A Survey on QoE-oriented Wireless Resources Scheduling <s> I. INTRODUCTION <s> Oral speech intelligibility tests were conducted with, and without, supplementary visual observation of the speaker's facial and lip movements. The difference between these two conditions was examined as a function of the speech‐to‐noise ratio and of the size of the vocabulary under test. The visual contribution to oral speech intelligibility (relative to its possible contribution) is, to a first approximation, independent of the speech‐to‐noise ratio under test. However, since there is a much greater opportunity for the visual contribution at low speech‐to‐noise ratios, its absolute contribution can be exploited most profitably under these conditions. <s> BIB001 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> I. INTRODUCTION <s> We propose a cross-layer optimization strategy that jointly optimizes the application layer, the data-link layer, and the physical layer of a wireless protocol stack using an application-oriented objective function. The cross-layer optimization framework provides efficient allocation of wireless network resources across multiple types of applications run by different users to maximize network resource usage and user perceived quality of service. We define a novel optimization scheme based on the mean opinion score (MOS) as the unifying metric over different application classes. Our experiments, applied to scenarios where users simultaneously run three types of applications, namely voice communication, streaming video and file download, confirm that MOS-based optimization leads to significant improvement in terms of user perceived quality when compared to conventional throughput-based optimization. <s> BIB002 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> I. INTRODUCTION <s> This paper proposes a Quality of Experience (QoE) based cross-layer design (CLD) framework for High Speed Downlink Packet Access (HSDPA). The proposed scheme aims at maximizing the user satisfaction by taking advantage of the link adaptation mechanism of HSDPA and the rate adaptation capability of multimedia applications. The main contributions of the paper are as follows. First, we describe the multiuser rate region of HSDPA by constructing a long-term radio link layer model. Next, we formulate multimedia QoE by constructing long-term utility functions, describe the multiuser utility space and derive its properties. We show analytically that the maximization of the sum of utility (max-MOS) can be efficiently solved by a fast greedy algorithm which searches only through the boundary of the utility space. We investigate two alternatives to the max-MOS approach, which introduce additional fairness in the system. We compare our proposed QoE-based cross layer optimization schemes to a system that is configured to maximize the overall throughput. For the sake of completeness, we also compare our approaches to a non-optimized HSDPA system. The performance comparison is made by simulation using a software implementation of an actually deployed HSDPA system. Results show that our QoE-based approach leads to significantly improved user perceived quality compared to the other approaches. <s> BIB003 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> I. INTRODUCTION <s> The increase in multimedia content on the Internet has created a renewed interest in quality assessment. There is however a main difference from the traditional quality assessment approaches, as now, the focus relies on the user perceived quality, opposed to the network centered approach classically proposed. In this paper we overview the most relevant challenges to perform Quality of Experience (QoE) assessment in IP networks and highlight the particular considerations necessary when compared to alternative mechanisms, already deployed, such as Quality of Service (QoS). To assist on the handling of such challenges we first discuss the different approaches to Quality of Experience assessment along with the most relevant QoE metrics, and then we discuss how they are used to provide objective results about user satisfaction. <s> BIB004 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> I. INTRODUCTION <s> This White Paper is a contribution of the European Network on Quality of Experience in Multimedia Systems and Services, Qualinet (COST Action IC 1003, see www.qualinet.eu), to the scientific discussion about the term "Quality of Experience" (QoE) and its underlying concepts. It resulted from the need to agree on a working definition for this term which facilitates the communication of ideas within a multidisciplinary group, where a joint interest around multimedia communication systems exists, however approached from different perspectives. Thus, the concepts and ideas cited in this paper mainly refer to the Quality of Experience of multimedia communication systems, but may be helpful also for other areas where QoE is an issue. The Network of Excellence (NoE) Qualinet aims at extending the notion of network-centric Quality of Service (QoS) in multimedia systems, by relying on the concept of Quality of Experience (QoE). The main scientific objective is the development of methodologies for subjective and objective quality metrics taking into account current and new trends in multimedia communication systems as witnessed by the appearance of new types of content and interactions. A substantial scientific impact on fragmented efforts carried out in this field will be achieved by coordinating the research of European experts under the catalytic COST umbrella. The White Paper has been compiled on the basis of a first open call for ideas which was launched for the February 2012 Qualinet Meeting held in Prague, Czech Republic. The ideas were presented as short statements during that meeting, reflecting the ideas of the persons listed under the headline "Contributors" in the previous section. During the Prague meeting, the ideas have been further discussed and consolidated in the form of a general structure of the present document. An open call for authors was issued at that meeting, to which the persons listed as "Authors" in the previous section have announced their willingness to contribute in the preparation of individual sections. For each section, a coordinating author has been