Non-orthogonal multiple access (NOMA), with its exceptional spectrum efficiency, was thought to be a promising technology for upcoming wireless communications. Physical layer security has also been investigated to improve the security performance of the system. Power-domain NOMA has been considered for this paper, where multiple users can share the same spectrum which bases this sharing on distinct power values. Power allocation is used to allocate different power to the users based on their channel condition. Data signals of different users are superimposed on the transmitter's side, and the receiver uses successive interference cancellation (SIC) to remove the unwanted signals before decoding its own signal. There exist an eavesdropper whose motive is to eavesdrop on the confidential information that is being shared with the users. The network model developed in this way consists of two links, one of which considers the relay transmission path from the source to Near User to Far User and the other of which takes into account the direct transmission path from the source to the destination, both of which experience Nakagami-m fading. To degrade the eavesdropper's channel, the jamming technique is used against the eavesdropper where users are assumed to be in a full-duplex mode which aims to improve the security of the physical layer. Secrecy performance metrics such as secrecy outage probability, secrecy capacity, etc. are evaluated and analyzed for the considered system. Mathematical analysis and simulation using MATLAB are done to assess, analyze and visualize the system's performance in the presence of an eavesdropper when the jamming technique is applied. According to simulation results, the active jamming approach enhances the secrecy performance of the entire system and leads to a positive improvement in the secrecy rate.

De nos jours, certaines applications multimédias embarquées tel que la visiophonie, l'internet à haut débit, etc., de par leur limitations en capacitée dues aux efets introduits par les canaux de transmission, requierent des traitements numériques ecaces des signaux recus. La turbo detection semble prometteuse pour ce genre de demande. Elle permet d'exploiter la totalitée de l'information mise à la disposition du récepteur. Cependant, ses performances pour des canaux fortement dégrades, dependent largement de l'estimation des paramètres du milieu de transmission. Sa complexité calculatoire est liée aux modules échangeant les informations extrinseques. Dans ce contexte, cette thèse cible la conception et l'analyse des récepteurs iteratifs de faible complexitée destinées à la transmission des symboles codés dans les canaux de Rayleigh multi trajets à évanouissements rapides, inconnus au récepteur. Nous nous interessons dans la première partie de la thèse à la turbo égalisation dans le contexte mono usager : nous proposons et analysons une architecture iterative de faible complexité, intégrant l'égalisation, le décodage et l'estimation de la réponse impulsionnelle du canal et ses statistiques. Grâce à des outils semi analytiques, nous expliquons l'in- uence des paramètres du milieu de propagation sur le turbo détecteur et justions le choix des modules realisant le meilleur compromis complexite/performances. D'autre part, nous demontrons que l'architecture proposee s'adapte bien aux milieux severement perturbes dont la reponse impulsionnelle et les statistiques sont inconnues au recepteur. Dans la seconde partie, nos travaux de recherche portent sur la turbo detection multi usagers pour une liaison montante d'un systeme DS-CDMA asynchrone. Nous etudions deux situations. Dans la premiere, le recepteur est equipe d'une seule antenne. Nous proposons et evaluons une architecture iterative constituee de modules de faible complexit e, joignant la detection multi usagers, le decodage et l'estimation des canaux de transmission. Quant a la deuxieme situation, nous exploitons le principe de diversite d'antennes en reception et etendons les modules de l'architecture proposee au contexte multi antennes. Nous demontrons par simulation que l'architecture proposee permet d'eradiquer les interferences occasionnees par les milieux de propagation sans augmenter de maniere significative le rapport signal a bruit. / Beyond their capacity limitations due to the transmission channels efects, nowadays, some embarked multimedia applications such as video telephony, broadband internet, etc., require ecient digital processing of the received signals. Turbo detection is a promising method to address these requirements. It allows exploiting all the available information at the receiver. However, its performance for the severe channels is highly dependent on the transmission parameter estimation. Its computational complexity is mainly due to the SISO modules. In this context, this thesis study the design and analysis of low complexity iterative receiver for the coded symbols over unknown fast fading multipath Rayleigh channels. In the first part of the thesis, we investigate the SISO turbo equalization for single user : we propose and analyze an iterative low complexity architecture, including equalization, decoding and channel estimation with its statistics. Using semi analytical tools, we explain the propagation efect on the turbo equalizer and justify the choice of modules realizing the best complexity/performance compromise. Furthermore, we demonstrate that the proposed architecture is efective in severe channel conditions where the impulse response and statistics are unknown to the receiver. In the second part, our research focuses on multi-user turbo detection for uplink asynchronous DS-CDMA systems. Two situations are considered. For the first one, the receiver has a single antenna. We propose and evaluate an iterative architecture involving lower complexity modules, handling multi-user detection, decoding and channels estimation. As for the second situation, we use the receiver diversity principle and we extend the proposed architecture modules to the multi antennas context. Simulation results showed that the proposed architecture eliminate almost all the interference caused by the channel without increasing significantly the required signal to noise ratio.

