QoE Driven Multimedia Service Schemes in Wireless Networks Resource Allocation: Evolution from Optimization, Game Theory, to Economics

In order to deal with the Quality of Experience (QoE) improvement issue in the wireless networks services. In this dissertation we first investigated the Device to Device (D2D) relaying approach in the conventional Base Station (BS) to User Equipment (UE) two entities multimedia service system. In this part, the Multiple Input Multiple Output (MIMO) technology will be implemented in the D2D communication. Furthermore, factors such as the multimedia content distribution (i.e., Quad-tree fractal image compression method), the power allocation strategy, and modulation size are jointly considered to improve the QoE performance and energy efficiency. In addition, the emerging Non-Orthogonal Multiple Access (NOMA) transmission method is becoming very popular and being considered as one of the most potential technologies for the next generation of wireless networks. For the purpose of improving the QoE of UE in the wireless multimedia service, the power allocation method and the corresponding limitations are studied in detail in the wireless system where the traditional Orthogonal Multiple Access (OMA) technology and the promising NOMA technology are compared. At last, facing the real business model in the wireless network services, where the Content Provider (CP), Wireless Carrier (WC), and UE are included, we extend on work from the conventional BS-UE two entities research model to the CP-WC-UE three entities model. More specifically, a generalized best response Smart Media Pricing (SMP) method is studied in this dissertation. In our work, the CP and WC are treated as the service provider alliance. The SMP approach and the game theory are utilized to determine the data length of UE and the data price rate determined by the CP-WC union. It is worth pointing out that the concavity of utility function is no longer necessary for seeking the game equilibrium under the proposed best response game solution. Numerical simulation results also validate the system performance improvement of our proposed transmission schemes

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Optimisation des Systèmes Partiellement Observables dans les Réseaux Sans-fil (Théorie des jeux, Auto-adaptation et Apprentissage)

La dernière décennie a vu l'émergence d'Internet et l'apparition des applications multimédia qui requièrent de plus en plus de bande passante, ainsi que des utilisateurs qui exigent une meilleure qualité de service. Dans cette perspective, beaucoup de travaux ont été effectués pour améliorer l'utilisation du spectre sans fil.Le sujet de ma thèse de doctorat porte sur l'application de la théorie des jeux, la théorie des files d'attente et l'apprentissage dans les réseaux sans fil,en particulier dans des environnements partiellement observables. Nous considérons différentes couches du modèle OSI. En effet, nous étudions l'accès opportuniste au spectre sans fil à la couche MAC en utilisant la technologie des radios cognitifs (CR). Par la suite, nous nous concentrons sur le contrôle de congestion à la couche transport, et nous développons des mécanismes de contrôle de congestion pour le protocole TCP.Since delay-sensitive and bandwidth-intense multimedia applications have emerged in the Internet, the demand for network resources has seen a steady increase during the last decade. Specifically, wireless networks have become pervasive and highly populated.These motivations are behind the problems considered in this dissertation.The topic of my PhD is about the application of game theory, queueing theory and learning techniques in wireless networks under some QoS constraints, especially in partially observable environments.We consider different layers of the protocol stack. In fact, we study the Opportunistic Spectrum Access (OSA) at the Medium Access Control (MAC) layer through Cognitive Radio (CR) approaches.Thereafter, we focus on the congestion control at the transport layer, and we develop some congestion control mechanisms under the TCP protocol.The roadmap of the research is as follows. Firstly, we focus on the MAC layer, and we seek for optimal OSA strategies in CR networks. We consider that Secondary Users (SUs) take advantage of opportunities in licensed channels while ensuring a minimum level of QoS. In fact, SUs have the possibility to sense and access licensed channels, or to transmit their packets using a dedicated access (like 3G). Therefore, a SU has two conflicting goals: seeking for opportunities in licensed channels, but spending energy for sensing those channels, or transmitting over the dedicated channel without sensing, but with higher transmission delay. We model the slotted and the non-slotted systems using a queueing framework. Thereafter, we analyze the non-cooperative behavior of SUs, and we prove the existence of a Nash equilibrium (NE) strategy. Moreover, we measure the gap of performance between the centralized and the decentralized systems using the Price of Anarchy (PoA).Even if the OSA at the MAC layer was deeply investigated in the last decade, the performance of SUs, such as energy consumption or Quality of Service (QoS) guarantee, was somehow ignored. Therefore, we study the OSA taking into account energy consumption and delay. We consider, first, one SU that access opportunistically licensed channels, or transmit its packets through a dedicated channel. Due to the partial spectrum sensing, the state of the spectrum is partially observable. Therefore, we use the Partially Observable Markov Decision Process (POMDP) framework to design an optimal OSA policy for SUs. Specifically, we derive some structural properties of the value function, and we prove that the optimal OSA policy has a threshold structure.Thereafter, we extend the model to the context of multiple SUs. We study the non-cooperative behavior of SUs and we prove the existence of a NE. Moreover, we highlight a paradox in this situation: more opportunities in the licensed spectrum may lead to worst performances for SUs. Thereafter, we focus on the study of spectrum management issues. In fact, we introduce a spectrum manager to the model, and we analyze the hierarchical game between the network manager and SUs.Finally, we focus on the transport layer and we study the congestion control for wireless networks under some QoS and Quality of Experience (QoE) constraints. Firstly, we propose a congestion control algorithm that takes into account applications' parameters and multimedia quality. In fact, we consider that network users maximize their expected multimedia quality by choosing the congestion control strategy. Since users ignore the congestion status at bottleneck links, we use a POMDP framework to determine the optimal congestion control strategy.Thereafter, we consider a subjective measure of the multimedia quality, and we propose a QoE-based congestion control algorithm. This algorithm bases on QoE feedbacks from receivers in order to adapt the congestion window size. Note that the proposed algorithms are designed based on some learning methods in order to face the complexity of solving POMDP problems.AVIGNON-Bib. numérique (840079901) / SudocSudocFranceF

