20 research outputs found

    Network Formation Games for Distributed Uplink Tree Construction in IEEE 802.16j Networks

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    International audienceThis paper investigates the problem of the formation of the uplink tree structure among the mobile multi-hop relay (MMR) network's base station (MMR-BS) and its different relay stations (RSs). We model the problem as a network formation game in which the RSs want to form a directed tree graph to improve their utility in terms of the Packet Success Rate (PSR) by using multi-hop cooperative transmission while accounting for a link maintenance cost. In this game, the relay stations engage in bilateral negotiations which result in a contractual agreement to form a directed link between each pair. For network dynamics, we propose a myopic algorithm based on the local best responses of the RSs that converges to a local Nash network. Moreover, the proposed dynamics algorithm allows the RSs to autonomously adapt the network topology to changes in the environment due to mobility or to the presence of heterogeneous traffic. Simulations results show how the RSs can self-organize in a tree structure while improving the network's overall PSR up to 17:5% and 15:6% compared, respectively, to the cases where no RSs exist and where the RSs are directly connected to the MMR-BS

    Network Formation Games Among Relay Stations in Next Generation Wireless Networks

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    The introduction of relay station (RS) nodes is a key feature in next generation wireless networks such as 3GPP's long term evolution advanced (LTE-Advanced), or the forthcoming IEEE 802.16j WiMAX standard. This paper presents, using game theory, a novel approach for the formation of the tree architecture that connects the RSs and their serving base station in the \emph{uplink} of the next generation wireless multi-hop systems. Unlike existing literature which mainly focused on performance analysis, we propose a distributed algorithm for studying the \emph{structure} and \emph{dynamics} of the network. We formulate a network formation game among the RSs whereby each RS aims to maximize a cross-layer utility function that takes into account the benefit from cooperative transmission, in terms of reduced bit error rate, and the costs in terms of the delay due to multi-hop transmission. For forming the tree structure, a distributed myopic algorithm is devised. Using the proposed algorithm, each RS can individually select the path that connects it to the BS through other RSs while optimizing its utility. We show the convergence of the algorithm into a Nash tree network, and we study how the RSs can adapt the network's topology to environmental changes such as mobility or the deployment of new mobile stations. Simulation results show that the proposed algorithm presents significant gains in terms of average utility per mobile station which is at least 17.1% better relatively to the case with no RSs and reaches up to 40.3% improvement compared to a nearest neighbor algorithm (for a network with 10 RSs). The results also show that the average number of hops does not exceed 3 even for a network with up to 25 RSs.Comment: IEEE Transactions on Communications, vol. 59, no. 9, pp. 2528-2542, September 201

    Coalitional Game Theory for Communication Networks: A Tutorial

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    Game theoretical techniques have recently become prevalent in many engineering applications, notably in communications. With the emergence of cooperation as a new communication paradigm, and the need for self-organizing, decentralized, and autonomic networks, it has become imperative to seek suitable game theoretical tools that allow to analyze and study the behavior and interactions of the nodes in future communication networks. In this context, this tutorial introduces the concepts of cooperative game theory, namely coalitional games, and their potential applications in communication and wireless networks. For this purpose, we classify coalitional games into three categories: Canonical coalitional games, coalition formation games, and coalitional graph games. This new classification represents an application-oriented approach for understanding and analyzing coalitional games. For each class of coalitional games, we present the fundamental components, introduce the key properties, mathematical techniques, and solution concepts, and describe the methodologies for applying these games in several applications drawn from the state-of-the-art research in communications. In a nutshell, this article constitutes a unified treatment of coalitional game theory tailored to the demands of communications and network engineers.Comment: IEEE Signal Processing Magazine, Special Issue on Game Theory, to appear, 2009. IEEE Signal Processing Magazine, Special Issue on Game Theory, to appear, 200

    Efficient design of WIMAX/802.16 mesh networks

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    Broadband wireless networks are becoming increasingly popular due to their fast and inexpensive deployment and their capabilities of providing flexible and ubiquitous Internet access. While the majority of existing broadband wireless networks are still exclusively limited to single hop access, it is the ability of these networks to forward data frames over multi-hop wireless routes which enabled them to easily extend the network coverage area. Unfortunately, achieving good multi- hop throughput has been challenging due to several factors, such as lossy wireless links caused by interference from concurrent transmissions, and intra-path interference caused by transmissions on successive hops along a single path. A wireless mesh network WMN consists of a number of stationary wireless mesh routers, forming a wireless backbone. The wireless mesh routers serve as access points (APs) for wireless mobile devices, and some of them also act as gateways to the Internet via high speed wireless links. Several technologies are currently being considered for mesh (multi-hop) networks, including, IEEE 802.11 (both single channel and multi-channel), IEEE 802.16/WiMAX, and next generation cellular networks (LTE). In this work, we focus on the IEEE 802.16. To maximize the network performance of mesh networks (e.g., throughput), it is essential to consider a cross-layer design, exploiting the dependency between protocol layers such as the routing network layer and the scheduling resource allocation MAC layer. Therefore this PhD thesis considers a cross-layer design approach for designing efficient wireless mesh networks; we first develop mathematical models (link-based and path-based) for the problem of joint routing tree construction and link scheduling in WiMAX-based mesh networks with the objective of minimizing the schedule length to satisfy a set of uplink and downlink demands. This is achieved by maximizing the number of concurrent active transmissions in the network by efficiently reusing the spectrum spatially. Second, we exploit the broadcasts nature of the wireless medium and enhance our design models by incorporating opportunistic network coding into the joint routing tree construction and link scheduling problem. Identifying coding-aware routing structures and utilizing the broadcasting feature of the wireless medium play an important role in realizing the achievable gain of network coding. Last, the uprising mobile WiMAX (802.16e amendment) has introduced more difficulties and challenges into the network design problem; thus, ensuring larger connection lifetime and better routing stability become of greater interest for the joint routing and scheduling problem. This is addressed by augmenting the previously designed models. Throughout this thesis, we assume centralized scheduling at the base station (BS) and we develop, for the joint problems, integer linear programming (ILP) models which require the enumeration of all feasible solutions to reach the optimal solution. Given their complexities, we rely on optimization decomposition methods using column generation for solving each model in an efficient way

