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Traffic on future fifth-generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time, and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle ultra-high-definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user’s perceived quality by adopting quality of experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modeling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the “health” of video application flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner. [ABSTRACT FROM AUTHOR]

To meet the challenging key performance indicators of the fifth generation (5G) system, the network infrastructure becomes more heterogeneous and complex. This will bring a high pressure on the reduction of OPEX and the improvement of the user experience. Hence, shifting today’s manual and semi-automatic network management into an autonomic and intelligent framework will play a vital role in the upcoming 5G system. Based on the cutting-edge technologies, such as Software-Defined Networking and Network Function Virtualization, a novel management framework upon the software-defined and Virtualized Network is proposed by EU H2020 SELFNET project. In the paper, the reference architecture of SELFNET, which is divided into Infrastructure Layer, Virtualized Network Layer, SON Control Layer, SON Autonomic Layer, NFV Orchestration and Management Layer, and Access Layer, will be presented. [ABSTRACT FROM AUTHOR]

Sharp increase of video traffic is expected to account for the majority of traffic in future 5G networks. This paper introduces the SELFNET 5G project and describes the video streaming use case that will be used to demonstrate the self-optimising capabilities of SELFNET’s autonomic network management framework. SELFNET’s framework will provide an advanced self-organizing network (SON) underpinned by seamless integration of Software Defined Networking (SDN), Network Function Virtualization (NFV), and network intelligence. The self-optimisation video streaming use case is going beyond traditional quality of service approaches to network management. A set of monitoring and analysis components will facilitate a user-oriented, quality of experience (QoE) and energy-aware approach. Firstly, novel SON-Sensors will monitor both traditional network state metrics and new video and energy related metrics. The combination of these low level metrics provides highly innovative health of network (HoN) composite metrics. HoN composite metrics are processed via autonomous decisions not only maintaining but also proactively optimising users’ video QoE while minimising the end-to-end energy consumption of the 5G network. This contribution provided a detailed technical overview of this ambitious use case. [ABSTRACT FROM AUTHOR]

The 5G infrastructure initiative in Europe 1 1 5G Infrastructure Public Private Partnership, [Online]. Available here: https://5g-ppp.eu/ has agreed a number of challenging key performance indicators (KPIs) to significantly enhance the user experience and support a number of use cases with very demanding requirements on the network infrastructure. At the same time there is high pressure on the reduction of the operational expenditure (OPEX). A contribution to meeting the KPIs and to reduce OPEX is to evolve the management of the network into a fully autonomic and intelligent framework. Based on advanced technologies, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), the EU H2020 project SELFNET ( https://selfnet-5g.eu/ ) is proposing an advanced network management framework to achieve these objectives. [ABSTRACT FROM AUTHOR]