Quality Of Experience Evaluation Research Articles

State-of-the-Practice in Evaluation of Quality of Experience in Real-Life Environments

Continuous monitoring of achieved level of service quality in packet-switched networks represents an activity of major importance for network and service providers. This is paramount for network resources provisioning which have to satisfy expectations of fickle customers. However, providing enough resources to specific user does not automatically increase their Quality of Experience (QoE), hence understanding of the relationship between these two is crucial in the network management process. Essentially, this requires subjective testing of service quality which is usually done in controlled environments such as laboratories. Nevertheless, the most accurate subjective evaluation of QoE includes real-life experiments in the environments where the services are actually used. Therefore, the aim of this paper is to provide a review of the current state-of-the-practice in evaluating QoE in real-life environments.

A New Method of Objective Speech Quality Assessment in Communication System

On the Quality of Experience (QoE) evaluation of communication system, the quality of speech is an important factor to evaluate the system. Perceptual evaluation of speech quality (PESQ) is a well known objective speech quality assessment method for the voice QoE evaluation. It is proposed by International Telecommunication Union (ITU) and is formed as the ITU-T P.862 Recommendations. PESQ applies Bark-scale frequency to evaluate the Mean Opinion Score (MOS) for speech quality of voice communication system. But through our research, we find that the PESQ algorithm has limitations for evaluating speech quality. In order to change these limitations, this paper proposes a new objective evaluation algorithm by using ERB-scale to take the place of Bark-scale frequency. The ERB-scale is more accurate than Bark-scale to describe the frequency selectivity of the human ear when frequency at lower domain. We call the new algorithm as NPESQ (New Perceptual Evaluation of Speech Quality) whose accuracy is tested in our experiment. Through experimental comparison against PESQ and NPESQ, the results demonstrate the improvement of the NPESQ. Therefore, it can be concluded that the new algorithm can improve the accuracy of the measurement.

Towards a QoE-Driven Resource Control in LTE and LTE-A Networks

We propose a novel architecture for providing quality of experience (QoE) awareness to mobile operator networks. In particular, we describe a possible architecture for QoE-driven resource control for long-term evolution (LTE) and LTE-advanced networks, including a selection of KPIs to be monitored in different network elements. We also provide a description and numerical results of the QoE evaluation process for different data services as well as potential use cases that would benefit from the rollout of the proposed framework.

Quality of experience for HTTP adaptive streaming services

The growing consumer demand for mobile video services is one of the key drivers of the evolution of new wireless multimedia solutions requiring exploration of new ways to optimize future wireless networks for video services towards delivering enhanced quality of experience (QoE). One of these key video enhancing solutions is HTTP adaptive streaming (HAS), which has recently been spreading as a form of Internet video delivery and is expected to be deployed more broadly over the next few years. As a relatively new technology in comparison with traditional push-based adaptive streaming techniques, deployment of HAS presents new challenges and opportunities for content developers, service providers, network operators and device manufacturers. One of these important challenges is developing evaluation methodologies and performance metrics to accurately assess user QoE for HAS services, and effectively utilizing these metrics for service provisioning and optimizing network adaptation. In that vein, this article provides an overview of HAS concepts, and reviews the recently standardized QoE metrics and reporting framework in 3GPP. Furthermore, we present an end-to-end QoE evaluation study on HAS conducted over 3GPP LTE networks and conclude with a discussion of future challenges and opportunities in QoE optimization for HAS services.

Measurement-based peer selection for P2P-IPTV services in campus networks

P2P-based IPTV has been a gradual hot topic both for the academic institutions and service providers, which offers residential and commercial users digital television services through IP protocol and media sharing among peers at low cost. A rational peer selection algorithm plays an essential role on offering reliable media streaming transmission and excellent user experience. Meanwhile, convenient and effective quality of experience (QoE) assessment mechanism is not only an important evaluation index for IPTV service providers, but also can supply high-efficient performance feedback for them, especially under a limited network resource environment. Our contributions in this paper are three-fold: 1) we confirm the key parameters which affect QoE among P2P live application according to our 6-month trace, and establish a rational peer selection algorithm by virtue of the parameters above; 2) we set up a novel and passive model for QoE assessment representation; 3) during the popularization in campus networks, we approve the effectiveness of our new QoE evaluation method and the improvement of users' video quality caused by peer selection strategy. Whether or not, we hope our work can supply reliable references for IPTV service providers, moreover, actual improvement for future IPTV deployment.

Quality of experience issues in multimedia provision

Currently, the success of providing novel multimedia services over wired/wireless networks depends on how good the quality of the service is and whether it meets an end user’s expectations. Thus, it is critical for equipment manufacturers, network operators and service providers to be able to assess, predict and possibly control the end-to-end perceptual multimedia (e.g., voice and video) quality for commercial and technical reasons. The Quality of Service (QoS) perceived as user satisfaction has received through past years some efforts from the research community, introducing the concept of the Quality of Experience (QoE). The evaluation of the QoE will provide an end user with a range of potential choices, covering the possibilities of low, medium, or high quality levels. This QoE evaluation will also give service providers and network operators the capability to minimize the storage and network resources by allocating only the ones that are necessary to maintain a specific level of user satisfaction. This special issue focuses on novel accurate, efficient and robust QoE models for multimedia services, including both VoIP and video services, novel QoE-driven cross-layer architectures, including performance evaluation, traffic man-

Linking Users' Subjective QoE Evaluation to Signal Strength in an IEEE 802.11b/g Wireless LAN Environment

Although the literature on Quality of Experience (QoE) has boomed over the last few years, only a limited number of studies have focused on the relation between objective technical parameters and subjective user-centric indicators of QoE. Building on an overview of the related literature, this paper introduces the use of a software monitoring tool as part of an interdisciplinary approach to QoE measurement. In the presented study, a panel of test users evaluated a mobile web-browsing application (i.e., Wapedia) on a PDA in an IEEE 802.11b/g Wireless LAN environment by rating a number of key QoE dimensions on the device immediately after usage. This subjective evaluation was linked to the signal strength, monitored during PDA usage at four different locations in the test environment. The aim of this study is to assess and model the relation between the subjective evaluation of QoE and the (objective) signal strength in order to achieve future QoE optimization.