Browsing by Author "Saad, Walid"
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Item A Cooperative Bayesian Nonparametric Framework for Primary User Activity Monitoring in Cognitive Radio Networks(IEEE Journal on Selected Areas in Communications, 2/2/2012) Saad, Walid; Han, Zhu; Poor, H. Vincent; Ba?ar, Tamer; Song, Jin BinThis paper introduces a novel approach that enables a number of cognitive radio devices that are observing the availability pattern of a number of primary users (PUs), to cooperate and use Bayesian nonparametric techniques to estimate the distributions of the PUs' activity pattern. To address this problem, a coalitional game is formulated between the cognitive devices and an algorithm for cooperative coalition formation is proposed. It is shown that the proposed coalition formation algorithm allows the cognitive nodes that are experiencing a similar behavior from some PUs to self-organize into disjoint, independent coalitions. Inside each coalition, the cooperative cognitive nodes use Bayesian nonparametric techniques so as to improve the accuracy of the estimated PUs' activity distributions. Simulation results show that the proposed algorithm significantly improves the estimates of the PUs' activity patterns.Item A Game-Theoretic Approach to Energy Trading in the Smart Grid(IEEE Transactions on Smart Grid, 4/15/2014) Wang, Yunpeng; Saad, Walid; Han, Zhu; Poor, H. Vincent; Ba?ar, TamerElectric storage units constitute a key element in the emerging smart grid system. In this paper, the interactions and energy trading decisions of a number of geographically distributed storage units are studied using a novel framework based on game theory. In particular, a noncooperative game is formulated between storage units, such as plug-in hybrid electric vehicles, or an array of batteries that are trading their stored energy. Here, each storage unit's owner can decide on the maximum amount of energy to sell in a local market so as to maximize a utility that reflects the tradeoff between the revenues from energy trading and the accompanying costs. Then in this energy exchange market between the storage units and the smart grid elements, the price at which energy is traded is determined via an auction mechanism. The game is shown to admit at least one Nash equilibrium and a novel algorithm that is guaranteed to reach such an equilibrium point is proposed. Simulation results show that the proposed approach yields significant performance improvements, in terms of the average utility per storage unit, reaching up to 130.2% compared to a conventional greedy approach.Item Coalition Formation Games for Collaborative Spectrum Sensing(IEEE Transactions on Vehicular Technology, 10/21/2010) Saad, Walid; Han, Zhu; Ba?ar, Tamer; Debbah, Mérouane; Hjorungnes, AreCollaborative spectrum sensing (CSS) between secondary users (SUs) in cognitive networks exhibits an inherent tradeoff between minimizing the probability of missing the detection of the primary user (PU) and maintaining a reasonable false alarm probability (e.g., for maintaining good spectrum utilization). In this paper, we study the impact of this tradeoff on the network structure and the cooperative incentives of the SUs that seek to cooperate to improve their detection performance. We model the CSS problem as a nontransferable coalitional game, and we propose distributed algorithms for coalition formation (CF). First, we construct a distributed CF algorithm that allows the SUs to self-organize into disjoint coalitions while accounting for the CSS tradeoff. Then, the CF algorithm is complemented with a coalitional voting game to enable distributed CF with detection probability (CF-PD) guarantees when required by the PU. The CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e., coalitions that achieve the target detection probability with minimal costs. For both algorithms, we study and prove various properties pertaining to network structure, adaptation to mobility, and stability. Simulation results show that CF reduces the average probability of miss per SU up to 88.45%, relative to the noncooperative case, while maintaining a desired false alarm. For CF-PD, the results show that up to 87.25% of the SUs achieve the required detection probability through MWCs.Item Coalition Formation Games for Distributed Cooperation Among Roadside Units in Vehicular Networks(IEEE Journal on Selected Areas in Communications, 12/30/2010) Saad, Walid; Han, Zhu; Hjorungnes, Are; Niyato, Dusit; Hossain, EkramVehicle-to-roadside (V2R) communications enable vehicular networks to support a wide range of applications for enhancing the efficiency of road transportation. While existing work focused on non-cooperative techniques for V2R communications between vehicles and roadside units (RSUs), this paper investigates novel cooperative strategies among the RSUs in a vehicular network. We propose a scheme whereby, through cooperation, the RSUs in a vehicular network can coordinate the classes of data being transmitted through V2R communication links to the vehicles. This scheme improves the diversity of the information circulating in the network while exploiting the underlying content-sharing vehicle-to-vehicle communication network. We model the problem as a coalition formation game with transferable utility and we propose an algorithm for forming coalitions among the RSUs. For coalition formation, each RSU can take an individual decision to join or leave a coalition, depending on its utility which accounts for the generated revenues and the costs for coalition coordination. We show that the RSUs can self-organize into a Nash-stable partition and adapt this partition to environmental changes. Simulation results show that, depending on different scenarios, coalition formation presents a performance