Applications of Game Theory and Microeconomics in Cognitive Radio and Femtocell Networks

Cognitive radio networks have recently been proposed as a promising approach to overcome the serious problem of spectrum scarcity. Other emerging concept for innovative spectrum utilization is femtocells. Femtocells are low-power and short-range wireless access points installed by the end-user in residential or enterprise environments. A common feature of cognitive radio and femtocells is their two-tier nature involving primary and secondary users (PUs, SUs). While this new paradigm enables innovative alternatives to conventional spectrum management and utilization, it also brings its own technical challenges. A main challenge in cognitive radio is the design of efficient resource (spectrum) trading methods. Game and microeconomics theories provide tools for studying the strategic interactions through rationality and economic benefits between PUs and SUs for effective resource allocation. In this thesis, we investigate some efficient game theoretic and microeconomic approaches to address spectrum trading in cognitive networks. We propose two auction frameworks for shared and exclusive use models. In the first auction mechanism, we consider the shared used model in cognitive radio networks and design a spectrum trading method to maximize the total satisfaction of the SUs and revenue of the Wireless Service Provider (WSP). In the second auction mechanism, we investigate spectrum trading via auction approach for exclusive usage spectrum access model in cognitive radio networks. We consider a realistic valuation function and propose an efficient concurrent Vickrey-Clarke-Grove (VCG) mechanism for non-identical channel allocation among r-minded bidders in two different cases. The realization of cognitive radio networks in practice requires the development of effective spectrum sensing methods. A fundamental question is how much time to allocate for sensing purposes. In the literature on cognitive radio, it is commonly assumed that fixed time durations are assigned for spectrum sensing and data transmission. It is however possible to improve the network performance by finding the best tradeoff between sensing time and throughput. In this thesis, we derive an expression for the total average throughput of the SUs over time-varying fading channels. Then we maximize the total average throughput in terms of sensing time and the number of SUs assigned to cooperatively sense each channel. For practical implementation, we propose a dynamical programming algorithm for joint optimization of sensing time and the number of cooperating SUs for sensing purpose. Simulation results demonstrate that significant improvement in the throughput of SUs is achieved in the case of joint optimization. In the last part of the thesis, we further address the challenge of pricing in oligopoly market for open access femtocell networks. We propose dynamic pricing schemes based on microeconomic and game theoretic approaches such as market equilibrium, Bertrand game, multiple-leader-multiple-follower Stackelberg game. Based on our approaches, the per unit price of spectrum can be determined dynamically and mobile service providers can gain more revenue than fixed pricing scheme. Our proposed methods also provide residential customers more incentives and satisfaction to participate in open access model.1 yea

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

On the evolution of infrastructure sharing in mobile networks: A survey

ABSTRACT: Infrastructure sharing for mobile networks has been a prolific research topic for more than three decades now. The key driver for Mobile Network Operators to share their network infrastructure is cost reduction. Spectrum sharing is often studied alongside infrastructure sharing although on its own it is a vast research topic outside the scope of this survey. Instead, in this survey we aim to provide a complete picture of infrastructure sharing both over time and in terms of research branches that have stemmed from it such as performance evaluation, resource management etc. We also put an emphasis on the relation between infrastructure sharing and the decoupling of infrastructure from services, wireless network virtualization and multi-tenancy in 5G networks. Such a relation reflects the evolution of infrastructure sharing over time and how it has become a commercial reality in the context of 5

Optimizing total cost of ownership (TCO) for 5G multi-tenant mobile backhaul (MBH) optical transport networks

