In this thesis, we address the statistics of mutual information of amplify-and-forward (AF) multiple-input multiple-output (MIMO) two-hop relay channels, where the source terminal (ST), relay terminal (RT) and destination terminal (DT) are equipped with a number of correlated antennas and there is a line-of-sight (LOS) component (Rician fading) of each link. To the best of our knowledge, deriving analytical expressions for the statistics of mutual information of the relay channel is difficult and still unsolvable. To circumvent the mathematical difficulties, we consider this problem under the large-system regimen in which the numbers of antennas at the transmitter and receiver go to infinity with a fixed ratio. In the large-system regimen, this thesis has made the following contributions: 1) We get the mean and the variance of the mutual information of the concerned relay channel. 2) We show that the mutual information distribution converges to the Gaussian distribution. The analytical results are derived by mean of two powerful tools developed in the context of theoretical physics: emph{saddle-point approximation} and emph{superanalysis}. The derived analytical results are very general and can degenerate to several previously results as special cases. From a degenerated case, we realize that the previous result by Wagner {em et al.} cite{Wag-08} is wrong and thus we provide the corrected result. Finally, Simulation results demonstrate that even for a moderate number of antennas at each end, the proposed analytical results provide undistinguishable results as those obtained by Monte-Carlo results.

Several emerging wireless communication systems require direct transmission between mobile terminals to support efficient data transfer and user mobility. Such mobile-to-mobile communication systems differ from the conventional cellular systems where only the user unit is mobile. In addition, there might be a relay, also called a repeater, between the original transmitter and the final receiver to improve the network range and coverage. Potential applications for mobile-to-mobile systems include Intelligent Highways for coordinated traffic control and ad-hoc networks meant for military and disaster management. Relays may be deployed in cellular networks and IEEE 802.16 mesh networks for wireless broadband access. Extensive research in cellular radio channels has led to the successful deployment of cellular networks. However, our knowledge of the radio channels encountered in mobile-to-mobile and relay-based systems is still inadequate. This forms the primary motivation behind our research in addressing wireless channel modeling, simulation, and estimation issues for these systems. Specifically, we investigate frequency-flat mobile-to-mobile channels and develop simulation models by using the sum-of-sinusoids method, which is widely used for cellular channels. In addition, we present the properties of amplify and forward relay channels via theoretical analysis. This analysis, to the best of our knowledge, is the first of its kind. Further, we address the unique challenges, which arise because of the different underlying channel model, for channel estimation in amplify and forward relay systems. Our work would provide other researchers the necessary tools for the design and testing of these emerging communication systems.

In heterogeneous dense networks where spectrum is shared, users privacy remains one of the major challenges. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk becomes information leakage.We propose a novel and efficient secrecy rate enhancing relay strategy EFFIN for information leakage neutralization. The relay matrix is chosen such that the effective leakage channel (spectral and spatial) is zero. Thus, it ensures secrecy regardless of receive processing employed at eavesdroppers and does not rely on wiretaps codes to ensure secrecy, unlike other physical layer security techniques such as artificial noise. EFFIN achieves a higher sum secrecy rate over several state-of-the-art baseline methods.

In heterogeneous dense networks where spectrum is shared, users' privacy remains one of the major challenges. On a multi-antenna relay-assisted multi-carrier interference channel, each user shares the spectral and spatial resources with all other users. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk on the spectral and spatial channels becomes information leakage. In this paper, we propose a novel secrecy rate enhancing relay strategy that utilizes both spectral and spatial resources, termed as information leakage neutralization. To this end, the relay matrix is chosen such that the effective channel from the transmitter to the colluding eavesdropper is equal to the negative of the effective channel over the relay to the colluding eavesdropper and thus the information leakage to zero. Interestingly, the optimal relay matrix in general is not block-diagonal which encourages users' encoding over the frequency channels. We proposed two information leakage neutralization strategies, namely efficient information leakage neutralization (EFFIN) and local-optimized information leakage neutralization (LOPTIN). EFFIN provides a simple and efficient design of relay processing matrix and precoding matrices at the transmitters in the scenario of limited power and computational resources. LOPTIN, despite its higher complexity, provides a better sum secrecy rate performance by optimizing the relay processing matrix and the precoding matrices jointly. The proposed methods are shown to improve the sum secrecy rates over several state-of-the-art baseline methods.