assigned which coordinated the writing of that section, and which is underlined in the author list preceding each section. The individual sections were then integrated and aligned by an editing group (listed as "Editors" in the previous section), and the entire document was iterated with the entire group of authors. Furthermore, the draft text was discussed with the participants of the Dagstuhl Seminar 12181 "Quality of Experience: From User Perception to Instrumental Metrics" which was held in Schlos Dagstuhl, Germany, May 1-4 2012, and a number of changes were proposed, resulting in the present document. As a result of the writing process and the large number of contributors, authors and editors, the document will not reflect the opinion of each individual person at all points. Still, we hope that it is found to be useful for everybody working in the field of Quality of Experience of multimedia communication systems, and most probably also beyond that field. <s> BIB005
Wireless resources scheduling is the process of allocating physical radio resources among users and of determining the order for serving the users (also known as prioritizing). The goal is to fulfill some service requirements such as fairness (including avoiding greedy users, where one user consumes overmuch system resources) or congestion, along with other constrains like delay or packet loss rate. Since a wireless channel has a time-varying behavior in comparison to wired networks, more complex scheduling schemes are required for the former case. However, since the scheduling process allows to save resources, wireless schedulers play an important role in efficient management of scarce radio resources. In order to improve the service level, wireless systems have adopted in the past years schedulers that provide Quality of Service (QoS), i.e., the ability of the network to provide a service with an assured service level. Since QoS is usually measured in terms of delay, packet loss rate, jitter or throughput, it can be regarded as a network-centric characterization of the service quality. Despite the popularity of QoS-oriented schedulers design, the final judge of the received service quality still remains the end-user, i.e. humans. In literature, some pioneering authors BIB002 - BIB003 showed that the application of a subjective-based approach may lead to significant improvements on user perceived quality, i.e., Quality of Experience (QoE), compared to I. Sousa, M. P. Queluz and A. Rodrigues are with Instituto de Telecomunicações, Portugal. Contact email: ivo.sousa@lx.it.pt network-centric approaches, such as throughput maximization. Hence, a shift from QoS-to QoE-oriented mechanisms design has been observed in recent years. QoE is a concept that tries to cover everything that a user experiences when dealing with multimedia services and systems BIB005 ; it is not only limited to the use of a multimedia system or service, but also takes into account the information content. Therefore, QoE can be regarded as a user-centric characterization of the service quality. As the number of dimensions involved in the users' subjective evaluation is immense, QoE-based techniques are becoming progressively more complex and sophisticated than the previous QoS-oriented algorithms. Schedulers that make use of QoE features consequently try to directly reflect the subjective experiences of the users, resulting that their resource allocation and prioritization techniques are more efficient in terms of satisfying the users than the schedulers that adopt conventional metrics. This efficiency can be achieved by avoiding wasting resources in situations where there is little or even no effect on the user experience. Therefore, QoEoriented wireless resources schedulers are the ones that aim at fulfilling the mobile system users expectations: watch/listen what I want, when I want and where I want. This survey paper provides a comprehensive overview of the key facets of QoE-oriented wireless resources scheduling. The first two sections that follow this introduction provide a contextualization regarding what is QoE and how traditional schedulers work: in Section II, the factors that influence the QoE in multimedia services over communication systems are presented, along with some QoE estimation methods; Section III illustrates some scheduling algorithms, ranging from the simplest ones to QoS-aware approaches, followed by the introduction of QoS-QoE mapping strategies and utilitybased optimization. Section IV provides the main contribution of this survey, namely the presentation of recent research directions regarding QoE-oriented wireless resources schedulingstate-of-the-art QoE-aware scheduling methods are discussed and classified based on the adjustments required at the enduser devices in order to implement the different scheduling strategies on wireless systems. Section V concludes the paper. This survey serves as a reference for those who want to implement QoE-aware wireless resource schedulers and also aims to be a value contribution for those who want to perform research within this topic. II. UNDERSTANDING QOE According to the Qualinet white paper BIB005 , QoE is defined as "the degree of delight or annoyance of the user of an appliarXiv:1705.07839v1 [cs.NI] 22 May 2017 Fig. 1 . Example of quality assessment operations in video delivery BIB004 . cation or service. It results from the fulfillment of his or her expectations with respect to the utility and / or enjoyment of the application or service in the light of the user's personality and current state". In the context of communication systems, QoE can then be influenced by factors such as service, content, network, device, application and context of use. For instance, the authors of BIB001 showed that if supplementary visual observation of the speaker's facial and lip movements are also utilized in addition to the oral speech, humans can tolerate higher noise interference levels than if no visual factors were utilized. Hence, QoE assessment operations are performed in a broader domain when compared to QoS measurements -cf. Fig. 1 . The following subsections provide some details about the factors that influence the user experience, as well as some QoE estimation methods regarding multimedia services over communication systems.