Power allocation for D2D communications using max-min message-passing algorithm

The approach of factor-graphs (FGs) is applied in the context of power control and user pairing in Device-to-Device (D2D) communications as an effective underlay concept in wireless cellular networks. D2D communications can increase the spectral efficiency of wireless cellular networks by establishing a direct link between devices with limited help from the evolved node base stations (eNBs). A well-designed user pairing and power allocation scheme with low complexity can remarkably improve the system’s performance. In this paper, a simple and distributed FG based approach is utilized for power control and user pairing implementation in an underlay cellular network with D2D communications. A max-min criterion is proposed to maximize the minimum rate of all active users in the network, including the cellular and multiple D2D co-channel links in the uplink direction. An associated message-passing (MP) algorithm is presented to distributedly solve the resultant NP-hard maximization problem, with a guaranteed convergence compared to game-theoretic and Q-learning based methods. The complexity and convergence of the proposed method are analyzed and numerical results confirm that the proposed scheme outperforms alternative algorithms in terms of complexity, while keeping the sum-rate of users nearly the same as centralized counterpart methods

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Energy sustainable paradigms and methods for future mobile networks: A survey

In this survey, we discuss the role of energy in the design of future mobile networks and, in particular, we advocate and elaborate on the use of energy harvesting (EH) hardware as a means to decrease the environmental footprint of 5G technology. To take full advantage of the harvested (renewable) energy, while still meeting the quality of service required by dense 5G deployments, suitable management techniques are here reviewed, highlighting the open issues that are still to be solved to provide eco-friendly and cost-effective mobile architectures. Several solutions have recently been proposed to tackle capacity, coverage and efficiency problems, including: C-RAN, Software Defined Networking (SDN) and fog computing, among others. However, these are not explicitly tailored to increase the energy efficiency of networks featuring renewable energy sources, and have the following limitations: (i) their energy savings are in many cases still insufficient and (ii) they do not consider network elements possessing energy harvesting capabilities. In this paper, we systematically review existing energy sustainable paradigms and methods to address points (i) and (ii), discussing how these can be exploited to obtain highly efficient, energy self-sufficient and high capacity networks. Several open issues have emerged from our review, ranging from the need for accurate energy, transmission and consumption models, to the lack of accurate data traffic profiles, to the use of power transfer, energy cooperation and energy trading techniques. These challenges are here discussed along with some research directions to follow for achieving sustainable 5G systems.Comment: Accepted by Elsevier Computer Communications, 21 pages, 9 figure

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio