A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> A growing trend has emerged in network architecture research to switch focus from Quality of Service (QoS) to Quality of Experience (QoE) optimization. In this paper, we first present QoE models that characterize user satisfaction of video, audio, and data services over wireless networks. We then develop a novel packet scheduling algorithm for multi-hop wireless networks that jointly optimizes the delivery of multiple video, audio, and data flows according to the QoE metrics. We formulate a multidimensional optimization problem that minimizes the overall distortion across all flows for the given network resources on wireless links. Fairness constraints over the flows are also considered as part of the optimization. Our experimental results, obtained with the NS-2 IEEE 802.16 MESH-mode simulator, show that distortion-aware scheduling can significantly increase the perceived quality of different wireless services under bandwidth constraints. Additionally, improved fairness across the competing flows is demonstrated relative to conventional scheduling techniques. <s> BIB001 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> The increasing popularity of user-generated content and the high quality upstreaming capabilities of mobile phones indicate a prevalence of video traffic in the uplink of next generation mobile networks. Need arises for optimizing the network resource allocation while preserving the user satisfaction. In this paper, we propose a service-centric approach for uplink distribution of real-time user-generated content based on the Quality of Experience (QoE) and popularity of the video content. In case of limited network resources, the proposed approach assigns more resources for popular contents while maintaining a minimum guaranteed QoE for the less popular ones. We compare our service-centric approach with a QoE-driven one that does not consider video popularity and evaluate both approaches for the uplink of an LTE system. The simulation results show that a significant gain in terms of average user satisfaction can be achieved. <s> BIB002 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> The widespread use of heterogeneous wireless network technologies and their integration with multi-mode terminals enable users to be associated to the best available networks according to user preferences and application specific requirements. We study a user-centric quality of experience based resource allocation problem with several operators, several types of users and different classes of services. We propose a framework for future short term user-operator contractual vision. We also study the equilibrium solution for the mentioned problem using a game-theoretic approach. Based on experimental measurements, we formulate the utility functions for the users and the operators. Our results are validated through OPNET simulations for different service classes including FTP, VoIP and Video streaming over Long Term Evolution (LTE), and Wireless Local Area Networks (WLAN) technologies. We also implement the IPv6 based flow management for congestion avoidance at inter-operator level, and study the performance of various splitting and non-splitting approaches. <s> BIB003 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Power management is a critical issue for mobile devices, where a significant portion of the total system energy can be often consumed by heavy wireless network activity. In this paper we present a framework that reduces the energy consumption of wireless mobile devices during streaming video content over Wireless LAN networks by utilizing the power saving mechanisms defined in the IEEE 802.11e standard. The framework allows video applications to directly optimize the overall energy efficiency by controlling the sleep cycles of wireless network adapters based on video QoE. The framework employs a simple QoE estimation algorithm that estimates the user level video quality, and adjusts the sleep intervals of the wireless adapter to maintain video quality while maximizing power efficiency. As an important part of our paper the building and configuration steps of a working testbed system is carefully described, which demonstrates the availability and efficiency of the U-APSD power saving technology at hand. A preliminary evaluation of the proposed framework supports that by enabling the WMM Power Saving feature 20-30\% of total system energy can be saved even in case of asynchronous video traffic. <s> BIB004 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> In this paper, a joint uplink (UL) and downlink (DL) framework for wireless mobile camera networks over an OFDMA-based infrastructure is proposed. On the UL, this system collects unicast real-time video streams from mobile wireless camera stations (CSs) and forwards them to a control center. On the DL, the aggregated video streams are multicast to multiple mobile stations (MSs) to facilitate monitoring of the same video scenes. A target bit rate is set for each UL video stream, based on an objective function that includes both the quality of experience (QoE) and popularity of video contents as key criteria. A QoE-driven scheduling and resource allocation policy at the MAC/PHY layers, and a real-time scalable video layer adaptation algorithm in the APP layer are proposed. On the DL, a previously published opportunistic layered multicasting scheduling algorithm is applied. Simulation results demonstrate that this proposed novel architecture can significantly enhance both the spectral efficiency