La modulation codée est une technique de transmission efficace en largeur de bande qui intègre le codage de canal et la modulation en une seule entité et ce, afin d'améliorer les performances tout en conservant la même efficacité spectrale comparé à la modulation non codée. Les codes de parité à faible densité (low-density parity-check codes, LDPC) sont les codes correcteurs d'erreurs les plus puissants et approchent la limite de Shannon, tout en ayant une complexité de décodage relativement faible. L'idée de combiner les codes LDPC et la modulation efficace en largeur de bande a donc été considérée par de nombreux chercheurs. Dans ce mémoire, nous étudions une méthode de modulation codée à la fois puissante et efficace en largeur de bande, ayant d'excellentes performances de taux d'erreur binaire et une complexité d'implantation faible. Ceci est réalisé en utilisant un encodeur rapide, un décoder de faible complexité et aucun entrelaceur. Les performances du système proposé pour des transmissions sur un canal additif gaussien blanc et un canal à évanouissements plats de Rayleigh sont évaluées au moyen de simulations. Les résultats numériques montrent que la méthode de modulation codée utilisant la modulation d'amplitude en quadrature à M niveaux (M-QAM) peut atteindre d'excellentes performances pour toute une gamme d'efficacité spectrale. Une autre contribution de ce mémoire est une méthode simple pour réaliser une modulation codée adaptative avec les codes LDPC pour la transmission sur des canaux à évanouissements plats et lents de Rayleigh. Dans cette méthode, six combinaisons de paires encodeur modulateur sont employées pour une adaptation trame par trame. L'efficacité spectrale moyenne varie entre 0.5 et 5 bits/s/Hz lors de la transmission. Les résultats de simulation montrent que la modulation codée adaptative avec les codes LDPC offre une meilleure efficacité spectrale tout en maintenant une performance d'erreur acceptable.

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No / Many studies have been conducted to investigate the performance of priority queuing (PQ) systems with constant service capacity. However, due to the time-varying nature of wireless channels in wireless communication networks, the service capacity of queuing systemsmay vary over time. Therefore, it is necessary to investigate the performance of PQ systems in the presence of varying service capacity. In addition, self-similar traffic has been discovered to be a ubiquitous phenomenon in various communication networks, which poses great challenges to performance modelling of scheduling systems due to its fractal-like nature. Therefore, this paper develops a flow-decomposition based approach to performance modelling of PQ systems subject to self-similar traffic and varying service capacity. It specifically proposes an analytical model to investigate queue length distributions of individual traffic flows. The validity and accuracy of the model is demonstrated via extensive simulation experiments.

