Energy Efficiency and Quality of Services in Virtualized Cloud Radio Access Network

Cloud Radio Access Network (C-RAN) is being widely studied for soft and green fifth generation of Long Term Evolution - Advanced (LTE-A). The recent technology advancement in network virtualization function (NFV) and software defined radio (SDR) has enabled virtualization of Baseband Units (BBU) and sharing of underlying general purpose processing (GPP) infrastructure. Also, new innovations in optical transport network (OTN) such as Dark Fiber provides low latency and high bandwidth channels that can support C-RAN for more than forty-kilometer radius. All these advancements make C-RAN feasible and practical. Several virtualization strategies and architectures are proposed for C-RAN and it has been established that C-RAN offers higher energy efficiency and better resource utilization than the current decentralized radio access network (D-RAN). This project studies proposed resource utilization strategy and device a method to calculate power utilization. Then proposes and analyzes a new resource management and virtual BBU placement strategy for C-RAN based on demand prediction and inter-BBU communication load. The new approach is compared with existing state of art strategies with same input scenarios and load. The trade-offs between energy efficiency and quality of services is discussed. The project concludes with comparison between different strategies based on complexity of the system, performance in terms of service availability and optimization efficiency in different scenarios

Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed

Cloud Radio Access Network (C-RAN) is emerging as a transformative architecture for the next generation of mobile cellular networks. In C-RAN, the Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in a centralized processing center. While the potential benefits of C-RAN have been studied extensively from the theoretical perspective, there are only a few works that address the system implementation issues and characterize the computational requirements of the virtualized BBU. In this paper, a programmable C-RAN testbed is presented where the BBU is virtualized using the OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment (UEs) are implemented using USRP boards. Extensive experiments have been performed in a FDD downlink LTE emulation system to characterize the performance and computing resource consumption of the BBU under various conditions. It is shown that the processing time and CPU utilization of the BBU increase with the channel resources and with the Modulation and Coding Scheme (MCS) index, and that the CPU utilization percentage can be well approximated as a linear increasing function of the maximum downlink data rate. These results provide real-world insights into the characteristics of the BBU in terms of computing resource and power consumption, which may serve as inputs for the design of efficient resource-provisioning and allocation strategies in C-RAN systems.Comment: In Proceedings of the IEEE International Conference on Autonomic Computing (ICAC), July 201

Fronthaul-Constrained Cloud Radio Access Networks: Insights and Challenges

As a promising paradigm for fifth generation (5G) wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between a baseband unit (BBU) and a remote radio head (RRH), requires high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained C-RANs, including system architectures and key techniques. In particular, key techniques for alleviating the impact of constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified.Comment: 5 Figures, accepted by IEEE Wireless Communications. arXiv admin note: text overlap with arXiv:1407.3855 by other author

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.Peer ReviewedPostprint (author's final draft

Soft-Defined Heterogeneous Vehicular Network: Architecture and Challenges

Heterogeneous Vehicular NETworks (HetVNETs) can meet various quality-of-service (QoS) requirements for intelligent transport system (ITS) services by integrating different access networks coherently. However, the current network architecture for HetVNET cannot efficiently deal with the increasing demands of rapidly changing network landscape. Thanks to the centralization and flexibility of the cloud radio access network (Cloud-RAN), soft-defined networking (SDN) can conveniently be applied to support the dynamic nature of future HetVNET functions and various applications while reducing the operating costs. In this paper, we first propose the multi-layer Cloud RAN architecture for implementing the new network, where the multi-domain resources can be exploited as needed for vehicle users. Then, the high-level design of soft-defined HetVNET is presented in detail. Finally, we briefly discuss key challenges and solutions for this new network, corroborating its feasibility in the emerging fifth-generation (5G) era

Will SDN be part of 5G?

For many, this is no longer a valid question and the case is considered settled with SDN/NFV (Software Defined Networking/Network Function Virtualization) providing the inevitable innovation enablers solving many outstanding management issues regarding 5G. However, given the monumental task of softwarization of radio access network (RAN) while 5G is just around the corner and some companies have started unveiling their 5G equipment already, the concern is very realistic that we may only see some point solutions involving SDN technology instead of a fully SDN-enabled RAN. This survey paper identifies all important obstacles in the way and looks at the state of the art of the relevant solutions. This survey is different from the previous surveys on SDN-based RAN as it focuses on the salient problems and discusses solutions proposed within and outside SDN literature. Our main focus is on fronthaul, backward compatibility, supposedly disruptive nature of SDN deployment, business cases and monetization of SDN related upgrades, latency of general purpose processors (GPP), and additional security vulnerabilities, softwarization brings along to the RAN. We have also provided a summary of the architectural developments in SDN-based RAN landscape as not all work can be covered under the focused issues. This paper provides a comprehensive survey on the state of the art of SDN-based RAN and clearly points out the gaps in the technology.Comment: 33 pages, 10 figure

Pilvipohjaisen radioliityntäverkon kustannusten mallintaminen

The rapid growth of mobile data traffic is challenging the current way of building and operating the current radio access network. Cloud-based radio access network is researched as a solution to provide the required capacity for rapidly growing traffic demand in more economical manner. Scope of this thesis is to evaluate the costs of different existing and future radio access network architectures depending on the given network and traffic scenario. This is done by creating a cost model based on expert interviews to solve the most economical solution for the given network in terms of total cost of ownership. The results show that the cloud-based radio access network’s cost benefits are dependent on the expected traffic growth. In the low traffic growth scenario, the cost benefits of cloud-based radio access network are questionable, but in the high traffic growth scenario clear cost benefits are achieved.Mobiilidataliikenteen nopea kasvu haastaa nykyisen tavan rakentaa ja hallinnoida tämän hetkisiä radioliityntäverkkoja. Pilvipohjaista radioliityntäverkkoa tutkitaan ratkaisuksi tarjota tarvittavaa verkkokapasiteettia entistä taloudellisemmin. Tämän opinnäytetyön tarkoituksena on arvioida nykyisten ja pilvipohjaisten radioliityntäverkkoarkkitehtuurien kustannuksia riippuen verkon rakenteesta ja liikenteestä. Tämä toteutetaan luomalla kustannusmalli, joka perustuu asiantuntijoiden haastatteluihin. Mallin avulla on mahdollista vertailla annetun verkon eri arkkitehtuurien kokonaiskustannuksia ja selvittää taloudellisin radioliityntäverkkoarkkitehtuuri verkolle. Mallinnuksen tulokset osoittavat, että pilvipohjaisen radioliityntäverkon taloudelliset hyödyt ovat riippuvaisia dataliikenteen kasvusta verkossa. Vähäisellä data-liikenteen kasvulla pilvipohjaisen radioliityntäverkon kustannusedut ovat kyseenalaiset, mutta suurella dataliikenteen kasvulla saadaan selviä säästöjä verrattuna nykyisiin arkkitehtuureihin