Resource allocation in wireless networks is one of the most studied class of problems. Generally, these problems are formulated as utility maximization problems under relevant constraints. The challenges posed by these problems vary widely depending on the nature of the utility function under consideration. Recently, the widespread prevalence of wireless devices prompted researchers and engineers to delve into the security issues of wireless communication. As compared to the wired medium, ensuring security for the wireless medium is more challenging mainly due to the broadcast nature of the transmission. But the ongoing research on physical layer security promises robust and reliable security schemes for wireless communication. Contrary to conventional cryptographic schemes, physical layer security techniques are impregnable as the security is ensured by the inherent randomness present in the wireless medium. In this thesis, we consider several wireless scenarios and propose secrecy enhancing resource allocation schemes for them in the first few chapters. We initially address the problem of secure transmission by following the conventional approach in the secrecy literature|secrecy rate maximization. Needless to say, in these chapters, secrecy rate is the utility function and the constraints are posed by the available power budget. Then we consider a pragmatic approach where we target the signal-to-noise ratio (SNR) of participating nodes and ensure information secrecy by appropriately constraining the SNRs of those nodes. In those SNR based formulations, SNR at the destination is the utility function and we are interested in maximizing it. In the last two chapters, we study two scenarios in a non-secrecy setting. In one of them, end-to-end data rate is the utility, whereas, in the other one, two utility functions|based on revenue generated|are defined for two rational agents in a game-theoretic setting. In the second chapter, we study parallel independent Gaussian channels with imperfect channel state information (CSI) for the eavesdropper. Firstly, we evaluate the probability of zero secrecy rate in this system for (i) given instantaneous channel conditions and (ii) a Rayleigh fading scenario. Secondly, when non-zero secrecy is achievable in the low SNR regime, we aim to solve a robust power allocation problem which minimizes the outage probability at a target secrecy rate. In the third, fourth and fifth chapters, we consider scenarios where the source node transmits a message to the destination using M parallel amplify-and-forward (AF) relays in the presence of a single or multiple eavesdroppers. The third chapter addresses the problem of the maximum achievable secrecy rate for two specific network models: (a) degraded eavesdropper channel with complex channel gain and (b) scaled eavesdropper channel with real-valued channel gains. In the fourth chapter, we consider the SNR based approach and address two problems: (i) SNR maximization at the destination and (ii) Total relay power minimization. In the fifth chapter, we assume that the relay nodes are untrusted and to counter them, we deliberately introduce artificial noise in the source message. For this model, we propose and solve SNR maximization problems for the following two scenarios: (i) Total power constraint on all the relay nodes and (ii) Individual power constraints on each of the relay nodes. In the sixth chapter, we address the problem of passive eavesdroppers in multi-hop wire-less networks using the technique of friendly jamming. Assuming decode-and-forward (DF) relaying, we consider a scheduling and power allocation (PA) problem for a multiple-source multiple-sink scenario so that eavesdroppers are jammed, and source-destination throughput targets are met. When channel state information (CSI) of all the node are available, we intend to minimize the total power consumption of all the transmitting nodes. In the absence of eavesdroppers CSI, we minimize vulnerability region of the network. In chapter seven, the problem of cooperative beamforming for maximizing the achievable data rate of two-hop amplify-and-forward (AF) network (in the absence of eavesdropper(s)) is considered. Along with an individual power constraint on each of the relay nodes, we consider a weighted sum power constraint. To solve this problem, we propose a novel algorithm based on the Quadratic Eigenvalue Problem (QEP) and discuss its convergence. In chapter eight, we study a Stackelberg game between a base station and a multi-antenna power beacon for wireless energy harvesting in a multiple sensor node scenario. Assuming imperfect CSI between the sensor nodes and the power beacon, we propose a utility function that is based on throughput non-outage probability at the base station. We find the optimal strategies for the base station and the power beacon that maximize their respective utility functions.

In heterogeneous dense networks where spectrum is shared, users privacy remains one of the major challenges. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk becomes information leakage.We propose a novel and efficient secrecy rate enhancing relay strategy EFFIN for information leakage neutralization. The relay matrix is chosen such that the effective leakage channel (spectral and spatial) is zero. Thus, it ensures secrecy regardless of receive processing employed at eavesdroppers and does not rely on wiretaps codes to ensure secrecy, unlike other physical layer security techniques such as artificial noise. EFFIN achieves a higher sum secrecy rate over several state-of-the-art baseline methods.

In heterogeneous dense networks where spectrum is shared, users' privacy remains one of the major challenges. On a multi-antenna relay-assisted multi-carrier interference channel, each user shares the spectral and spatial resources with all other users. When the receivers are not only interested in their own signals but also in eavesdropping other users' signals, the cross talk on the spectral and spatial channels becomes information leakage. In this paper, we propose a novel secrecy rate enhancing relay strategy that utilizes both spectral and spatial resources, termed as information leakage neutralization. To this end, the relay matrix is chosen such that the effective channel from the transmitter to the colluding eavesdropper is equal to the negative of the effective channel over the relay to the colluding eavesdropper and thus the information leakage to zero. Interestingly, the optimal relay matrix in general is not block-diagonal which encourages users' encoding over the frequency channels. We proposed two information leakage neutralization strategies, namely efficient information leakage neutralization (EFFIN) and local-optimized information leakage neutralization (LOPTIN). EFFIN provides a simple and efficient design of relay processing matrix and precoding matrices at the transmitters in the scenario of limited power and computational resources. LOPTIN, despite its higher complexity, provides a better sum secrecy rate performance by optimizing the relay processing matrix and the precoding matrices jointly. The proposed methods are shown to improve the sum secrecy rates over several state-of-the-art baseline methods.

Cette thèse traite de l'estimation d'un canal de communication radio-mobile multi-bond. La communication entre l'émetteur et le récepteur est ainsi faite par l'intermédiaire de relais (de type « Amplify and-Forward ») en série. Les différents éléments (émetteurs, relais, récepteurs) peuvent être fixes ou mobiles. Chaque lien de communication (chaque bond) est modélisé par un canal de Rayleigh à évanouissements plats, avec un spectre Doppler issu de deux environnements possibles de diffusion : en deux dimensions (2D, amenant le spectre en U de Jakes), ou en trois dimensions (3D, amenant un spectre Doppler plat). L'objectif majeur de la thèse est l'estimation dynamique du canal global issue de la cascade des différents liens. A cette fin, la cascade de canaux est approchée par une modèle auto-régressif du premier ordre (AR (1)), et l'estimation est réalisée à l'aide d'un algorithme standard, le filtre de Kalman. La méthode couramment utilisée dans la littérature pour fixer le paramètre du modèle AR(1) est basée sur un critère de « corrélation matching » (CM). Cependant, nous montrons que pour des canaux à variations lentes, un autre critère basé sur la minimisation de la variance asymptotique (MAV) de la sortie du filtre de Kalman est plus approprié. Pour les deux critères, CM et MAV, cette thèse donne une justification analytique en fournissant des formules approchées de la variance d'estimation par le filtre de Kalman, ainsi que du réglage optimal du paramètre du modèle AR(1). Ces formules analytiques sont données en fonctions des fréquences Doppler et du rapport signal sur bruit, pour les environnements de diffusion 2D et 3D, quel que soit le nombre et le type de bonds (fixe-mobile ou mobile-mobile). Les résultats de simulations montrent un gain considérable en termes de l'erreur quadratique moyenne (MSE) de l'estimateur de canal bien réglé, en particulier pour le scénario le plus courant de canal à évanouissements lents. / This thesis deals with the estimation of the multihop Amplify-and-Forward relay communications. The various objects (transmitter, relays, receivers) can be fixed or mobile. Each link is modeled by a flat fading Rayleigh channel, with a Doppler spectrum resulting from two-dimensional (2D, leading to the U-shape Dopller spectrum) or three-dimensional (3D, leading to a flat Doppler spectrum) scattering environments. The cascade of channel hops is approximated by a first-order autoregressive (AR(1)) model and is tracked by a standard estimation algorithm, the Kalman Filter (KF). The common method used in the literature to tune the parameter of the AR(1) model is based on a Correlation Matching (CM) criterion. However, for slow fading variations, another criterion based on the off-line Minimization of the Asymptotic Variance (MAV) of the KF is shown to be more appropriate. For both the CM and MAV criteria, this thesis gives analytic justification by providing approximated closed-form expressions of the estimation variance in output of the Kalman filter, and of the optimal AR(1) parameter. The analytical results are calculated for given Doppler frequencies and Signal-to-Noise Ratio for both scattering environments, whatever the number and type of transmission hops (Fixed-to-Mobile or Mobile-to-Mobile). The simulation results show a considerable gain in terms of the Mean Square Error (MSE) of the well tuned Kalman-based channel estimator, especially for the most common scenario of slow-fading channel.