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

A Bankruptcy Game Approach for Resource Allocation in Cooperative Femtocell Networks

Abstract-Femtocells have recently appeared as a viable solution to enable broadband connectivity in mobile cellular networks. Instead of redimensioning macrocells at the base station level, the modular installation of short-range access points can grant multiple benefits, provided that interference is efficiently managed. In the case where femtocells use different frequency bands than macrocells (i.e., split-spectrum approach), interference between femtocells is the major issue. In particular, congestion cases in which femtocell demands exceed the available bandwidth pose an important challenge. If, as expected, the femtocell service is going to be separately billed by legacy wire-line Internet Service Providers, strategic interference management and resource allocation mechanisms are needed to avoid performance degradation during congestion cases. In this paper, we model the resource allocation in cooperative femtocell networks as a bankruptcy game. We identify possible solutions from cooperative game theory, namely the Shapley value and the Nucleolus, and show through extensive simulations of realistic scenarios that they outperform two state-of-the-art schemes, namely Centralized-Dynamic Frequency Planning, C-DFP, and Frequency-ALOHA, F-ALOHA. In particular, the Nucleolus solution offers best performance overall in terms of throughput and fairness, at a lower time complexity

Resource allocation in networks via coalitional games

The main goal of this dissertation is to manage resource allocation in network engineering problems and to introduce efficient cooperative algorithms to obtain high performance, ensuring fairness and stability. Specifically, this dissertation introduces new approaches for resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) wireless networks and in smart power grids by casting the problems to the coalitional game framework and by providing a constructive iterative algorithm based on dynamic learning theory.  Software Engineering (Software)Algorithms and the Foundations of Software technolog

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

DISCO:Interference-Aware Distributed Cooperation with Incentive Mechanism for 5G Heterogeneous Ultra-Dense Networks

Interference and traffic imbalance hinder improved system performance in heterogeneous ultra-dense networks. Network cooperation has become a promising paradigm with sophisticated techniques that can significantly enhance performance. In this article, a coalition game-theoretic framework is introduced to characterize cooperative behaviors, thus exploring these cooperative benefits and diversity gains. First, we introduce the basis of the coalition games. Then we survey its latest applications, in particular, interference mitigation and traffic offloading. Different from most current applications, we concentrate on cooperative incentive mechanism design since node cooperation always means resource consumption and other costs. Moreover, for the incentive mechanism, cooperative spectrum leasing is introduced. To mitigate interference and balance traffic, we propose two schemes under the presented framework: IASL and TOSL. Simulation results show the improved performance of the cooperative gains using the proposed IASL and TOSL schemes

Planning and optimisation of 4G/5G mobile networks and beyond

As mobile networks continue to evolve, two major problems have always existed that greatly affect the quality of service that users experience. These problems are (1) efficient resource management for users at the edge of the network and those in a network coverage hole. (2) network coverage such that improves the quality of service for users while keeping the cost of deployment very low. In this study, two novel algorithms (Collaborative Resource Allocation Algorithm and Memetic-Bee-Swarm Site Location-Allocation Algorithm) are proposed to solve these problems. The Collaborative Resource Allocation Algorithm (CRAA) is inspired by lending and welfare system from the field of political economy and developed as a Market Game. The CRAA allows users to collaborate through coalition formation for cell edge users and users with less than the required Signal-to-Noise-plus-Interference-Ratio to transmit at satisfactory Quality of Service, which is a result of the payoff, achieved and distributed using the Shapley value computed using the Owens Multi Linear Extension function. The Memetic-Bee-Swarm Site Location-Allocation Algorithm (MBSSLAA) is inspired by the behaviour of the Memetic algorithm and Bee Swarm Algorithm for site location. Series of System-level simulations and numerical evaluations were run to evaluate the performance of the algorithms. Numerical evaluation and simulations results show that the Collaborative Resource Allocation Algorithm compared with two popular Long Term Evolution-Advanced algorithms performs higher in comparison when assessed using throughput, spectral efficiency and fairness. Also, results from the simulation of MBSSLAA using realistic network design parameter values show significant higher performance for users in the coverage region of interest and signifies the importance of the ultra-dense small cells network in the future of telecommunications’ services to support the Internet of Things. The results from the proposed algorithms show that following from the existing solutions in the literature; these algorithms give higher performance than existing works done on these problems. On the performance scale, the CRAA achieved an average of 30% improvement on throughput and spectral efficiency for the users of the network. The results also show that the MBSSLAA is capable of reducing the number of small cells in an ultra-dense small cell network while providing the requisite high data coverage. It also indicates that this can be achieved while maintaining high SINR values and throughput for the users, therefore giving them a satisfactory level of quality of service which is a significant requirement in the Fifth Generation network’s specification