improvement, in terms of the average payoff per RSU, ranging between 20.5% and 33.2%, relative to the non-cooperative case.Item Coalitional game theory for communication networks(IEEE Signal Processing Magazine, 5/25/2009) Saad, Walid; Han, Zhu; Debbah, Mérouane; Hjorungnes, Are; Ba?ar, TamerIn this tutorial, we provided a comprehensive overview of coalitional game theory, and its usage in wireless and communication networks. For this purpose, we introduced a novel classification of coalitional games by grouping the sparse literature into three distinct classes of games: canonical coalitional games, coalition formation games, and coalitional graph games. For each class, we explained in details the fundamental properties, discussed the main solution concepts, and provided an in-depth analysis of the methodologies and approaches for using these games in both game theory and communication applications. The presented applications have been carefully selected from a broad range of areas spanning a diverse number of research problems. The tutorial also sheds light on future opportunities for using the strong analytical tool of coalitional games in a number of applications. In a nutshell, this article fills a void in existing communications literature, by providing a novel tutorial on applying coalitional game theory in communication networks through comprehensive theory and technical details as well as through practical examples drawn from both game theory and communication application.Item Coalitional Games in Partition Form for Joint Spectrum Sensing and Access in Cognitive Radio Networks(IEEE Journal of Selected Topics in Signal Processing, 10/10/2011) Saad, Walid; Han, Zhu; Zheng, Rong; Hjorungnes, Are; Ba?ar, Tamer; Poor, H. VincentUnlicensed secondary users (SUs) in cognitive radio networks are subject to an inherent tradeoff between spectrum sensing and spectrum access. Although each SU has an incentive to sense the primary user (PU) channels for locating spectrum holes, this exploration of the spectrum can come at the expense of a shorter transmission time, and, hence, a possibly smaller capacity for data transmission. This paper investigates the impact of this tradeoff on the cooperative strategies of a network of SUs that seek to cooperate in order to improve their view of the spectrum (sensing), reduce the possibility of interference among each other, and improve their transmission capacity (access). The problem is modeled as a coalitional game in partition form and an algorithm for coalition formation is proposed. Using the proposed algorithm, the SUs can make individual distributed decisions to join or leave a coalition while maximizing their utilities which capture the average time spent for sensing as well as the capacity achieved while accessing the spectrum. It is shown that, by using the proposed algorithm, the SUs can self-organize into a network partition composed of disjoint coalitions, with the members of each coalition cooperating to jointly optimize their sensing and access performance. Simulation results show the performance improvement that the proposed algorithm yields with respect to the noncooperative case. The results also show how the algorithm allows the SUs to self-adapt to changes in the environment such as changes in the traffic of the PUs, or slow mobility.Item Coalitional Games with Overlapping Coalitions for Interference Management in Small Cell Networks(IEEE Transactions on Wireless Communications, 4/4/2014) Zhang, Zengfeng; Song, Lingyang; Han, Zhu; Saad, WalidIn this paper, we study the problem of cooperative interference management in an OFDMA two-tier small cell network. In particular, we propose a novel approach for allowing the small cells to cooperate, so as to optimize their sum-rate, while cooperatively satisfying their maximum transmit power constraints. Unlike existing work which assumes that only disjoint groups of cooperative small cells can emerge, we formulate the small cells' cooperation problem as a coalition formation game with overlapping coalitions. In this game, each small cell base station can choose to participate in one or more cooperative groups (or coalitions) simultaneously, so as to optimize the tradeoff between the benefits and costs associated with cooperation. We study the properties of the proposed overlapping coalition formation game and we show that it exhibits negative externalities due to interference. Then, we propose a novel decentralized algorithm that allows the small cell base stations to interact and self-organize into a stable overlapping coalitional structure. Simulation results show that the proposed algorithm results in a notable performance advantage in terms of the total system sum-rate, relative to the noncooperative case and the classical algorithms for coalitional games with non-overlapping coalitions.Item Contract-based Incentive Mechanism for LTE over Unlicensed Channels(IEEE Transactions on Communications, 4/11/2019) Hamidouche, Kenza; Saad, Walid; Debbah, Mérouane; Thai, My T.; Han, ZhuIn this paper, a novel economic approach, based on the framework of contract theory, is proposed for providing incentives for LTE over unlicensed channels (LTE-U) in cellular-networks. In this model, a mobile network operator (MNO) designs and offers a set of contracts to the users to motivate them to accept being served over the unlicensed bands. A practical model in which the information about the quality-of-service (QoS) required by every user is not known to the MNO and other users, is considered. For this contractual model, the closed-form expression of the price charged by the MNO for every user is derived and the problem of spectrum allocation is formulated as a matching game with incomplete information. For the matching problem, a distributed algorithm