A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> A balanced strategy for OFDMA radio resource allocation based on game theory concepts is presented. Its main novelty with respect to state-of-the-art methods is that resource allocation is based on application-oriented Mean Opinion Score (MOS), rather than the aggregate system data rate. Thus, users' data flows cooperate in a proactive way in order to jointly maximize the Quality of Experience (QoE). Experimental results show that the MOS achievable by the proposed resource allocation strategy is higher than the one provided by uncoordinated strategies based on water-filling and cooperative strategies based on pure data rate maximization. <s> BIB001 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> In this paper, we propose a cross-layer design scheme for optimizing resource allocation of video applications based on Quality of Experience (QoE) prediction. A novel mapping model between Peak Signal-to-Noise Ratio (PSNR) and Mean Opinion Score (MOS) based on hyperbolic tangent function is presented to reflect the relation between objective parameters and subjective perceived quality. On the basis of this model, we propose a QoE prediction function and utilize the Particle Swarm Optimization (PSO) method to solve the resource allocation problem. Simulation results show that our QoE-based cross-layer design scheme leads to significant improvements in terms of maximizing user-perceived quality as well as maintaining fairness among users. <s> BIB002 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> Quality of Experience (QoE) has taken a center stage in the performance evaluation of multimedia delivery technologies. The Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) system is the latest generation of wireless cellular technology expected to deliver higher data rates and meet the burgeoning data demand. With the projected dominant share of video services in mobile traffic, providing satisfactory QoE to video users is a key objective for LTE system design. In this paper, we present a QoE-based evaluation methodology to assess the LTE system video capacity in terms of the number of unicast video consumers that can be simultaneously supported for a given target QoE. We define and use the notion of rebuffering outage capacity to quantify the video service capacity. Our evaluation further incorporates adaptive streaming, a promising technology for video delivery over wireless, and presents its consequent QoE-capacity tradeoff. The impact of QoE-based outage criteria is also investigated on the downlink video capacity. Finally, we propose a QoE-aware radio resource management (RRM) framework which allows the network operator to further enhance the video capacity. Our results demonstrate that there is a significant potential to optimize video capacity through QoE awareness both at the application level and radio access network (RAN) level. <s> BIB003 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> With the introduction of 4th generation mobile networks, applications such as high-quality video streaming to the end user becomes possible. However, the expected demand for such services outpaces the capacity increase of the networks. Since there is mostly a capacity bottleneck in the air interface between a base station and user equipment, one of the main challenges for radio resource management is therefore to enforce precise quality guarantees for users with high expectations on service quality. We consider, in this paper, an OFDMA access network with YouTube users, and address the challenge of improving the quality of experience (QoE) of a dedicated user by utilizing the buffered playtime of a YouTube video for scheduling. The advantage of this approach is that scheduling is done according to the instantaneous throughput requirement of the end user application, and not by the network by maintaining average quality-of-service (QoS) parameters. The paper describes the concept and provides a simulative evaluation of the approach in an LTE network to demonstrate the benefits. <s> BIB004 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> This research studies Dynamic Adaptive Streaming over HTTP (DASH) in cellular broadband access networks (e.g. HSDPA, HSPA+, LTE). We propose a wireless DASH (WiDASH) proxy to enhance the Quality-of-Experience (QoE) of wireless DASH. WiDASH proxy locates at the edge between Internet and wireless core networks. Different from conventional DASH, whose rate adaptation logics are either implemented locally in the user equipment or in the DASH server, WiDASH proxy is in charge of video adaptation, which makes it feasible to perform global optimization over multiple concurrent DASH flows. WiDASH proxy improves DASH QoE by three novel technologies. The first one is architecture level innovation. WiDASH simultaneously explores the potential of both split TCP and parallel TCP. It splits the original TCP connection from DASH server to a wireless user into one wired TCP and multiple wireless TCPs. This approach is able to increase video streams' average throughput without sacrificing inter user fairness. Second, WiDASH proxy employs video quality aware dynamic prioritization. Low bit rate video streams are entitled with high priority to guarantee minimum QoE for users with bad wireless channel quality. A video stream's priority is gradually dropped to normal state with the growth of its bit rate so that inter flow fairness between video streams and background best effort flows are still maintained. Third, we design a multiple-input multiple-output adaptive optimal controller, based on adaptive control theory. This rate controller minimizes a quadratic cost function which is defined as the weighted sum of multiple concurrent DASH videos' distortion, bit rate variation, and playback jitter. The solution of the optimization problem implicitly coordinates multiple DASH streams to improve overall streaming QoE. Simulation results verify that WiDASH proxy is able to improve QoE by providing smoother video streams with higher average visual quality for wireless HTTP video streaming. <s> BIB005 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> We consider the problem of scheduling multiple adaptive streaming video users sharing a time-varying wireless channel such as in modern 3GPP Long Term Evolution (LTE) systems. HTTP Adaptive Streaming (HAS) framework is used by the video users for video rate adaptation. HAS is a client driven video delivery solution that has been gaining popularity due to its inherent advantages over other existing solutions. Quality of Experience (QoE) has become the prime performance criterion for media delivery technologies and wireless resource management is a critical part in providing a target QoE for video delivery over wireless systems. We propose a novel cross-layer Video-QoE aware optimization framework for wireless resource allocation that constraints rebuffering probability for adaptive streaming users. We propose a Re-buffering Aware Gradient Algorithm (RAGA) to solve this optimization problem. RAGA relies on simple periodic feedback of media buffer levels by adaptive streaming clients. Our simulation results on an LTE system level simulator demonstrate significant reduction in re-buffering percentage using RAGA without compromising video quality. <s> BIB006 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> We consider the problem of optimizing video de- livery for a network supporting video clients streaming stored video. Specifically, we consider the joint optimization of network resource allocation and video quality adaptation. Our objective is to fairly maximize video clients' Quality of Experience (QoE) re- alizing tradeoffs among the mean quality, temporal variability in quality, and fairness, incorporating user preferences on rebuffer- ing and cost of video delivery. We present a simple asymptotically optimal online algorithm, NOVA, to solve the problem. NOVA is asynchronous, and using minimal communication, distributes the tasks of resource allocation to network controller, and quality adaptation to respective video clients. Video quality adaptation in NOVA is also optimal for standalone video clients, and is well suited for use in the DASH framework. Further, NOVA can be extended for use with more general QoE models, networks shared with other traffic loads and networks using fixed/legacy resource allocation. <s> BIB007 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> Managing the Quality-of-Experience (QoE) of video streaming for wireless clients is becoming increasingly important due to the rapid growth of video traffic on wireless networks. The inherent variability of the wireless channel as well as the Variable Bit Rate (VBR) of the compressed video streams make QoE management a challenging problem. Prior work has studied this problem in the context of transmitting a single video stream. In this paper, we investigate multiplexing schemes to transmit multiple video streams from a base station to mobile clients that use number of playout stalls as a performance metric. In this context, we present an epoch-by-epoch framework to fairly allocate wireless transmission slots to streaming videos. In each epoch our scheme essentially reduces the vulnerability to stalling by allocating slots to videos in a way that maximizes the minimum ‘playout lead’ across all videos. Next, we show that the problem of allocating slots fairly is NP-complete even for a constant number of videos. We then present a fast lead-aware greedy algorithm for the problem. Our choice of greedy algorithm is motivated by the fact that this algorithm is optimal when the channel quality of a user remains unchanged within an epoch (but different users may experience different channel quality). Moreover, our experimental results based on public MPEG-4 video traces and wireless channel traces that we collected from a WiMAX test-bed show that the lead-aware greedy approach performs a fair distribution of stalls across the clients when compared to other algorithms, while still maintaining similar or lower average number of stalls per client. <s> BIB008 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> There is a growing interest in over-the-top (OTT) dynamic adaptive streaming over Hypertext Transfer Protocol (HTTP) (DASH) services. In mobile DASH, a client controls the streaming rate and the base station in the mobile network decides on the resource allocation. Different from the majority of previous works that focus on client-based rate adaptation mechanisms, this paper investigates the mobile network potential for enhancing the user quality-of-experience (QoE) in multiuser OTT DASH. Specifically, we first present proactive and reactive QoE optimization approaches for adapting the adaptive HTTP video delivery in an long-term evolution network. We then show, using subjective experiments, that by taking a proactive role in determining the transmission and streaming rates, the network operator can provide a better video quality and a fairer QoE across the streaming users. Furthermore, we consider the playout buffer time of the clients and propose a novel playout buffer-dependent approach that determines for each client the streaming rate for future video segments according to its buffer time and the achievable QoE under current radio conditions. In addition, we show that by jointly solving for the streaming and transmission rates, the wireless network resources are more efficiently allocated among the users and substantial gains in the user perceived video quality can be achieved. <s> BIB009 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> This work presents a QoE-based interworking call admission, handoff, and packet scheduling system to provide a seamless multimedia streaming services over LTE network. First, QoE metrics are defined based on the amount of buffered frames at the video decoder buffer. Based on these QoE metrics, the proposed call admission algorithm estimates the cell idleness at the next call arriving time to determine the admission of a new UE and the proposed handoff algorithm determines the appropriate handoff trigger timing to keep a balance of the QoE satisfaction levels among immediately adjacent cells. The proposed packet scheduling algorithm has designed in consideration of both the QoE satisfaction levels and the wireless link states of all admitted UEs. Finally, experimental results indicate that the proposed interworking system improves the QoE satisfaction levels of all admitted UEs and overall network utilization better than other existing methods. <s> BIB010 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> In LTE system, HTTP streaming services sometimes experience video quality deterioration because of the constraint of available wireless resources, which leads to reduce of Quality of Experience (QoE). In this paper, we propose a new scheduling scheme which is QoE-oriented from user's perceptive to improve the performance of HTTP streaming service in a LTE system. First of all, we adopt the jerkiness, frame freezing for example, perceived at an end user as the prominent QoE factor and implement a jerkiness measuring algorithm on end devices. Secondly, we implement a prioritized traffic flow scheduling algorithm at the base station, and put the end users who experience the maximum jerkiness to be scheduled with the highest priority. Finally, we compare the performance of the proposed QoE-oriented scheme with the traditional scheduling algorithm (i.e. Round Robin scheduling algorithm) in terms of jerkiness for HTTP streaming service. Simulation result shows that the proposed scheme can dramatically improve QoE from user's perspective by effectively decrease the jerkiness of HTTP streaming video. <s> BIB011 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> Recently, Dynamic Adaptive Streaming over HTTP (DASH) has attracted significant attention. In this paper, we consider DASH-based transmission of scalable videos in wireless broadband access networks (e.g., long-term evolution and WiMAX), and propose three methods to enhance the quality of experience of wireless DASH users. First, we design an improved mapping scheme from scalable video coding layers to DASH layers that can provide the desired bitrates, enhance the video end-to-end throughput, and reduce the HTTP communication overhead. Second, we develop a DASH-friendly scheduling and resource allocation algorithm by integrating the DASH-based media delivery and the radio-level adaptation via a cross-layer approach. It utilizes the characteristics of video content and scalable video coding, and greatly reduces the possibility of video playback interruption by considering the client buffer status. The optimization problem is formulated as a mixed binary integer programming problem, and is solved by a subgradient method. Finally, a DASH proxy-based bitrate stabilization algorithm is proposed to improve the video playback smoothness that can achieve the desired tradeoff between playback quality and stability. Simulations with the Qualnet tool demonstrate that our schemes achieve better performances than other methods in the literature. <s> BIB012 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> Recently, the way people consume video content has been undergoing a dramatic change. Plain TV sets, that have been the center of home entertainment for a long time, are losing ground to hybrid TVs, PCs, game consoles, and, more recently, mobile devices such as tablets and smartphones. The new predominant paradigm is: watch what I want, when I want, and where I want. The challenges of this shift are manifold. On the one hand, broadcast technologies such as DVB-T/C/S need to be extended or replaced by mechanisms supporting asynchronous viewing, such as IPTV and video streaming over best-effort networks, while remaining scalable to millions of users. On the other hand, the dramatic increase of wireless data traffic begins to stretch the capabilities of the existing wireless infrastructure to its limits. Finally, there is a challenge to video streaming technologies to cope with a high heterogeneity of end-user devices and dynamically changing network conditions, in particular in wireless and mobile networks. In the present work, our goal is to design an efficient system that