and the QoE of users in both UL and DL directions. <s> BIB005 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> With the fast growing of multimedia communication applications, cognitive radio networks have gained the popularity as they can provide high wireless bandwidth and support quality-driven wireless multimedia services. In multimedia applications such as video conferences over the cognitive radio, the Quality of Experience (QoE) that directly measures the satisfaction of the end users cannot be easily realized due to the limited spectrum resources. The opportunistic spectrum access cognitive radio (CR) is an efficient technology to address this issue. However, the unstable channels allocated to the multimedia secondary users (SUs) can be re-occupied by the primary users (PUs) at any time, which makes the CR difficult to meet the QoE requirements. Therefore, it is important to study how to allocate frequency or spectrum resources to SUs according to their QoE requirements. This paper proposes a novel QoE-driven channel allocation scheme for SUs and cognitive radio networks (CRN) base station (BS). The historical QoE data under different primary channels (PCs) are collected by the SUs and delivered to a Cognitive Radio Base Station (CRBS). The CRBS will allocate available channel resources to the SUs based on their QoE expectations and maintain a priority service queue. The modified ON/OFF models of PCs and service queue models of SUs are jointly investigated for this channel allocation scheme. The performance of multimedia transmission of images and H.264 videos under our CR channel allocation scheme is studied, the results show that the proposed channel allocation approach can significantly improve the QoE of the priority-based SUs over the cognitive radio networks. <s> BIB006 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> In Multi-user MIMO system, traditional user scheduling methods are usually aiming at maximizing the sum-rate capacity of the target system. Such methods select the users which have the best channel quality to service but ignore users' satisfaction. In this paper, we proposed a user satisfaction based judgment criteria, and designed a novel scheduling method in order to ensure users' satisfaction. We apply zero-forcing beam forming (ZFBF) precoding into downlink transmission, and assume perfect knowledge of CSI at the base station. Simulation results show that the algorithm achieved a higher system average user satisfaction degree while suffered a little performance loss compared with the classical SUS-ZFBF strategy. <s> BIB007 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Minimizing energy consumption is becoming more and more crucial in today's mobile terminals communications. Reducing its use pass necessarily by exploiting low power design techniques and by adopting novel energy-aware applications and protocols. The focus in this paper mainly concerns the Voice over IP over Wireless Local Area Network (VoWLAN) application, which is beyond doubt the most popular application in mobile terminals. The real-time nature of this application makes the conventional approaches inefficient, as they conserve energy by either: (i) switching the wireless device from the active mode to the sleep mode when no data is buffered for transmission or reception, which completely block the mobile terminal in the active mode (i.e. waste of energy), or (ii) forcing the switching to the sleep mode, which is clearly a detrimental behavior for such delay-constrained application. The idea of the proposed paper is to wisely determine the optimal schedule between the Sleep and Wakeup periods based on the application requirements. Hence, we propose in the following a quality of experience (QoE)-aware protocol, maximizing the sleep mode duration, for VoIP application. The performance of the proposed protocol is performed through computer simulation. The obtained results clearly demonstrate the superiority of the protocol in conserving energy while keeping the QoE at a desired level. <s> BIB008 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> In cognitive radio network (CRN), secondary users (SU) can share the licensed spectrum with the primary users (PU). Compared with the traditional network, spectrum utilization in CRN will be greatly improved. In order to ensure the performance of SUs as well as PU, wireless relaying can be employed to improve the system capacity. Meanwhile, quality-of-experience (QoE) should be considered and provisioned in the relay scheduling scheme to ensure user experience and comprehensive network performance. In this paper, we studied a QoE provisioning mechanism for a queuing based optimal relay scheduling problem in CRN. We designed a QoE provisioning scheme with multiple optimized goals about higher capacity and lower packet loss probability. The simulation results showed that our mechanism could get a much better performance on packet loss with suboptimum system capacity. And it indicated that our mechanism could guarantee a better user experience through the specific QoS-QoE mapping models. So our mechanism can improve the network performance and user experience comprehensively. <s> BIB009 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Carrier aggregation (CA) is an essential feature in the Long Term Evolution-Advanced (LTE-A) system, which can aggregate two and more component carriers (CCs) to form a much wider transmission bandwidth up to 100 MHz. By means of CA, a user equipment (UE) can be scheduled on multiple CCs simultaneously to transmit data traffic. Recently, the