is proposed to assign the users to the licensed and unlicensed spectra. Simulation results show that the proposed pricing mechanism can increase the fraction of users that achieve their QoS requirements by up to 45% compared to classical algorithms that do not account for users requirements. Moreover, the performance of the proposed algorithm in the case of incomplete information is shown to approach the performance of the same mechanism with complete information.Item Device Fingerprinting in Wireless Networks: Challenges and Opportunities(IEEE Communications Surveys & Tutorials, 9/3/2015) Xu, Qiang; Zheng, Rong; Saad, Walid; Han, ZhuNode forgery or impersonation, in which legitimate cryptographic credentials are captured by an adversary, constitutes one major security threat facing wireless networks. The fact that mobile devices are prone to be compromised and reverse engineered significantly increases the risk of such attacks in which adversaries can obtain secret keys on trusted nodes and impersonate the legitimate node. One promising approach toward thwarting these attacks is through the extraction of unique fingerprints that can provide a reliable and robust means for device identification. These fingerprints can be extracted from transmitted signal by analyzing information across the protocol stack. In this paper, the first unified and comprehensive tutorial in the area of wireless device fingerprinting for security applications is presented. In particular, we aim to provide a detailed treatment on developing novel wireless security solutions using device fingerprinting techniques. The objectives are three-fold: (i) to introduce a comprehensive taxonomy of wireless features that can be used in fingerprinting, (ii) to provide a systematic review on fingerprint algorithms including both white-list based and unsupervised learning approaches, and (iii) to identify key open research problems in the area of device fingerprinting and feature extraction, as applied to wireless security.Item Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents(IEEE Transactions on Mobile Computing, 12/23/2010) Saad, Walid; Han, Zhu; Ba?ar, Tamer; Debbah, Mérouane; Hjorungnes, AreAutonomous wireless agents such as unmanned aerial vehicles, mobile base stations, cognitive devices, or self-operating wireless nodes present a great potential for deployment in next-generation wireless networks. While current literature has been mainly focused on the use of agents within robotics or software engineering applications, this paper proposes a novel usage model for self-organizing agents suitable for wireless communication networks. In the proposed model, a number of agents are required to collect data from several arbitrarily located tasks. Each task represents a queue of packets that require collection and subsequent wireless transmission by the agents to a central receiver. The problem is modeled as a hedonic coalition formation game between the agents and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of agents, designated as collectors, which move between the different tasks present in the coalition, collect and transmit the packets. Within each coalition, some agents might also take the role of a relay for improving the packet success rate of the transmission. The proposed hedonic coalition formation algorithm allows the tasks and the agents to take distributed decisions to join or leave a coalition, based on the achieved benefit in terms of effective throughput, and the cost in terms of polling system delay. As a result of these decisions, the agents and tasks structure themselves into independent disjoint coalitions which constitute a Nash-stable network partition. Moreover, the proposed coalition formation algorithm allows the agents and tasks to adapt the topology to environmental changes, such as the arrival of new tasks, the removal of existing tasks, or the mobility of the tasks. Simulation results show how the proposed algorithm allows the agents and tasks to self-organize into independent coalitions, while improving the performance, in terms of average player (agent or task) payoff, of at least 30.26 percent (for a network of five agents with up to 25 tasks) relatively to a scheme that allocates nearby tasks equally among agents.Item Joint Communication, Computation, Caching, and Control in Big Data Multi-access Edge Computing(IEEE Transactions on Mobile Computing, 3/29/2019) Ndikumana, Anselme; Tran, Nguyen H.; Ho, Tai Manh; Han, Zhu; Saad, Walid; Niyato, Dusit; Hong, Choong SeonThe concept of Multi-access Edge Computing (MEC) has been recently introduced to supplement cloud computing by deploying MEC servers to the network edge so as to reduce the network delay and alleviate the load on cloud data centers. However, compared to the resourceful cloud, MEC server has limited resources. When each MEC server operates independently, it cannot handle all computational and big data demands stemming from users' devices. Consequently, the MEC server cannot provide significant gains in overhead reduction of data exchange between users' devices and remote cloud. Therefore, joint Computing, Caching, Communication, and Control (4C) at the edge with MEC server collaboration is needed. To address these challenges, in this paper, the problem of joint 4C in big data MEC is formulated as an optimization problem whose goal is to jointly optimize a linear combination of the bandwidth consumption and network latency. However, the formulated problem is shown to be non-convex. As a result, a proximal upper bound problem of the original formulated problem is proposed. To solve the proximal upper bound problem, the block successive upper bound minimization method is applied. Simulation results show that the proposed approach satisfies computation deadlines and minimizes bandwidth consumption and network latency.Item Matching theory for future wireless networks: fundamentals and applications(IEEE Communications Magazine, 5/14/2015) Gu, Yunan; Saad, Walid; Bennis, Mehdi; Debbah, Mérouane; Han, ZhuThe emergence of novel wireless networking paradigms such as small cell and cognitive radio networks has forever transformed the way in which wireless systems are operated. In particular, the need for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many emerging wireless systems. In this article, the first comprehensive tutorial on the use of matching theory, a Nobel Prize winning framework, for resource management in wireless networks is developed. To cater for the unique features of emerging wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then the key solution concepts and algorithmic implementations of this framework are exposed. The developed concepts are applied in three important wireless networking areas in order to demonstrate the usefulness of this analytical tool. Results show how matching theory can effectively improve the performance of resource allocation in all three applications discussed.Item Matching Theory Framework for 5G Wireless Communications(2016-12) Gu, Yunan; Han, Zhu; Saad, Walid; Prasad, Saurabh; Qian, Lijun; Pan, MiaoThe prevalence of high-performance mobile devices such as smartphones and tablets has brought fundamental changes to the existing wireless networks. The growth of multimedia and location-based mobile services has exponentially increased the network congestion and the demands for more wireless resources. The extremely high computational complexity and communication overhead resulting from the conventional centralized resource management methods are no longer suitable to capture the scale of tomorrow’s wireless networks. As a result, the resource management in next-generation networks is shifting from the centralized optimization to the self-organizing solutions. The goal of this thesis is to demonstrate the effectiveness of matching theory, a powerful operational research framework, for solving the wireless resource allocation problems in a distributed manner. Matching theory, as a Nobel-prize winning framework, has already been widely used in many economic fields. More recently, matching theory has been shown to have a promising potential for modeling and analyzing wireless resource allocation problems due to three reasons: (1) it offers suitable models that can inherently capture various wireless communication features; (2) the ability to use notions, such as preference relations, that can interpret complex system requirements; (3) it provides low-complexity and near-optimal matching algorithms while guaranteeing the system stability. This dissertation provides a theoretical research of implementing the matching theory into the wireless communication fields. The main contributions of this dissertation are summarized as follows. An overview of the basic concepts, classifications, and models of the matching theory is provided. Furthermore, comparisons with existing mathematical solutions for the resource allocation problems in the wireless networks are conducted. Applications of matching theory in the wireless communications are studied. Especially, the stable marriage model, the student project allocation model and so on are introduced and applied to solve the resource allocation problems, such as the device-to-device (D2D) communication, LTE-Unlicensed, and so on. Both theoretical and numerical analysis are provided to show that matching theory can model complex system requirements, and also provide semi-distributive matching algorithms to achieve stable and close-optimal results. The potential and challenges of the matching theory for designing resource allocation mechanisms in the future wireless networks are discussed.Item Network Formation Games Among Relay Stations in Next Generation Wireless Networks(IEEE Transactions on Communications, 6/30/2011) Saad, Walid; Han, Zhu; Ba?ar, Tamer; Debbah, Mérouane; Hjorungnes, AreThe 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 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 structure and 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.Item Overlapping coalition formation games for emerging communication networks(IEEE Network, 9/29/2016) Wang, Tianyu; Song, Lingyang; Han, Zhu; Saad, Walidhomogenous architectures into a mix of various technologies, in which the network devices are densely and randomly deployed in a decentralized and heterogenous architecture. This shift in network architecture requires network devices to become more autonomous and, potentially, cooperate with one another. Such cooperation can, for example, take place between interfering small access points that seek to coordinate their radio resource allocation, nearby single-antenna users that can cooperatively perform virtual MIMO communications, or even unlicensed users that wish to cooperatively sense the spectrum of licensed users. Such cooperative mechanisms involve the simultaneous sharing and distribution of resources among a number of overlapping cooperative groups or coalitions. In this article, a novel mathematical framework from cooperative games, dubbed overlapping coalition formation games (OCF games), is introduced to model and solve such cooperative scenarios. First, the concepts of OCF games are presented, and then several algorithmic aspects are studied for two main classes of OCF games. Subsequently, two example applications, interference management and cooperative spectrum sensing, are discussed in detail to show how the proposed models and algorithms can be used in future scenarios of wireless systems. Finally, we conclude by providing an overview on future directions and applications of OCF games.