Resource Allocation for Interference Management in Wireless Networks

Interference in wireless networks is a major problem that impacts system performance quite substantially. Combined with the fact that the spectrum is limited and scarce, the performance and reliability of wireless systems significantly deteriorates and, hence, communication sessions are put at the risk of failure. In an attempt to make transmissions resilient to interference and, accordingly, design robust wireless systems, a diverse set of interference mitigation techniques are investigated in this dissertation. Depending on the rationale motivating the interfering node, interference can be divided into two categories, communication and jamming. For communication interference such as the interference created by legacy users(e.g., primary user transmitters in a cognitive radio network) at non-legacy or unlicensed users(e.g.,secondary user receivers), two mitigation techniques are presented in this dissertation. One exploits permutation trellis codes combined with M-ary frequency shift keying in order to make SU transmissions resilient to PUs’ interference, while the other utilizes frequency allocation as a mitigation technique against SU interference using Matching theory. For jamming interference, two mitigation techniques are also investigated here. One technique exploits time and structures a jammer mitigation framework through an automatic repeat request protocol. The other one utilizes power and, following a game-theoretic framework, employs a defense strategy against jamming based on a strategic power allocation. Superior performance of all of the proposed mitigation techniques is shown via numerical results

Mathematical optimization and game theoretic methods for radar networks

Radar systems are undoubtedly included in the hall of the most momentous discoveries of the previous century. Although radars were initially used for ship and aircraft detection, nowadays these systems are used in highly diverse fields, expanding from civil aviation, marine navigation and air-defence to ocean surveillance, meteorology and medicine. Recent advances in signal processing and the constant development of computational capabilities led to radar systems with impressive surveillance and tracking characteristics but on the other hand the continuous growth of distributed networks made them susceptible to multisource interference. This thesis aims at addressing vulnerabilities of modern radar networks and further improving their characteristics through the design of signal processing algorithms and by utilizing convex optimization and game theoretic methods. In particular, the problems of beamforming, power allocation, jammer avoidance and uncertainty within the context of multiple-input multiple-output (MIMO) radar networks are addressed. In order to improve the beamforming performance of phased-array and MIMO radars employing two-dimensional arrays of antennas, a hybrid two-dimensional Phased-MIMO radar with fully overlapped subarrays is proposed. The work considers both adaptive (convex optimization, CAPON beamformer) and non-adaptive (conventional) beamforming techniques. The transmit, receive and overall beampatterns of the Phased-MIMO model are compared with the respective beampatterns of the phased-array and the MIMO schemes, proving that the hybrid model provides superior capabilities in beamforming. By incorporating game theoretic techniques in the radar field, various vulnerabilities and problems can be investigated. Hence, a game theoretic power allocation scheme is proposed and a Nash equilibrium analysis for a multistatic MIMO network is performed. A network of radars is considered, organized into multiple clusters, whose primary objective is to minimize their transmission power, while satisfying a certain detection criterion. Since no communication between the clusters is assumed, non-cooperative game theoretic techniques and convex optimization methods are utilized to tackle the power adaptation problem. During the proof of the existence and the uniqueness of the solution, which is also presented, important contributions on the SINR performance and the transmission power of the radars have been derived. Game theory can also been applied to mitigate jammer interference in a radar network. Hence, a competitive power allocation problem for a MIMO radar system in the presence of multiple jammers is investigated. The main objective of the radar network is to minimize the total power emitted by the radars while achieving a specific detection criterion for each of the targets-jammers, while the intelligent jammers have the ability to observe the radar transmission power and consequently decide its jamming power to maximize the interference to the radar system. In this context, convex optimization methods, noncooperative game theoretic techniques and hypothesis testing are incorporated to identify the jammers and to determine the optimal power allocation. Furthermore, a proof of the existence and the uniqueness of the solution is presented. Apart from resource allocation applications, game theory can also address distributed beamforming problems. More specifically, a distributed beamforming and power allocation technique for a radar system in the presence of multiple targets is considered. The primary goal of each radar is to minimize its transmission power while attaining an optimal beamforming strategy and satisfying a certain detection criterion for each of the targets. Initially, a strategic noncooperative game (SNG) is used, where there is no communication between the various radars of the system. Subsequently, a more coordinated game theoretic approach incorporating a pricing mechanism is adopted. Furthermore, a Stackelberg game is formulated by adding a surveillance radar to the system model, which will play the role of the leader, and thus the remaining radars will be the followers. For each one of these games, a proof of the existence and uniqueness of the solution is presented. In the aforementioned game theoretic applications, the radars are considered to know the exact radar cross section (RCS) parameters of the targets and thus the exact channel gains of all players, which may not be feasible in a real system. Therefore, in the last part of this thesis, uncertainty regarding the channel gains among the radars and the targets is introduced, which originates from the RCS fluctuations of the targets. Bayesian game theory provides a framework to address such problems of incomplete information. Hence, a Bayesian game is proposed, where each radar egotistically maximizes its SINR, under a predefined power constraint

Protecting Secret Key Generation Systems Against Jamming: Energy Harvesting and Channel Hopping Approaches