This thesis examines the benefits of using adaptive modulation and coding in terms of spectral efficiency and probability of bit error. Specifically, we examine the performance enhancement made possible by using linear prediction along with channel estimation in conjunction with adaptive modulation. We begin this manuscript with basic fundamentals of our study, followed by a detailed view of simulations, their results, and our conclusions from them. The study includes simulations in slow and moderately fast flat fading Rayleigh channels. We present our findings regarding the advantages of using predictive measures to foresee the state of the channel and make adjustments to transmissions accordingly. In addition to finding the general advantages of channel prediction in adaptive modulation, we explore various ways to adjust the prediction algorithm when we are faced with high Doppler rates and fast fading. By the end of this work, we should have a better understanding of when channel prediction is most valuable to adaptive modulation and when it is weakest, and how we can alleviate the problems that prediction will have in harsh environments. / Master of Science

One of the fundamental limitations of mobile radio communications is their time-varying fading channel. This thesis addresses the efficient use of channel state information to improve the communication systems, with a particular emphasis on practical issues such as compatibility with the existing wireless systems and low complexity implementation. The closed-loop transmit diversity technique is used to improve the performance of the downlink channel in MIMO communication systems. For example, the WCDMA standard endorsed by 3GPP adopts a mode of downlink closed-loop scheme based on partial channel state information known as mode 1 of 3GPP. Channel state information is fed back from the mobile unit to the base station through a low-rate uncoded feedback bit stream. In these closed-loop systems, feedback error and feedback delay, as well as the sub-optimum reconstruction of the quantized feedback data, are the usual sources of deficiency. In this thesis, we address the efficient reconstruction of the beamforming weights in the presence of the feedback imperfections, by exploiting the residual redundancies in the feedback stream. We propose a number of algorithms for reconstruction of beamforming weights at the base-station, with the constraint of a constant transmit power. The issue of the decoding at the receiver is also addressed. In one of the proposed algorithms, channel fading prediction is utilized to combat the feedback delay. We introduce the concept of Blind Antenna Verification which can substitute the conventional Antenna Weight Verification process without the need for any training data. The closed-loop mode 1 of 3GPP is used as a benchmark, and the performance is examined within a WCDMA simulation framework. It is demonstrated that the proposed algorithms have substantial gain over the conventional method at all mobile speeds, and are suitable for the implementation in practice. The proposed approach is applicable to other closed-loop schemes as well. The problem of (long-range) prediction of the fading channel is also considered, which is a key element for many fading-compensation techniques. A linear approach, usually used to model the time evolution of the fading process, does not perform well for long-range prediction applications. We propose an adaptive algorithm using a state-space approach for the fading process based on the sum-sinusoidal model. Also to enhance the widely-used linear approach, we propose a tracking method for a multi-step linear predictor. Comparing the two methods in our simulations shows that the proposed algorithm significantly outperforms the linear method, for both stationary and non-stationary fading processes, especially for long-range predictions. The robust structure, as well as the reasonable computational complexity, makes the proposed algorithm appealing for practical applications.

One of the fundamental limitations of mobile radio communications is their time-varying fading channel. This thesis addresses the efficient use of channel state information to improve the communication systems, with a particular emphasis on practical issues such as compatibility with the existing wireless systems and low complexity implementation. The closed-loop transmit diversity technique is used to improve the performance of the downlink channel in MIMO communication systems. For example, the WCDMA standard endorsed by 3GPP adopts a mode of downlink closed-loop scheme based on partial channel state information known as mode 1 of 3GPP. Channel state information is fed back from the mobile unit to the base station through a low-rate uncoded feedback bit stream. In these closed-loop systems, feedback error and feedback delay, as well as the sub-optimum reconstruction of the quantized feedback data, are the usual sources of deficiency. In this thesis, we address the efficient reconstruction of the beamforming weights in the presence of the feedback imperfections, by exploiting the residual redundancies in the feedback stream. We propose a number of algorithms for reconstruction of beamforming weights at the base-station, with the constraint of a constant transmit power. The issue of the decoding at the receiver is also addressed. In one of the proposed algorithms, channel fading prediction is utilized to combat the feedback delay. We introduce the concept of Blind Antenna Verification which can substitute the conventional Antenna Weight Verification process without the need for any training data. The closed-loop mode 1 of 3GPP is used as a benchmark, and the performance is examined within a WCDMA simulation framework. It is demonstrated that the proposed algorithms have substantial gain over the conventional method at all mobile speeds, and are suitable for the implementation in practice. The proposed approach is applicable to other closed-loop schemes as well. The problem of (long-range) prediction of the fading channel is also considered, which is a key element for many fading-compensation techniques. A linear approach, usually used to model the time evolution of the fading process, does not perform well for long-range prediction applications. We propose an adaptive algorithm using a state-space approach for the fading process based on the sum-sinusoidal model. Also to enhance the widely-used linear approach, we propose a tracking method for a multi-step linear predictor. Comparing the two methods in our simulations shows that the proposed algorithm significantly outperforms the linear method, for both stationary and non-stationary fading processes, especially for long-range predictions. The robust structure, as well as the reasonable computational complexity, makes the proposed algorithm appealing for practical applications.

