This paper analyzes current standardization situation of 5G and the role network softwarization plays in order to address the challenges the new generation of mobile networks must face. This paper surveys recent documentation from the main stakeholders to pick out the use cases, scenarios and emerging vertical sectors that will be enabled by 5G technologies, and to identify future high-level service requirements. Driven by those service requirements 5G systems will support diverse radio access technology scenarios, meet end-to-end user experienced requirements and provide capability of flexible network deployment and efficient operations. Then, based on the identified requirements, the paper overviews the main 5G technology trends and design principles to address them. In particular, the paper emphasizes the role played by three main technologies, namely SDN, NFV and MEC, and analyzes the main open issues of these technologies in relation to 5G.
Abstract: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 cloudenabled 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.
This paper presents a novel architecture for optimizing the HTTP-based multimedia delivery in multi-user mobile networks. This proposal combines the usual client-driven dynamic adaptation scheme DASH-3GPP with network-assisted adaptation capabilities, in order to maximize the overall Quality of Experience. The foundation of this combined adaptation scheme is based on two state of the art technologies. On one hand, adaptive HTTP streaming with multi-layer encoding allows efficient media delivery and improves the experienced media quality in highly dynamic channels. Additionally, it enables the possibility to implement network-level adaptations for better coping with multi-user scenarios. On the other hand, mobile edge computing facilitates the deployment of mobile services close to the user. This approach brings new possibilities in modern and future mobile networks, such as close to zero delays and awareness of the radio status. The proposal in this paper introduces a novel element, denoted as Mobile Edge-DASH Adaptation Function, which combines all these advantages to support efficient media delivery in mobile multi-user scenarios. Furthermore, we evaluate the performance enhancements of this content-and user contextaware scheme through simulations of a mobile multimedia scenario.Mobile multimedia traffic has been experiencing a dramatic increase in the last years, dominated by the explosion of media delivery through Dynamic Adaptive Streaming over HTTP (DASH). This approach, standardized by MPEG as ISO/IEC CD 23009-1 and adopted by 3GPP as 3GP-DASH, splits media contents in short media segments. These chunks can be made available at different quality versions, allowing users to switch between different quality representations from one interval to the following one. In this way, multimedia services are endowed with client-driven dynamic adaptation capabilities, which is a crucial feature for reacting to variable channel conditions. In AVC-based DASH (DASH-AVC), media content is split in K media segments (AVC k in Fig. 1a) available at N different representations (AVC n in Fig. 1a), corresponding to different quality levels. Each combination of media segment and quality representation is described as a unique HTTP object in a Media Presentation Description (MPD) file, and can be independently retrieved through HTTP GET requests. Therefore, at each time slot, the user device requests a unique video representation.SVC-based DASH (DASH-SVC) allows more flexible delivery schemes since different layers (base layer and enhancement layers) are split into different HTTP objects containing additive information. Each HTTP object in the MPD file represents a quality layer of a video segment. When client devices select the most suitable media representation (SVC 1 -SVC n objects in Fig. 1b) for a media segment (SVC k in Fig. 1b), the different layers are transmitted over the network as standalone HTTP transactions.Dynamic content delivery reacts to the specific network conditions based on either quick client-dri...
5G envisages a “hyperconnected society” where trillions of diverse entities could communicate with each other anywhere and at any time, some of which will demand extremely challenging performance requirements such as submillisecond low latency. Mobile Edge Computing (MEC) concept where application computing resources are deployed at the edge of the mobile network in proximity of an end user is a promising solution to improve quality of online experience. To make MEC more flexible and cost-effective Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN) technologies are widely adopted. It leads to significant CAPEX and OPEX reduction with the help of a joint radio-cloud management and orchestration logic. In this paper we discuss and develop a reference architecture for the orchestration and management of the MEC ecosystem. Along with the lifecycle management flows of MEC services, indicating the interactions among the functional modules inside the Orchestrator and with external elements, QoS management with a focus on the channel state information technique is presented.
The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS) networks. In order to characterize the Quality of Service (QoS) level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS) and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS). The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.
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