Game Theory and Microeconomic Theory for Beamforming Design in Multiple-Input Single-Output Interference Channels

In interference-limited wireless networks, interference management techniques are important in order to improve the performance of the systems. Given that spectrum and energy are scarce resources in these networks, techniques that exploit the resources efficiently are desired. We consider a set of base stations operating concurrently in the same spectral band. Each base station is equipped with multiple antennas and transmits data to a single-antenna mobile user. This setting corresponds to the multiple-input single-output (MISO) interference channel (IFC). The receivers are assumed to treat interference signals as noise. Moreover, each transmitter is assumed to know the channels between itself and all receivers perfectly. We study the conflict between the transmitter-receiver pairs (links) using models from game theory and microeconomic theory. These models provide solutions to resource allocation problems which in our case correspond to the joint beamforming design at the transmitters. Our interest lies in solutions that are Pareto optimal. Pareto optimality ensures that it is not further possible to improve the performance of any link without reducing the performance of another link. Strategic games in game theory determine the noncooperative choice of strategies of the players. The outcome of a strategic game is a Nash equilibrium. While the Nash equilibrium in the MISO IFC is generally not efficient, we characterize the necessary null-shaping constraints on the strategy space of each transmitter such that the Nash equilibrium outcome is Pareto optimal. An arbitrator is involved in this setting which dictates the constraints at each transmitter. In contrast to strategic games, coalitional games provide cooperative solutions between the players. We study cooperation between the links via coalitional games without transferable utility. Cooperative beamforming schemes considered are either zero forcing transmission or Wiener filter precoding. We characterize the necessary and sufficient conditions under which the core of the coalitional game with zero forcing transmission is not empty. The core solution concept specifies the strategies with which all players have the incentive to cooperate jointly in a grand coalition. While the core only considers the formation of the grand coalition, coalition formation games study coalition dynamics. We utilize a coalition formation algorithm, called merge-and-split, to determine stable link grouping. Numerical results show that while in the low signal-to-noise ratio (SNR) regime noncooperation between the links is efficient, at high SNR all links benefit in forming a grand coalition. Coalition formation shows its significance in the mid SNR regime where subset link cooperation provides joint performance gains. We use the models of exchange and competitive market from microeconomic theory to determine Pareto optimal equilibria in the two-user MISO IFC. In the exchange model, the links are represented as consumers that can trade goods within themselves. The goods in our setting correspond to the parameters of the beamforming vectors necessary to achieve all Pareto optimal points in the utility region. We utilize the conflict representation of the consumers in the Edgeworth box, a graphical tool that depicts the allocation of the goods for the two consumers, to provide closed-form solution to all Pareto optimal outcomes. The exchange equilibria are a subset of the points on the Pareto boundary at which both consumers achieve larger utility then at the Nash equilibrium. We propose a decentralized bargaining process between the consumers which starts at the Nash equilibrium and ends at an outcome arbitrarily close to an exchange equilibrium. The design of the bargaining process relies on a systematic study of the allocations in the Edgeworth box. In comparison to the exchange model, a competitive market additionally defines prices for the goods. The equilibrium in this economy is called Walrasian and corresponds to the prices that equate the demand to the supply of goods. We calculate the unique Walrasian equilibrium and propose a coordination process that is realized by the arbitrator which distributes the Walrasian prices to the consumers. The consumers then calculate in a decentralized manner their optimal demand corresponding to beamforming vectors that achieve the Walrasian equilibrium. This outcome is Pareto optimal and lies in the set of exchange equilibria. In this thesis, based on the game theoretic and microeconomic models, efficient beamforming strategies are proposed that jointly improve the performance of the systems. The gained results are applicable in interference-limited wireless networks requiring either coordination from the arbitrator or direct cooperation between the transmitters