supports a high number of unicast streaming sessions in a dense wireless access network. We address this goal by jointly considering the two problems of wireless transmission scheduling and video quality adaptation, using techniques inspired by the robustness and simplicity of proportional-integral-derivative (PID) controllers. We show that the control-theoretic approach allows to efficiently utilize available wireless resources, providing high quality of experience (QoE) to a large number of users. <s> BIB013 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> B. Active End-user Device / Passive User Strategies <s> In this paper we propose evaluation models and calculate range of potential gains for enhancing the average web-browsing QoE of all the users in a mobile network with given capacity. We investigate a method that takes capacity from users during QoE insensitive periods. The gained capacity is distributed among users being in QoE affecting state. Our models of web page network prioritization show that the potential gain for QoE affecting periods highly depends on the correlation between data downloaded during QoE affecting and QoE insensitive periods. The numerical evaluation of wide range of scenarios with web traffic shows that the achievable gain is up to 104% i.e., halving the download time of QoE affecting part. Network prioritization of web pages has good potential to improve web-browsing QoE. <s> BIB014
One way to enhance the subjective quality perception of a service is to perform QoE assessment as close as possible to the end-user and to report this information to the base station. In this way, there is a higher degree of confidence regarding the influence of the scheduler adjustments versus the QoE improvement, since more accurate QoE metrics can be used. On the other hand, this type of scheduling algorithms require feedback channels for QoE measurements. Recent standards, like DASH, already incorporate specifications about how relevant QoE parameters can be reported to the server. In the scheduling strategies described in this subsection, the end-users devices are regarded as clients that are able to measure and to report to the base stations the QoE metrics that will be be taken into account by the scheduler, while the user itself does not perform any action. 1) Video Streaming: In BIB002 , a QoE cross-layer design for video service is formulated where the scheduler allocates resources taking into account the video distortion caused by the radio channel, which is estimated and reported by the end-user devices according to channel quality and packet loss rate. A radio resource management with tunable parameters is proposed in BIB003 , which works in conjunction with adaptive streaming of video delivery in order to maximize the number of satisfied customers within LTE systems. Besides introducing the notion of rebuffering outage capacity for evaluating the capacity of downlink LTE air interface for buffered video services, the rebuffering percentage (the percentage of the total streaming time spent rebuffering) is adopted as a QoE metric that the clients feedback, enabling to design a QoE-aware prioritization engine and a playback buffer aware downlink scheduler. The buffer status of a video client can also play an important role when performing QoE-based scheduling. The authors of BIB004 describe and evaluate a QoE-oriented scheduling for YouTube videos in OFDMA networks, where a client-based feedback is used to directly forward the buffered playtime of each video, so as to optimize the user perceived quality by allocating resources according to the current state of the respective end-user application. In BIB006 , a cross-layer mediabuffer aware optimization framework is proposed for wireless resource allocation that constrains rebuffering probability for adaptive video streaming over LTE. The scheduling algorithm is based on periodic feedback of the buffer status of video clients, where priorities are given not only taking into account the absolute values of client media buffer levels, but also considering the rate of change of these buffer levels. The work described in BIB008 presents a framework to fairly allocate wireless transmission slots to multiple video streams from a base station to mobile clients, where the authors propose that clients communicate their buffered data in order to suggest a scheduling scheme that attempts to prevent stalls by equitably maximizing the buffer level among all receivers. The authors of BIB009 propose an optimization process to adapt the mobile video in LTE by considering the radio conditions and playout buffer levels of the clients. More specifically, a proxy-based method is adopted to match the streaming rate of each user to the QoE optimization result, as well as a resource allocation based on the buffer demands of the users. In BIB010 , a QoE-based interworking call admission, handoff, and scheduling system is proposed to provide a seamless multimedia streaming services over LTE networks. QoE metrics are defined based on the amount of stored video frames at the video decoder buffer, which are then used to try to guarantee the QoE satisfaction levels of already admitted UEs, to provide smooth multimedia streaming services to as many UEs as possible and to keep a balance of the QoE satisfaction levels among adjacent cells. An application-aware scheduler for video delivery over LTE is proposed in  where, by taking into account the buffered playtime sent by the users, the scheduler prioritizes the video flows that are in a critical state. More elaborate techniques have also been proposed, which combine other QoE relevant parameters with information related to either the rebuffering events or the buffer level. The authors of BIB005 presented a dynamic priority assignment algorithm that enables a wireless scheduler to prioritize DASH video, so as to guarantee a minimum QoE, which is defined by the authors as a weighted sum of video bitrate, jitter and smoothness of playback. This algorithm works in conjunction with a rate adaptive HTTP video streaming proxy for wireless broadband access networks, so that when the selected video rate is below a certain threshold, it can be interpreted that the DASH user's channel condition is not good enough, meaning that the respective flow should be prioritized by the scheduler. In BIB011 , the authors propose a resource scheduling scheme to improve the performance of HTTP video streaming service in LTE systems. First, by analyzing the time-dimension of QoE, namely frame freezing, and by considering not only instantaneous service quality, but also past service quality deterioration, an algorithm to measure the 'jerkiness' at each end device is presented. Afterwards, the proposed base station scheduling algorithm prioritizes the traffic flow accordingly to the 'jerkiness' reported by each device: the end users who experience the maximum 'jerkiness' are scheduled with the highest priority. A DASH-based scheduling scheme is developed in BIB012 for the streaming of scalable videos over HTTP in OFDMA systems, which is cross-layer and QoEaware. The proposed algorithm dynamically allocates wireless subchannels and power based on the currently played segment and following requested segment (both reported by the clients), so as to avoid playback interruption due to buffer underflow and to improve the decoded video quality of all users. The integration of not only both rebuffering events and buffer level informations, but also other metrics for the development of QoE-oriented scheduling methods, has been also addressed by some authors. In BIB013 , an approach for joint transmission scheduling (capacity allocation) and video quality selection is presented, in order to design an efficient system that supports a high number of unicast HTTP adaptive video streaming sessions in a dense wireless access network. The authors use QoE-related performance metrics such as total rebuffering time, start-up delay, average media bitrate, media bitrate fluctuations and media bitrate fairness (computed by users and communicated to the network as part of the download request), so as to not only maintain a desired video quality, but also to allocate the remaining capacity, if available, in a fair manner in order to provide high network utilization and to eventually enable users to switch to a higher video quality. A simple asymptotically optimal online algorithm to jointly optimize HTTP video delivery quality adaptation and wireless network resource allocation is presented in BIB007 . The authors propose that minimal signaling is used from the clients to the network controller in order to enhance the scheduling task and to fairly maximize video clients' QoE, taking into account trade-offs among the average quality, temporal variability in quality, rebuffering time (including startup delay), and cost of video delivery. 2) VoIP, Web Browsing & Unspecified Applications: Turning the attention to applications other than video streaming, the authors of  proposed a downlink scheduling method for LTE networks, which is evaluated for VoIP traffic. More specifically, the users' devices compute and feedback to the base station a QoE metric based on the the overall effect of delay and packet loss rate, so that the scheduler is able to allocate the radio resources in a fairly and efficient way. In BIB014 , a collaborative QoE-aware resource redistribution mechanism is proposed for web browsing where, taking into account the web page load time, a method is investigated that takes capacity from users during QoE insensitive periods and redistributes the respective network resources among users who can utilize this capacity to increase their QoE. Regarding multi-service applications, a QoE-oriented strategy is introduced in BIB001 for OFDMA radio resource allocation based on game theory, in which users cooperate with each other in a practical way to jointly maximize QoE. In particular, the authors consider a utility function that aims at the maximization of the minimum MOS experienced by the users, which is based on date rate and packet-error-probability, in order to optimize the fairness in terms of MOS of heterogeneous users' requirements (voice, video, and data). A summary of the aforementioned active end-user device / passive user strategies is given in Table II . As can be seen, information related to the rebuffering events and the buffer level are commonly adopted as QoE metrics for these type of scheduling approaches when dealing with video streaming. On the other hand, delay still plays an important role for VoIP and web browsing applications, whereas buffer-aware scheduling is also not adopted for the case where the application is not specified, since it might not make sense to use this information when dealing with generic approaches (i.e., where the application or its buffer characteristics are not known in advance).