studies on the efficient operation of an LTE-A based CA system have received much attention under simultaneous access scenarios for multiple CCs. However, the existing literature lacks efforts on Quality of Experience (QoE)-aware CA, especially in the uplink. In this paper, we propose a joint resource allocation algorithm for an uplink LTE-A based system, focusing on QoE-aware CA. We first present a framework for the evaluation of UE's QoE satisfaction level by designing a link reward, resource cost, and link utility function. Then, a QoE-aware joint resource allocation algorithm is proposed for the efficient sharing of radio resource by UEs, so that uplink system utility is maximized. Numerical results demonstrate the validity of the proposed algorithm. <s> BIB010 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> The increasing energy demand of mobile phone networks is a problem for the environment and a cost factor for mobile network operators. Multimedia content is increasingly popular, demands high data rates, and increases energy usage of mobile phone networks. Thus it is important to reduce energy usage of mobile phone networks while serving multimedia content with a high quality of experience (QoE). We developed an approach to power-cycle base stations and control the playback of video streams while reducing the energy consumption and not decreasing the QoE for users. We present two implementations: an optimization problem and an iterative algorithm. Up to 80% of energy can be saved by combining power cycling and video stream controlling in low-load situations. With increasing load, the energy consumption also increases while the QoE can still be improved. <s> BIB011 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Small cell networks (SCNs) are widely considered as a promising solution for future cellular deployments. Lately, the benefits of small cells to improve spectrum utilization and the user quality of experience (QoE) have been well documented. In addition, the power consumption of current deployments, for instance due to idle power and cooling equipment, is a major concern for operators. Small cells offer the opportunity for more dynamic power management of base stations, due to coverage overlaps and larger spatio-temporal load fluctuations. Yet, such power management decisions (e.g. turning off a base station) should not lead to excessive performance degradation for users associated with it or additional power consumption. This tradeoff becomes significantly more challenging to evaluate in future networks, due to the diversity of services offered to users beyond the traditional voice calls, as well as the complexity of traffic scheduling algorithms. The goal of this paper is to make a first step towards an analytical investigation of this tradeoff. To this end, we propose a number of QoE constraints that a power management decision should consider, and analytically relate them to key parameters such as user traffic mix, cell load, user density, etc. We then use this framework to perform a preliminary study of the potential energy savings an operator could achieve, while guaranteeing the satisfaction of these constraints. Our results provide some qualitative and quantitative insights on the interesting tradeoff between switch-off duration and number of small cells one can safely switch off. <s> BIB012 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Discontinuous Reception (DRX) in Long Term Evolution (LTE) is used to reduce the energy consumption when there is no data transfer for a given user. Current DRX works on a per-UE basis but works with fixed DRX. That is, DRX does not take into account that different services and different terminals have different requirements on Quality of Experience (QoE). We propose an efficient adaptive DRX method that can provide battery saving without degrading QoE of the services. This method utilizes service and terminal knowledge provided by Deep Packet Inspection (DPI) mechanism and modifies the DRX settings adaptively on the fly. This unique work analyses anonymous traffic data from an operational mobile broadband network and emulates the effects of various DRX settings upon this live traffic data. Live traffic has larger variance in the timescale of DRX than it is assumed by models used in state-of-the-art DRX schemes. Thus the proposed method outperforms existing solutions and get closer to the theoretically ideal case. <s> BIB013 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Globally, there is a tremendous growth in mobile data traffic and mobile network operators (MNO) are investing heavily to expand and operate their networks to serve them. The operational expenditure incurred by MNOs are increasing much more compared to revenue from mobile data traffic, thereby decreasing their profit margins. One of the major components of operational expenditure is the cost of operating cellular base stations using grid power or diesel generators in the absence of grid power. MNOs in off-grid sites constantly rely on diesel generators to run base stations that is very expensive. At the same time, they also cause adverse environmental impact due to CO2 emission. While the economics of renewable energy are already favorable in remote off-grid areas, it has been quite challenging for operators to handle the unpredictability of renewable energy sources while meeting the user QoE. In this work, we present GreenSlice, an `energy-source' aware asynchronous content delivery mechanism that adapts delivery of bulk delay-tolerant content in periods of