    Methodologies for Analyzing Equilibria in Wireless Games

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    Under certain assumptions in terms of information and models, equilibria correspond to possible stable outcomes in conflicting or cooperative scenarios where rational entities interact. For wireless engineers, it is of paramount importance to be able to predict and even ensure such states at which the network will effectively operate. In this article, we provide non-exhaustive methodologies for characterizing equilibria in wireless games in terms of existence, uniqueness, selection, and efficiency.Comment: To appear in IEEE Signal Processing Magazine, Sep. 200

    RESOURCE ALLOCATION FOR WIRELESS RELAY NETWORKS

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    In this thesis, we propose several resource allocation strategies for relay networks in the context of joint power and bandwidth allocation and relay selection, and joint power allocation and subchannel assignment for orthogonal frequency division multiplexing (OFDM) and orthogonal frequency division multiple access (OFDMA) systems. Sharing the two best ordered relays with equal power between the two users over Rayleigh flat fading channels is proposed to establish full diversity order for both users. Closed form expressions for the outage probability, and bit error probability (BEP) performance measures for both amplify and forward (AF) and decode and forward (DF) cooperative communication schemes are developed for different scenarios. To utilize the full potentials of relay-assisted transmission in multi user systems, we propose a mixed strategy of AF relaying and direct transmission, where the user transmits part of the data using the relay, and the other part is transmitted using the direct link. The resource allocation problem is formulated to maximize the sum rate. A recursive algorithm alternating between power allocation and bandwidth allocation steps is proposed to solve the formulated resource allocation problem. Due to the conflict between limited wireless resources and the fast growing wireless demands, Stackelberg game is proposed to allocate the relay resources (power and bandwidth) between competing users, aiming to maximize the relay benefits from selling its resources. We prove the uniqueness of Stackelberg Nash Equilibrium (SNE) for the proposed game. We develop a distributed algorithm to reach SNE, and investigate the conditions for the stability of the proposed algorithm. We propose low complexity algorithms for AF-OFDMA and DF-OFDMA systems to assign the subcarriers to the users based on high SNR approximation aiming to maximize the weighted sum rate. Auction framework is proposed to devise competition based solutions for the resource allocation of AF-OFDMA aiming tomaximize either vi the sum rate or the fairness index. Two auction algorithms are proposed; sequential and one-shot auctions. In sequential auction, the users evaluate the subcarrier based on the rate marginal contribution. In the one-shot auction, the users evaluate the subcarriers based on an estimate of the Shapley value and bids on all subcarriers at once

    Theoretical Foundations of Mobile Flexible Networks

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    Mobile Ad-Hoc Networks

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    Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

    Game Theory in Communications:a Study of Two Scenarios

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    Multi-user communication theory typically studies the fundamental limits of communication systems, and considers communication schemes that approach or even achieve these limits. The functioning of many such schemes assumes that users always cooperate, even when it is not in their own best interest. In practice, this assumption need not be fulfilled, as rational communication participants are often only interested in maximizing their own communication experience, and may behave in an undesirable manner from the system's point of view. Thus, communication systems may operate differently than intended if the behavior of individual participants is not taken into account. In this thesis, we study how users make decisions in wireless settings, by considering their preferences and how they interact with each other. We investigate whether the outcomes of their decisions are desirable, and, if not, what can be done to improve them. In particular, we focus on two related issues. The first is the decision-making of communication users in the absence of any central authority, which we consider in the context of the Gaussian multiple access channel. The second is the pricing of wireless resources, which we consider in the context of the competition of wireless service providers for users who are not contractually tied to any provider, but free to choose the one offering the best tradeoff of parameters. In the first part of the thesis, we model the interaction of self-interested users in a Gaussian multiple access channel using non-cooperative game theory. We demonstrate that the lack of infrastructure leads to an inefficient outcome for users who interact only once, specifically due to the lack of coordination between users. Using evolutionary game theory, we show that this inefficient outcome would also arise as a result of repeated interaction of many individuals over time. On the other hand, if the users correlate their decoding schedule with the outcome of some publicly observed (pseudo) random variable, the resulting outcome is efficient. This shows that sometimes it takes very little intervention on the part of the system planner to make sure that users choose a desirable operating point. In the second part of the thesis, we consider the competition of wireless service providers for users who are free to choose their service provider based on their channel parameters and the resource price. We model this situation as a two-stage game where the providers announce unit resource prices in the first stage and the users choose how much resource they want to purchase from each provider in the second stage. Under fairly general conditions, we show that the competitive interaction of users and providers results in socially optimal resource allocation. We also provide a decentralized primal-dual algorithm and prove its convergence to the socially optimal outcome
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