Signal processing has been playing a key role in providing solutions to key problems encountered in communications, in general, and in wireless communications, in particular. Time-Frequency Signal Processing (TFSP) provides eective tools for analyzing nonstationary signals where the frequency content of signals varies in time as well as for analyzing linear time-varying systems. This research aimed at exploiting the advantages of TFSP, in dealing with nonstationary signals, into the fundamental issues of signal processing, namely the signal estimation and signal separation. In particular, it has investigated the problems of (i) the Instantaneous Frequency (IF) estimation of Linear Frequency-Modulated (LFM) signals corrupted in complex-valued zero-mean Multiplicative Noise (MN), and (ii) the Underdetermined Blind Source Separation (UBSS) of LFM signals, while focusing onto the fast-growing area of Wireless Communications (WCom). A common problem in the issue of signal estimation is the estimation of the frequency of Frequency-Modulated signals which are seen in many engineering and real-life applications. Accurate frequency estimation leads to accurate recovery of the true information. In some applications, the random amplitude modulation shows up when the medium is dispersive and/or when the assumption of point target is not valid; the original signal is considered to be corrupted by an MN process thus seriously aecting the recovery of the information-bearing frequency. The IF estimation of nonstationary signals corrupted by complex-valued zero-mean MN was investigated in this research. We have proposed a Second-Order Statistics approach, rather than a Higher-Order Statistics approach, for IF estimation using Time-Frequency Distributions (TFDs). The main assumption was that the autocorrelation function of the MN is real-valued but not necessarily positive (i.e. the spectrum of the MN is symmetric but does not necessary has the highest peak at zero frequency). The estimation performance was analyzed in terms of bias and variance, and compared between four dierent TFDs: Wigner-Ville Distribution, Spectrogram, Choi-Williams Distribution and Modified B Distribution. To further improve the estimation, we proposed to use the Multiple Signal Classification algorithm and showed its better performance. It was shown that the Modified B Distribution performance was the best for Signal-to-Noise Ratio less than 10dB. In the issue of signal separation, a new research direction called Blind Source Separation (BSS) has emerged over the last decade. BSS is a fundamental technique in array signal processing aiming at recovering unobserved signals or sources from observed mixtures exploiting only the assumption of mutual independence between the signals. The term "blind" indicates that neither the structure of the mixtures nor the source signals are known to the receivers. Applications of BSS are seen in, for example, radar and sonar, communications, speech processing, biomedical signal processing. In the case of nonstationary signals, a TF structure forcing approach was introduced by Belouchrani and Amin by defining the Spatial Time- Frequency Distribution (STFD), which combines both TF diversity and spatial diversity. The benefit of STFD in an environment of nonstationary signals is the direct exploitation of the information brought by the nonstationarity of the signals. A drawback of most BSS algorithms is that they fail to separate sources in situations where there are more sources than sensors, referred to as UBSS. The UBSS of nonstationary signals was investigated in this research. We have presented a new approach for blind separation of nonstationary sources using their TFDs. The separation algorithm is based on a vector clustering procedure that estimates the source TFDs by grouping together the TF points corresponding to "closely spaced" spatial directions. Simulations illustrate the performances of the proposed method for the underdetermined blind separation of FM signals. The method developed in this research represents a new research direction for solving the UBSS problem. The successful results obtained in the research development of the above two problems has led to a conclusion that TFSP is useful for WCom. Future research directions were also proposed.

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