral efficiency further, a novel high spectral efficiency (20.62 bit/s/Hz) RoF link based on coherent detection and DSP with the spectral efficiency improved by employing both intensity and phase modulation and polarization multiplexing to transmit four microwave signals over a single optical carrier is investigated.

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Koudouridis, Georgios. "Study of Multi-Radio Transmission Diversity in Heterogeneous Access Networks". Licentiate thesis, KTH, Kommunikationsnät, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122723.

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With the advent of multi-radio access (MRA), an integration of differentradio access technologies (RATs) into a heterogeneous radio access network(RAN) becomes feasible. Such integration allows a user to be at any instantof time served by one or multiple radio accesses (RAs) concurrently, where anRA constitutes an independent radio resource, such as a carrier or a channel,implemented by a single RAT. It also allows a user´s service demands to bemapped onto the aggregated network resources in a transparent and efficientway. An approach for the realization of such multi-radio integrated environmentsis through a unifying generic link layer (GLL) that provides joint radiolink processing and enables communication between nodes and devices acrossdifferent radio accesses.Based on the requirements on multi-access, an architecture that supportsMRA is suggested and the functions of GLL that aims at integrating andutilising multiple RATs are defined. We explore the potential for performanceimprovements through novel extensions of the transmission diversityparadigm which builds on GLL functions that enable multi-radio access selection.Multi-radio transmission diversity (MRTD) is defined as the dynamicselection of radio access for the transmission of a user´s data and it can bethought of as consisting of a packet scheduler operating across multiple radiointerfaces. Different MRTD schemes may be envisaged through combinationsof access re-selection rate, transmission parallelism and transmission redundancy.The re-selection rate refers to the rate at which radio access selectionis performed. It may range from multiple IP packets to one single MACframe. Switched MRTD corresponds to an access selection scheme where auser transmits via one RA at a time, while parallel MRTD corresponds to ascheme where simultaneous transmissions over multiple RAs are scheduled.Finally, redundancy refers to the transmission of copies of the same data overmultiple RAs to increase the possibility of correct reception.The benefits of MRTD are investigated by simulation studies on two multiradiocase scenarios, based on generic RATs and on specific RATs respectively.In the RAT generic scenario, switched MRTD has been evaluated for networktopologies of collocated and non-collocated RAs consisting of macroand pico-cells. In the case of collocated RAs, spectral efficiency is increasedby exploiting diversity in multi-path fading while in non-collocated RAs, thespectral efficiency increase is due to diversity exploitation in both shadowingand multi-path fading. Simulation results show that switched MRTD is mostadvantageous when the RAs provide comparable throughputs. Furthermore,when combined with multi-radio ARQ, MRTD significantly reduces packetloss and packet transmission delays. This is also shown in the specific radioaccesssimulation scenario where a delay sensitive voice service is studied. Inaddition, switched MRTD provides comparable gains to parallel MRTD interms of average packet transmission delay and packet loss, while using lessradio resources. In all cases, it is concluded that maximum performance isconditioned on the reporting delays of the channel quality indicator (CQI).Reporting delays of CQI that are half the channel coherence time render sucha complex MRTD mechanism less effective.

QC 20130531

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Jabbar, A. I. A. "Simulation studies of protocols for random access packet radio networks". Thesis, University of Bradford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234244.

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Arbi, Abdelrahman. "Spectral and energy efficiency in cellular mobile radio access networks". Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/18518/.

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Abstract (sommario):

Driven by the widespread use of smartphones and the release of a wide range of online packet data services, an unprecedented growth in the mobile data usage has been observed over the last decade. Network operators recently realised that the traditional approach of deploying more macrocells could not cope with this continuous growth in mobile data traffic and if no actions are taken, the energy demand to run the networks, which are able to support such traffic volumes risks to become unmanageable. In this context, comprehensive investigations of different cellular network deployments, and various algorithms have been evaluated and compared against each other in this thesis, to determine the best deployment options which are able to deliver the required capacity at a minimum level of energy consumption. A new scalable base station power consumption model was proposed and a joint evaluation framework for the relative improvements in throughput, energy consumption,and energy efficiency is adopted to avoid the inherent ambiguity of using only the bit/J energy efficiency metric. This framework was applied to many cellular network cases studies including macro only, small cell only and heterogeneous networks to show that pure small cell deployments outperform the macro and heterogeneous networks in terms of the energy consumption even if the backhaul power consumption is included in the analysis. Interestingly, picocell only deployments can attain up to 3 times increase in the throughput and 2.27 times reduction in the energy consumed when compared with macro only RANs at high target capacities, while it offers 2 times more throughput and reduces the energy consumption by 12% when compared with the macro/pico HetNet deployments. Further investigations have focused on improving the macrocell RAN by adding more sectors and more antennas. Importantly, the results have shown that adding small cells to the macrocell RAN is more energy efficient than adding more sectors even if adaptive sectorisation techniques are employed. While dimensioning the network by using MIMO base stations results in less consumed energy than using SISO base stations. The impact of traffic offloading to small cell, sleep mode, and inter-cell interference coordination techniques on the throughput and energy consumption in dense heterogeneous network deployments have been investigated. Significant improvements in the throughput and energy efficiency in bit/J were observed. However, a decrease in the energy consumption is obtained only in heterogeneous networks with small cells deployed to service clusters of users. Finally, the same framework is used to evaluate the throughput and energy consumption of massive MIMO deployments to show the superiority of massive MIMOs versus macrocell RANs, small cell deployments and heterogeneous networks in terms of achieving the target capacity with a minimum level of energy consumption. 1.6 times reduction in the energy consumption is achieved by massive MIMOs when compared with picocell only RAN at the same target capacity and when the backhaul power consumption is included in the analysis.

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Chen, Si. "Vehicular Dynamic Spectrum Access: Using Cognitive Radio for Automobile Networks". Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-dissertations/418.

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Abstract (sommario):

"Vehicular Dynamic Spectrum Access (VDSA) combines the advantages of dynamic spectrum access to achieve higher spectrum efficiency and the special mobility pattern of vehicle fleets. This dissertation presents several noval contributions with respect to vehicular communications, especially vehicle-to-vehicle communications. Starting from a system engineering aspect, this dissertation will present several promising future directions for vehicle communications, taking into consideration both the theoretical and practical aspects of wireless communication deployment. This dissertation starts with presenting a feasibility analysis using queueing theory to model and estimate the performance of VDSA within a TV whitespace environment. The analytical tool uses spectrum measurement data and vehicle density to find upper bounds of several performance metrics for a VDSA scenario in TVWS. Then, a framework for optimizing VDSA via artificial intelligence and learning, as well as simulation testbeds that reflect realistic spectrum sharing scenarios between vehicle networks and heterogeneous wireless networks including wireless local area networks and wireless regional area networks. Detailed experimental results justify the testbed for emulating a mobile dynamic spectrum access environment composed of heterogeneous networks with four dimensional mutual interference. Vehicular cooperative communication is the other proposed technique that combines the cooperative communication technology and vehicle platooning, an emerging concept that is expected to both increase highway utilization and enhance both driver experience and safety. This dissertation will focus on the coexistence of multiple vehicle groups in shared spectrum, where intra-group cooperation and inter-group competition are investigated in the aspect of channel access. Finally, a testbed implementation VDSA is presented and a few applications are developed within a VDSA environment, demonstrating the feasibility and benefits of some features in a future transportation system."

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Hong, Xuemin. "Secondary mobile access via ultra-wideband and cognitive radio networks". Thesis, Heriot-Watt University, 2008. http://hdl.handle.net/10399/2196.

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Tesi sul tema "Radio access networks, RAN"

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