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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]

Video and multimedia streaming services continue to grow in popularity and are rapidly becoming the largest consumers of network capacity in both fixed and mobile networks. In this article we discuss the latest advances in video compression technology and demonstrate their potential to improve service quality for consumers while reducing bandwidth consumption. Our study focuses on the adaptation of scalable, highly compressed video streams to meet the resource constraints of a wide range of portable consumer devices in mobile environments. Exploring SHVC, the scalable extension to the recently standardized High Efficiency Video Coding scheme, we show the bandwidth savings that can be achieved over current encoding schemes and highlight the challenges that lie ahead in realizing a deployable and user-centric system. [ABSTRACT FROM PUBLISHER]

Users of modern portable consumer devices (smartphones, tablets etc.) expect ubiquitous delivery of high quality services, which fully utilise the capabilities of their devices. Video streaming is one of the most widely used yet challenging services for operators to deliver with assured service levels. This challenge is more apparent in wireless networks where bandwidth constraints and packet loss are common. The lower bandwidth requirements of High Efficiency Video Coding (HEVC) provide the potential to enable service providers to deliver high quality video streams in low-bandwidth networks; however, packet loss may result in greater damage in perceived quality given the higher compression ratio. This work considers the delivery of HEVC encoded video streams in impaired network environments and quantifies the effects of network impairment on HEVC video streaming from the perspective of the end user. HEVC encoded streams were transmitted over a test network with both wired and wireless segments that had imperfect communication channels subject to packet loss. Two different error concealment methods were employed to mitigate packet loss and overcome reference decoder robustness issues. The perceptual quality of received video was subjectively assessed by a panel of viewers. Existing subjective studies of HEVC quality have not considered the implications of network impairments. Analysis of results has quantified the effects of packet loss in HEVC on perceptual quality and provided valuable insight into the relative importance of the main factors observed to influence user perception in HEVC streaming. The outputs from this study show the relative importance and relationship between those factors that affect human perception of quality in impaired HEVC encoded video streams. The subjective analysis is supported by comparison with commonly used objective quality measurement techniques. Outputs from this work may be used in the development of quality of experience (QoE) oriented streaming applications for HEVC in loss prone networks. [ABSTRACT FROM PUBLISHER]

High Efficiency Video Coding (HEVC) is the next generation video compression standard currently under development within the ITU-T/ISO sponsored Joint Collaborative Team on Video Coding (JCT-VC). The standardization, and eventual adoption, of HEVC will contribute significantly to the future development of many consumer devices. Areas such as broadcast television, multimedia streaming, mobile communications and multimedia/video content storage will all be impacted by implementation of the emerging HEVC standard. Up to this point in time the research focus of HEVC has been on improvements to video compression efficiency and little work has been conducted into streaming of HEVC. In this work we consider the practical barriers to HEVC streaming in realistic environments and propose HEVStream, a streaming and evaluation framework for HEVC encoded content. Our framework fills the current gap in enabling networked HEVC visual applications and permits the implementation, testing and evaluation of HEVC encoded video streaming under a range of packet loss, bandwidth restriction and network delay scenarios in a realistic testbed environment. We provide a basic error concealment method for HEVC to overcome limitations within the decoder and an RTP packetisation format for HEVC Network Abstraction Layer (NAL) units. Comprehensive results of HEVC streaming experiments under various network circumstances are reported. These results provide an insight into the reduction in picture quality, measured as peak signal to noise ratio (PSNR), that can be expected under a wide range of network constraint and packet loss conditions. We report an average loss of 3.61dB when a bandwidth reduction of 10% is applied. We believe that this work will be amongst the first to report on successful design and implementation of HEVC network applications, and evaluation of the effects of network constraints or limitations on the quality of HEVC encoded video streams. [ABSTRACT FROM PUBLISHER]

The pace at which powerful portable wireless consumer devices such as smartphones and tablets have been adopted has not been matched by the ability of mobile networks to deliver high-quality video streams consistently to such nomadic users. In this work, we propose CMT-NEMO, a novel concurrent multipath transfer scheme for the delivery of scalable video content to users in multihomed mobile networks such as those expected to be found in public transport scenarios. Recent research in this context has shown that the single largest limiting factor for perceived video quality is the overhead introduced by path switching operations in multihomed mobile networks. CMT-NEMO eliminates the need for path switching and, by removing the associated path switching latency, provides a substantial performance improvement across a wide range of bandwidths and test sequences. An average Y-PSNR improvement of 5.9 dB is achieved when compared with previously proposed schemes. [ABSTRACT FROM AUTHOR]

Consumer demand for portable wireless devices such as smartphones or tablets capable of receiving high quality video content has risen sharply in recent years. This paper considers the real-time delivery of streamed H.264 Scalable Video Coding (SVC) content to users of such devices within mobile networks (e.g. situations where they are part of a group moving together on a bus or a train). We propose a novel scheme for the multipath delivery of H.264 SVC content to users in multihomed mobile networks .By implementing our scheme on a realistic testbed, we show that it offers a significant improvement in received video quality over previously proposed alternative schemes1. [ABSTRACT FROM AUTHOR]