Jamming attacks represent a critical vulnerability for wireless secret key generation (SKG) systems. In this paper, two counter-jamming approaches are investigated for SKG systems: first, the employment of energy harvesting (EH) at the legitimate nodes to turn part of the jamming power into useful communication power, and, second, the use of channel hopping or power spreading in block fading channels to reduce the impact of jamming. In both cases, the adversarial interaction between the pair of legitimate nodes and the jammer is formulated as a two-player zero-sum game and the Nash and Stackelberg equilibria are characterized analytically and in closed form. In particular, in the case of EH receivers, the existence of a critical transmission power for the legitimate nodes allows the full characterization of the game's equilibria and also enables the complete neutralization of the jammer. In the case of channel hopping versus power spreading techniques, it is shown that the jammer's optimal strategy is always power spreading while the legitimate nodes should only use power spreading in the high signal-to-interference ratio (SIR) regime. In the low SIR regime, when avoiding the jammer's interference becomes critical, channel hopping is optimal for the legitimate nodes. Numerical results demonstrate the efficiency of both counter-jamming measures

Protecting Secret Key Generation Systems Against Jamming: Energy Harvesting and Channel Hopping Approaches

Jamming attacks represent a critical vulnerability for wireless secret key generation (SKG) systems. In this paper, two counter-jamming approaches are investigated for SKG systems: first, the employment of energy harvesting (EH) at the legitimate nodes to turn part of the jamming power into useful communication power, and, second, the use of channel hopping or power spreading in block fading channels to reduce the impact of jamming. In both cases, the adversarial interaction between the pair of legitimate nodes and the jammer is formulated as a two-player zero-sum game and the Nash and Stackelberg equilibria are characterized analytically and in closed form. In particular, in the case of EH receivers, the existence of a critical transmission power for the legitimate nodes allows the full characterization of the game's equilibria and also enables the complete neutralization of the jammer. In the case of channel hopping versus power spreading techniques, it is shown that the jammer's optimal strategy is always power spreading while the legitimate nodes should only use power spreading in the high signal-to-interference ratio (SIR) regime. In the low SIR regime, when avoiding the jammer's interference becomes critical, channel hopping is optimal for the legitimate nodes. Numerical results demonstrate the efficiency of both counter-jamming measures

Physical layer security jamming : Theoretical limits and practical designs in wireless networks

Physical layer security has been recently recognized as a promising new design paradigm to provide security in wireless networks. In addition to the existing conventional cryptographic methods, physical layer security exploits the dynamics of fading channels to enhance secured wireless links. In this approach, jamming plays a key role by generating noise signals to confuse the potential eavesdroppers, and significantly improves quality and reliability of secure communications between legitimate terminals. This article presents theoretical limits and practical designs of jamming approaches for physical layer security. In particular, the theoretical limits explore the achievable secrecy rates of user cooperation based jamming whilst the centralized, and game theoretic based precoding techniques are reviewed for practical implementations. In addition, the emerging wireless energy harvesting techniques are exploited to harvest the required energy to transmit jamming signals. Future directions of these approaches, and the associated research challenges are also briefly outlined

An enhanced OFDM light weight physical layer encryption scheme

The broadcast nature of wireless networks makes them susceptible to attacks by eavesdroppers than wired networks. Any untrusted node can eavesdrop on the medium, listen to transmissions and obtain sensitive information within the wireless network. In this paper, we propose a new mechanism which combines the advantages of two techniques namely iJam and OFDM phase encryption. Our modified mechanism makes iJam more bandwidth efficient by using Alamouti scheme to take advantage of the repetition inherent in its implementation. The adversary model is extended to the active adversary case, which has not been done in the original work of iJam and OFDM phase encryption. We propose, through a max min optimization model, a framework that maximizes the secrecy rate by means of a friendly jammer. We formulate a Zero-Sum game that captures the strategic decision making between the transmitter receiver pair and the adversary. We apply the fictitious play (FP) algorithm to reach the Nash equilibria (NE) of the game. Our simulation results show a significant improvement in terms of the ability of the eavesdropper to benefit from the received information over the traditional schemes, i.e. iJam or OFDM phase encryption

Optimal Scanning Bandwidth Strategy Incorporating Uncertainty about Adversary's Characteristics

In this paper we investigate the problem of designing a spectrum scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem we model the situation as two games, between a Scanner and an Invader, and solve them sequentially. The first game is formulated to design the optimal (in maxmin sense) scanning algorithm, while the second one allows one to find the optimal values of the parameters for the algorithm depending on parameters of the network. These games provide solutions for two dilemmas that the rivals face. The Invader's dilemma consists of the following: the more bandwidth the Invader attempts to use leads to a larger payoff if he is not detected, but at the same time also increases the probability of being detected and thus fined. Similarly, the Scanner faces a dilemma: the wider the bandwidth scanned, the higher the probability of detecting the Invader, but at the expense of increasing the cost of building the scanning system. The equilibrium strategies are found explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the type of the Invader's award. This discontinuity of the fine means that the network provider has to take into account a human/social factor since some threshold values of fine could be very sensible for the Invader, while in other situations simply increasing the fine has minimal deterrence impact. Also we show how incomplete information about the Invader's technical characteristics and reward (e.g. motivated by using different type of application, say, video-streaming or downloading files) can be incorporated into scanning strategy to increase its efficiency.Comment: This is the last draft version of the paper. Revised version of the paper was published in EAI Endorsed Transactions on Mobile Communications and Applications, Vol. 14, Issue 5, 2014, doi=10.4108/mca.2.5.e6. arXiv admin note: substantial text overlap with arXiv:1310.724

A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks

A Mixed-Integer Programming Approach for Jammer Placement Problems for Flow-Jamming Attacks on Wireless Communication Networks

In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks