Are Hjørungnes

Coalitional game theory for communication networks

In 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.

Complex-Valued Matrix Differentiation: Techniques and Key Results

A systematic theory is introduced for finding the derivatives of complex-valued matrix functions with respect to a complex-valued matrix variable and the complex conjugate of this variable. In the framework introduced, the differential of the complex-valued matrix function is used to identify the derivatives of this function. Matrix differentiation results are derived and summarized in tables which can be exploited in a wide range of signal processing related situations

Coalitional Games for Distributed Collaborative Spectrum Sensing in Cognitive Radio Networks

Collaborative spectrum sensing among secondary users (SUs) in cognitive networks is shown to yield a significant performance improvement. However, there exists an inherent trade off between the gains in terms of probability of detection of the primary user (PU) and the costs in terms of false alarm probability. In this paper, we study the impact of this trade off on the topology and the dynamics of a network of SUs seeking to reduce the interference on the PU through collaborative sensing. Moreover, while existing literature mainly focused on centralized solutions for collaborative sensing, we propose distributed collaboration strategies through game theory. We model the problem as a non-transferable coalitional game, and propose a distributed algorithm for coalition formation through simple merge and split rules. Through the proposed algorithm, SUs can autonomously collaborate and self-organize into disjoint independent coalitions, while maximizing their detection probability taking into account the cooperation costs (in terms of false alarm). We study the stability of the resulting network structure, and show that a maximum number of SUs per formed coalition exists for the proposed utility model. Simulation results show that the proposed algorithm allows a reduction of up to 86.6% of the average missing probability per SU (probability of missing the detection of the PU) relative to the non-cooperative case, while maintaining a certain false alarm level. In addition, through simulations, we compare the performance of the proposed distributed solution with respect to an optimal centralized solution that minimizes the average missing probability per SU. Finally, the results also show how the proposed algorithm autonomously adapts the network topology to environmental changes such as mobility.

A distributed coalition formation framework for fair user cooperation in wireless networks

Cooperation in wireless networks allows single antenna devices to improve their performance by forming virtual multiple antenna systems. However, performing a distributed and fair cooperation constitutes a major challenge. In this work, we model cooperation in wireless networks through a game theoretical algorithm derived from a novel concept from coalitional game theory. A simple and distributed merge-and-split algorithm is constructed to form coalition groups among single antenna devices and to allow them to maximize their utilities in terms of rate while accounting for the cost of cooperation in terms of power. The proposed algorithm enables the users to self-organize into independent disjoint coalitions and the resulting clustered network structure is characterized through novel stability notions. In addition, we prove the convergence of the algorithm and we investigate how the network structure changes when different fairness criteria are chosen for apportioning the coalition worth among its members. Simulation results show that the proposed algorithm can improve the individual users payoff up to 40.42% as well as efficiently cope with the mobility of the distributed users.

Rethinking the Secrecy Outage Formulation: A Secure Transmission Design Perspective

This letter studies information-theoretic security without knowing the eavesdroppers channel fading state. We present an alternative secrecy outage formulation to measure the probability that message transmissions fail to achieve perfect secrecy. Using this formulation, we design two transmission schemes that satisfy the given security requirement while achieving good throughput performance.

On the Throughput Cost of Physical Layer Security in Decentralized Wireless Networks

This paper studies the throughput of large-scale decentralized wireless networks with physical layer security constraints. In particular, we are interested in the question of how much throughput needs to be sacrificed for achieving a certain level of security. We consider random networks where the legitimate nodes and the eavesdroppers are distributed according to independent two-dimensional Poisson point processes. The transmission capacity framework is used to characterize the area spectral efficiency of secure transmissions with constraints on both the quality of service (QoS) and the level of security. This framework illustrates the dependence of the network throughput on key system parameters, such as the densities of legitimate nodes and eavesdroppers, as well as the QoS and security constraints. One important finding is that the throughput cost of achieving a moderate level of security is quite low, while throughput must be significantly sacrificed to realize a highly secure network. We also study the use of a secrecy guard zone, which is shown to give a significant improvement on the throughput of networks with high security requirements.

Pilot Contamination for Active Eavesdropping

Existing studies on physical layer security often assume the availability of perfect channel state information (CSI) and overlook the importance of channel training needed for obtaining the CSI. In this letter, we discuss how an active eavesdropper can attack the training phase in wireless communication to improve its eavesdropping performance. We derive a new security attack from the pilot contamination phenomenon, which targets at systems using reverse training to obtain the CSI at the transmitter for precoder design. This attack changes the precoder used by the legitimate transmitter in a controlled manner to strengthen the signal reception at the eavesdropper during data transmission. Furthermore, we discuss an efficient use of the transmission energy of an advanced full-duplex eavesdropper to simultaneously achieve a satisfactory eavesdropping performance whilst degrading the detection performance of the legitimate receiver.

Coalition Formation Games for Distributed Cooperation Among Roadside Units in Vehicular Networks

Vehicle-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.

Coalition Formation Games for Collaborative Spectrum Sensing

Collaborative 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.

Joint iterative interference cancellation and parameter estimation for cdma systems

This letter proposes a unified approach to joint iterative parameter estimation and interference cancellation (IC) for uplink CDMA systems in multipath channels. A unified framework is presented in which the IC problem is formulated as an optimization problem of an IC parameter vector for each stage and user. We also propose detectors based on a least-squares (LS) joint optimization method for estimating the linear receiver filter front-end, the IC, and the channel parameters. Simulations for the uplink of a synchronous DS-CDMA system show that the proposed methods significantly outperform the best known IC schemes.