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Schmidt, Robert. "Slicing in heterogeneous software-defined radio access networks". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS525.
Pełny tekst źródła5G 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
Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043/document.
Pełny tekst źródłaCloud 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
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/.
Pełny tekst źródłaThainesh, Joseph S. "Radio access network (RAN) signalling architecture for dense mobile network". Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/811126/.
Pełny tekst źródłaDuan, 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.
Pełny tekst źródłaCentralized/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
Sharara, Mahdi. "Resource Allocation in Future Radio Access Networks". Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG024.
Pełny tekst źródłaThis 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
Rabia, Tarek. "Virtualisation des fonctions d'un Cloud Radio Access Network(C-RAN)". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS009/document.
Pełny tekst źródłaOver 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
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.
Pełny tekst źródłaOver 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
Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms". Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043.
Pełny tekst źródłaCloud 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
Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.
Pełny tekst źródłaNetwork 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
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.
Pełny tekst źródłaCloud 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
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.
Pełny tekst źródłaOver 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
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.
Pełny tekst źródłaA 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
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 %.
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.
Pełny tekst źródłaNetwork 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
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.
Pełny tekst źródłaCosta, 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.
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/.
Pełny tekst źródłaAlimi, 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.
Pełny tekst źródłaA 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.
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.
Pełny tekst źródłaCloud 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
Celebi, Hasari. "Location awareness in cognitive radio networks". [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002562.
Pełny tekst źródłaKalalas, Charalampos. "Cellular networks for smart grid communication". Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/620760.
Pełny tekst źródłaLas 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
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.
Pełny tekst źródła5G 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
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.
Pełny tekst źródłaOlsson, Joel, i Junior Asante. "5G Simulation Framework". Thesis, Linköpings universitet, Kommunikationssystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-149484.
Pełny tekst źródłaSalhab, Nazih. "Resource provisioning and dynamic optimization of Network Slices in an SDN/NFV environment". Thesis, Paris Est, 2020. http://www.theses.fr/2020PESC2019.
Pełny tekst źródłaTo 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
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.
Pełny tekst źródłaMontenegro, Manuel David Fonseca. "Capacity forecasting for radio access networks". Master's thesis, Universidade de Aveiro, 2014. http://hdl.handle.net/10773/15782.
Pełny tekst źródłaThe 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.
Clancy, Thomas Charles. "Dynamic spectrum access in cognitive radio networks". College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3511.
Pełny tekst źródłaThesis 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.
Bian, Kaigui. "Medium Access Control in Cognitive Radio Networks". Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/37591.
Pełny tekst źródłaPh. D.
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.
Pełny tekst źródłaUnder 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.
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.
Pełny tekst źródłaPiao, Guihua. "Radio resource management for integrated services in multi-radio access networks". Kassel Kassel Univ. Press, 2007. http://d-nb.info/986595012/34.
Pełny tekst źródłaAbbood, 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.
Pełny tekst źródłaSubramani, 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.
Pełny tekst źródłaEl, Helou Melhem. "Radio Access Technology Selection in Heterogeneous Wireless Networks". Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S086/document.
Pełny tekst źródłaTo 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
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.
Pełny tekst źródłaAl, Noor Mazin. "Green radio communication networks applying radio-over-fibre technology for wireless access". Thesis, Middlesex University, 2012. http://eprints.mdx.ac.uk/8995/.
Pełny tekst źródłaTuryagyenda, Charles. "Energy efficient radio resource management for future mobile cellular radio access networks". Thesis, University of Sheffield, 2014. http://etheses.whiterose.ac.uk/6247/.
Pełny tekst źródłaBolívar, Díaz Nicolás. "Medium access control messaging scheme for cognitive radio networks". Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/84098.
Pełny tekst źródłaHerlich, Matthias [Verfasser]. "Reducing energy consumption of radio access networks / Matthias Herlich". Paderborn : Universitätsbibliothek, 2014. http://d-nb.info/1048130053/34.
Pełny tekst źródłaBoulos, Karen. "BBU-RRH Association Optimization in Cloud-Radio Access Networks". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS209/document.
Pełny tekst źródłaThe 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
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.
Pełny tekst źródłaFoukas, Xenofon. "Towards a programmable and virtualized mobile radio access network architecture". Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31406.
Pełny tekst źródłaChen, 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.
Pełny tekst źródłaKoudouridis, 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.
Pełny tekst źródłaQC 20130531
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.
Pełny tekst źródłaArbi, Abdelrahman. "Spectral and energy efficiency in cellular mobile radio access networks". Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/18518/.
Pełny tekst źródłaChen, Si. "Vehicular Dynamic Spectrum Access: Using Cognitive Radio for Automobile Networks". Digital WPI, 2012. https://digitalcommons.wpi.edu/etd-dissertations/418.
Pełny tekst źródłaHong, 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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