Legacy network elements are reaching end-of-life and packet-based transport networks are not efficiently optimized. In particular, high density cell architecture in future 5G networks will face big technical and financial challenges due to avalanche of traffic volume and massive growth in connected devices. Raising density and ever-increasing traffic demand within future 5G Heterogeneous Networks (HetNets) will result in huge deployment, expansion and operating costs for upcoming Mobile BackHaul (MBH) networks with flat revenue generation. Thus, the goal of this dissertation is to provide an efficient physical network planning mechanism and an optimized resource engineering tool in order to reduce the Total Cost of Ownership (TCO) and increase the generated revenues. This will help Service Providers (SPs) and Mobile Network Operators (MNOs) to improve their network scalability and maintain positive Project Profit Margins (PPM). In order to meet this goal, three key issues are required to be addressed in our framework and are summarized as follows: i) how to design and migrate to a scalable and reliable MBH network in an optimal cost?, ii) how to control the deployment and activation of the network resources in such MBH based on required traffic demand in an efficient and cost-effective way?, and iii) how to enhance the resource sharing in such network and maximize the profit margins in an efficient way? As part of our contributions to address the first issue highlighted above and to plan the MBH with reduced network TCO and improved scalability, we propose a comprehensive migration plan towards an End-to-End Integrated-Optical-Packet-Network (E2-IOPN) for SP optical transport networks. We review various empirical challenges faced by a real SP during the transformation process towards E2-IOPN as well as the implementation of an as-built plan and a high-level design (HLD) for migrating towards lower cost-per-bit GPON, MPLS-TP, OTN and next-generation DWDM technologies. Then, we propose a longer-term strategy based on SDN and NFV approach that will offer rapid end-to-end service provisioning with costefficient centralized network control. We define CapEx and OpEx cost models and drive a cost comparative study that shows the benefit and financial impact of introducing new low-cost packet-based technologies to carry traffic from legacy and new services. To address the second issue, we first introduce an algorithm based on a stochastic geometry model (Voronoi Tessellation) to more precisely define MBH zones within a geographical area and more accurately calculate required traffic demands and related MBH infrastructure. In order to optimize the deployment and activation of the network resources in the MBH in an efficient and cost-effective way, we propose a novel method called BackHauling-as-a-Service (BHaaS) for network planning and Total Cost of Ownership (TCO) analysis based on required traffic demand and a "You-pay-only-for-what-you-use" approach. Furthermore, we enhance BHaaS performance by introducing a more service-aware method called Traffic-Profile-asa- Service (TPaaS) to further drive down the costs based on yearly activated traffic profiles. Results show that BHaaS and TPaaS may enhance by 22% the project benefit compared to traditional TCO model. Finally, we introduce a new cost (CapEx and OpEx) models for 5G multi-tenant Virtualized MBH (V-MBH) as part of our contribution to address the third issue. In fact, in order to enhance the resource sharing and maximize the network profits, we drive a novel pay-as-yougrow and optimization model for the V-MBH called Virtual-Backhaul-as-a-Service (VBaaS). VBaaS can serve as a planning tool to optimize the Project Profit Margin (PPM) while considering the TCO and the yearly generated Return-on-Investment (ROI). We formulate an MNO Pricing Game (MPG) for TCO optimization to calculate the optimal Pareto-Equilibrium pricing strategy for offered Tenant Service Instances (TSI). Then, we compare CapEx, OpEx, TCO, ROI and PPM for a specific use-case known in the industry as CORD project using Traditional MBH (T-MBH) versus Virtualized MBH (V-MBH) as well as using randomized versus Pareto-Equilibrium pricing strategies. The results of our framework offer SPs and MNOs a more precise estimation of traffic demand, an optimized infrastructure planning and yearly resource deployment as well as an optimized TCO analysis (CapEx and OpEx) with enhanced pricing strategy and generated ROI. Numerical results show more than three times increase in network profitability using our proposed solutions compared with Traditional MBH (T-MBH) methods

Game-Theoretic Frameworks for the Techno-Economic Aspects of Infrastructure Sharing in Current and Future Mobile Networks

RÉSUMÉ Le phénomène de partage d’infrastructure dans les réseaux mobiles a prévalu au cours des deux dernières décennies. Il a pris de l’ampleur en particulier pendant les deux dernières migrations technologiques, à savoir de la 2G à la 3G et de la 3G à la 4G et il sera encore plus crucial à très court terme avec l’avènement de la 5G. En permettant aux Opérateurs de Réseaux Mobiles (ORM) de faire face à la demande croissante des utilisateurs et à la baisse des revenus. Il n’est pas rare non plus que le partage d’infrastructure s’accompagne du partage du spectre, une ressource essentielle et de plus en plus rare pour les réseaux mobiles. Dans ce milieu, la communauté des chercheurs, parmis d’autres, a étudié les multiples aspects techniques du partage d’infrastructure parfois associés au partage du spectre. Entre autres, ces aspects techniques comprennent l’évaluation des performances en termes de métriques de réseau, de gestion de ressources et d’habilitateurs et d’architectures adaptées. Les aspects économiques ont également été abordés, mais généralement en se concentrant étroitement sur l’estimation des économies de coûts des dfférentes alternatives de partage d’infrastructure. Cependant, lorsqu’on considère le problème du partage d’infrastructure, et le cas échéant aussi du partage du spectre du point de vue d’un ORM, qui est une entité intéressée à maximiser le profit, il est important d’évaluer non seulement la réduction des coûts de cette infrastructure, et le cas échéant aussi le partage du spectre, mais aussi leur impact sur les performances du réseau et par conséquent sur les revenus de l’ORM. De ce point de vue, la viabilité du partage d’infrastructure ne doit pas être prise pour acquise ; afin d’étudier le problème stratégique d’un ORM concluant un accord de partage avec un ou plusieurs autres ORM, les aspects techniques et économiques doivent être pris en compte. Cette étude constitue le premier objectif de ce projet de recherche doctorale. Plus précisément, nous avons considéré plusieurs variantes résultant de deux cas où chaque variante a été abordée par un modèle mathématique approprié. Ces variantes répondent à un scénario 4G commun dans lequel il existe un ensemble de ORM avec des parts de marché données qui coexistent dans une zone géographique urbaine dense ; chaque ORM doit décider s’il faut déployer une couche de petites cellules dans la zone et, le cas échéant, s’il doit le faire lui-même ou en concluant un accord de partage en créant un réseau partagé avec certains, ou la totalité, des autres ORM, auquel cas une coalition est créée. Une caractéristique commune importante de ces variantes est le modèle de tarification de l’utilisateur défini comme une fonction linéaire du taux moyen perçu par l’utilisateur en fonction de la coalition dont fait partie l’ORM de l’utilisateur.----------ABSTRACT The phenomenon of infrastructure sharing in mobile networks has been prevalent over the last two decades. It has gathered momentum especially during the last two technology migrations, i.e., from 2G to 3G and from 3G to 4G and it will be even more crucial with the advent of 5G. The key rationale behind such phenomenon is cost reduction as a means for Mobile Network Operators (MNOs) to deal with an increasing user demand but declining revenues. It is also not unusual for infrastructure sharing to go hand in hand with sharing of spectrum, an essential and increasingly scarce resource for mobile networks. In this milieu, the research community (but not only) has addressed multiple technical aspects of infrastructure sharing sometimes combined with spectrum sharing. Among others, such technical aspects include performance evaluation in terms of network metrics, resource management and enablers and adapted architectures. Economic aspects have been addressed as well, but usually with a narrow focus on estimating the cost savings of the di˙erent infrastructure sharing alternatives. However, from the perspective of an MNO, which is a self-interested, profit-maximizing entity, it is important to assess not only the cost reduction that infrastructure sharing, and when applicable, also spectrum sharing bring about, but also their impact on the network performance and consequently on the MNO’s revenues. From this perspective, the viability of infrastructure sharing should not be taken for granted; in order to study the strategic problem of an MNO entering a sharing agreement with one or multiple other MNOs, both technical and economic aspects should be taken into account – such study has been the first objective of this doctoral research project. We have specifically considered multiple variants arising from two cases where each variant has been tackled by an appropriate mathematical model. These variants address a common 4G scenario in which there is a set of MNOs with given market shares that coexist in a given dense urban geographical area; each MNO has to decide whether to deploy a layer of small cells in the area and if so, whether to do that by itself or by entering a sharing agreement, i.e., building a shared network with a subset or all other MNOs (in which case a coalition is created). One key common feature of these variants is the user pricing model which is defined as a linear function of the average rate perceived by the user depending on the coalition joined by the user’s MNO; such pricing model allows us to capture the impact that infrastructure sharing, and, when applicable, also spectrum sharing have on the MNO’s revenues through a network performance metric. In turn, the two key outcomes of the models tackling these variants are the set of coalitions and the number of small cells they deploy