availability of renewable energy. In particular, given a set of heavy demands (such as downloads of videos, software updates etc.), we present a scheduling algorithm that balances the operator's energy cost and delay experienced by users. We use a novel adaptation of Lyapunov optimization framework to provide bounds on the content delivery time and resulting operational cost. Simulation studies show our mechanism reduces the energy cost by more than 33% compared to traditional schemes of using renewables and non-renewables without asynchronous content delivery, at the same time keeping the increase in delay negligible. <s> BIB014 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Mobile WiFi devices are becoming increasingly popular in non-seamless and user-controlled mobile traffic offloading alongside the standard WiFi hotspots. Unlike the operator-controlled hotspots, a mobile WiFi device relies on the capacity of the macro-cell for the data rate allocated to it. This type of devices can help offloading data traffic from the macro-cell base station and serve the end users within a closer range, but will change the pattern of resource distributions operated by the base station. We propose a resource allocation scheme that aims to optimize user quality of experience (QoE) when accessing video services in the environment where traffic offloading is taking place through interworking between a mobile communication system and low range wireless LANs. In this scheme, a rate redistribution algorithm is derived to perform scheduling which is controlled by a no-reference quality assessment metric in order to achieve the desired trade-offs between efficiency and fairness. We show the performance of this algorithm in terms of the distribution of the allocated data rates throughout the macro-cell investigated and the service coverage offered by the WiFi access point. <s> BIB015 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> The continuing advances in the storage and transmission abilities of user equipment have made it possible to share videos through device-to-device communications, which may be an efficient way to enhance the capacity of cellular network to provide wireless video services. In adaptive D2D video streaming, user experience is greatly influenced by the quality and fluency of the video, which is affected by the D2D link’s quality. Additionally, the quality of D2D links relies on the resource allocation scheme for D2D pairs. To improve the quality of experience in D2D video streaming, we propose a QoE-aware resource allocation scheme for adaptive D2D video streaming. The QoE-aware resource allocation scheme has the ability to cater to the user experience in adaptive video steaming while considering the co-channel interference derived from frequency reuse in D2D communications. Specifically, a dynamic network scheduling problem is formulated and solved, with the objective of maximizing the video quality while maintaining the long-term stable performance of fluency during video playback. Extensive numerical results demonstrate that the proposed QoE-aware resource allocation scheme outperforms the QoE-oblivious resource allocation scheme. <s> BIB016 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> We investigate the problem of streaming multi-user videos over the downlink of a cognitive radio network (CRN), where each cognitive user (CU) can access one channel at a time. We first consider the case where each CU can sense one channel at a time slot at most. To make the problem tractable, we tackle the optimal spectrum sensing and access problems separately and develop matching-based optimal algorithms to the subproblems, which yield an overall suboptimal solution. We then consider the case where each CU can sense multiple channels. We show that under the assumption that all the spectrum sensors work on the same operating point, a two-step approach can derive the optimal spectrum sensing and access policies that maximize the quality of experience (QoE) of the streaming videos. The superior performance of the proposed approaches is validated with simulations and comparisons with benchmark schemes, where a performance gain from 25% to 30% is demonstrated. <s> BIB017 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> We consider the problem of simultaneous on-demand streaming of stored video to multiple users in a multi-cell wireless network where multiple unicast streaming sessions are run in parallel and share the same frequency band. Each streaming session is formed by the sequential transmission of video "chunks," such that each chunk arrives into the corresponding user playback buffer within its playback deadline. We formulate the problem as a Network Utility Maximization (NUM) where the objective is to fairly maximize users' video streaming Quality of Experience (QoE) and then derive an iterative control policy using Lyapunov Optimization, which solves the NUM problem up to any level of accuracy and yields an online protocol with control actions at every iteration decomposing into two layers interconnected by the users' request queues : i) a video streaming adaptation layer reminiscent of DASH, implemented at each user node; ii) a transmission scheduling layer where a max-weight scheduler is implemented at each base station. The proposed chunk request scheme is a pull strategy where every user opportunistically requests video chunks from the neighboring base stations and dynamically adapts the quality of its requests based on the current size of the request queue. For the transmission scheduling component, we first describe the general max-weight scheduler and then particularize it to a wireless network where the base stations have multiuser MIMO (MU-MIMO) beamforming capabilities. We exploit the channel hardening effect of large-dimensional MIMO channels (massive MIMO) and devise a low complexity user selection scheme to solve the underlying combinatorial problem of selecting user subsets for downlink beamforming, which can be easily implemented and run independently at each base station. <s> BIB018 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> Computation offloading is a promising application of mobile clouds that can save energy of mobile devices via optimal transmission scheduling of mobile-to-cloud task offloading. Existing approaches to computation offloading have addressed various aspects of the tradeoff between energy consumption and application latency, but none of them explicitly considered the dependency in optimization on the mobile user''s context, e.g., user tendency, the remaining battery level. This paper captures such a user-centric perspective in the energy-latency tradeoff via a quality-of-experience (QoE) based cost function, and formulates the problem of data offloading scheduling as dynamic programming (DP). To derive the optimal schedule, we first introduce a database-assisted optimal DP algorithm and then propose a suboptimal but computationally-efficient approximate DP (ADP) algorithm based on the limited lookahead technique. An extensive numerical analysis has revealed that the ADP algorithm achieves near-optimal performance incurring only 2.27% extra cost on average than the optimum, and enhances QoE by up to 4.46 times compared to the energy-only scheduling. <s> BIB019 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> In this paper, we investigate an optimal resource on-off switching framework that minimizes the energy consumption of a heterogeneous cellular network. Specifically, our goal is to minimize the energy consumption of the cellular network while satisfying a desired level of buffer starvation probability, which can be considered as a quality of experience (QoE) term. For an ON/OFF bursty arrival process, we introduce recursive equations to obtain the buffer starvation probability of a mobile device (MD) for streaming services. The MD is in the coverage area of a femtocell base station (FBS) which is implemented at the cell edge of a macrocell base station (MBS), and when its buffer gets empty, the media player of the MD restarts the service after a certain amount of packets are prefetched (this event is known as start-up delay in the literature). Numerical simulations illustrate how our system significantly reduces the overall energy consumption of the network while guaranteeing a target starvation probability in comparison to the case where the MD is covered only by one MBS. <s> BIB020 </s> A Survey on QoE-oriented Wireless Resources Scheduling <s> D. Other QoE-oriented Scheduling Methods <s> This paper studies spectrum sharing for providing better quality of experience in 5G networks, which are characterized by multidimensional heterogeneity in terms of spectrum, cells, and user requirements. Specifically, spectrum access, power allocation, and user scheduling are jointly investigated and an optimization problem is formulated with the objective of maximizing the users’ satisfaction across the network. In order to reduce the complexity and overhead, decentralized solutions with local information are required. To this end, we employ game-theoretic approach and interference graph to solve the problem. The proposed game is proved to have at least one Nash Equilibrium (NE), corresponding to either the globally or locally optimal solution to the original optimization problem. A concurrent best-response iterative algorithm is first devised to find the solution, which can converge to an NE, but may not be globally optimal. Therefore, a spatial adaptive play iterative (SAPI) learning algorithm is further proposed to search the global optimum. Theoretical analysis demonstrates that the SAPI algorithm can guarantee to find the globally optimal solution with an arbitrary large probability, when the learning step is set to be sufficiently large. Simulation results are provided to validate the performance of the proposed algorithms. <s> BIB021
All the previous scheduling algorithms addressed the downlink scenario, with the goal of maximizing the aggregate experienced quality of all users within a cell of a single operator. Nonetheless, QoE-aware scheduling methods can enhance the wireless resources management in other scenarios, such as the uplink direction, under heterogeneous, cognitive BIB002 , which assigns more resources for popular contents while maintaining a minimum guaranteed QoE (based on the data rate) for the less popular ones. The authors of BIB005 presented a QoE-driven scheduler for uplink unicast video delivery (intended for surveillance systems), in which the required data rate and delay are the main factors taken into account by the resource allocation scheme. In BIB010 , a QoE-aware joint resource allocation algorithm is proposed for uplink LTE based systems that make use of carrier aggregation, where the evaluation of the users' QoE satisfaction level is performed by a link reward, resource cost and a link utility function designed by the authors. 2) Heterogeneous, Cognitive Radio, Relay & Multi-user MIMO Networks: Only single operators have been considered so far, but some research has already been done regarding heterogeneous wireless networks, where users want to be associated to the best available networks according to their preferences and application specific requirements. For instance, the authors of BIB003 adopt a game-theoretic approach as a framework for user satisfaction based resource allocation with several operators, several types of users and different classes of services. Regarding mobile traffic offloading, a solution for video streaming services, with the optimization of QoE distribution across the network through the interworking between LTE base station and WiFi hotspots, is proposed in BIB015 , where the subjective quality assessment is based on video playback discontinuities. In BIB016 , a QoE-aware scheduling scheme is proposed for video streaming through Device-toDevice (D2D) communications, where the target of radio resource allocation is to maximize the time-averaged quality of video streams transmitted over D2D communications, while constraining the number of stall events for each stream. QoE provisioning schemes can also be used when addressing other wireless resources scheduling problems, such as in cognitive radio networks. In BIB006 , the authors develop a channel allocation scheme for multimedia content transmission over cognitive radio networks, where the base station allocates available channels to secondary users based on their QoE requirements (delay and multimedia content quality). A jointly design of spectrum sensing and access policies for QoE-aware multi-user video streaming within cognitive radio networks is presented in BIB017 , in which the goal is to achieve fairness among the users while maximizing the overall QoE (which is based on the data rate). The authors of BIB021 addressed networks where different types of base stations are deployed to exploit a heterogeneous spectrum pool, consisting of licensed and harvested spectrum, in order to propose a game-theoretic approach that solves the problem of maximizing the users' satisfaction across the network (based on their transmission rate requirement) by jointly optimizing spectrum sharing, user scheduling, and power allocation in a decentralized manner. Regarding wireless relaying in cognitive radio networks, and by considering QoE indicators (relay buffer status) rather than traditional QoS indicators, the authors of BIB009 showed that better user experience can be achieved with sub-optimum system capacity. The work presented in BIB001 also considers multi-hop wireless networks and introduces a scheduling algorithm that jointly optimizes the delivery of multiple video, audio and data flows according to certain QoE metrics. In BIB018 , a system is proposed for efficient delivery of video content over a wireless network formed by a number of densely deployed wireless helper nodes with multi-user MIMO capabilities, where QoE metrics like video quality and rebuffering percentage are used to optimize the transmission scheduling of users at each base station. Another example of QoE-based scheduling is given in BIB007 , where a user selection procedure based on transmitted rate and delay is proposed in order to maximize the average satisfaction degree of multi-user MIMO systems. 3) Energy-related Issues: The "green" networks is also a domain where QoE-based wireless resources management can have an important role. For instance, an approach to power-cycle base stations and to control the playback of video streams is presented in BIB011 , where the goal is to reduce the overall energy consumption of the base stations while maintaining a high QoE for the users. A framework to reduce the energy consumption of small cell networks subject to QoE constraints has been proposed in BIB012 , where an analytical investigation is performed regarding the tradeoff between switching off underloaded base stations and the performance degradation experienced by the users. In BIB004 , a framework is presented that reduces the energy consumption of wireless mobile devices during streaming video content over Wireless Local Area Networks (WLANs), in which a QoEbased algorithm estimates the user level video quality and adjusts the sleep intervals of the wireless adapter to maintain video quality while maximizing power efficiency. The authors of BIB008 proposed a novel approach for energy conservation in mobile terminals regarding VoIP flows over WLANs, namely by controlling the sleep periods based on the requested quality in term of the user QoE. An adaptive discontinuous reception method for LTE systems has been proposed in BIB013 , which can provide battery saving for the terminals without degrading the QoE of the services, namely the delay perceived by a user. In BIB019 , a scheduling policy is proposed to save energy of mobile devices via optimal transmission scheduling of mobileto-cloud task offloading, which considers several QoE domains in order to capture the energy-latency trade-off. An energy efficient resource on-off switching framework for a cellular network comprising a femtocell at the cell edge of a macrocell is investigated in BIB020 , where the goal is to minimize the energy consumption of the cellular network while satisfying a desired level of QoE, which is defined as buffer starvation probability of a mobile device. In BIB014 , an "energy-source" aware asynchronous content delivery mechanism is presented, which adapts delivery of bulk delay-tolerant content in periods of availability of renewable energy, i.e., balances the operator's energy cost and the QoE (namely the delay) experienced by users. Table IV contains a summary of the QoE-oriented scheduling methods presented in this subsection.