Due to the uncertainties introduced by the propagation channel, and RF and mixed signal circuits imperfections, digital communication receivers require efficient and robust signal acquisition algorithms for timing and carrier recovery, and interfer- ence rejection. The main theme of this work is the development of efficient and robust signal synchronization and interference rejection schemes for narrowband, wideband and ultra wideband communications systems. A series of novel signal acquisition schemes together with their performance analysis and comparisons with existing state-of-the- art results are introduced. The design effort is first focused on narrowband systems, and then on wideband and ultra wideband systems. For single carrier modulated narrowband systems, it is found that conventional timing recovery schemes present low efficiency, e.g., certain feedback timing recov- ery schemes exhibit the so-called hang-up phenomenon, while another class of blind feedforward timing recovery schemes presents large self-noise. Based on a general re- search framework, we propose new anti-hangup algorithms and prefiltering techniques to speed up the feedback timing recovery and reduce the self-noise of feedforward tim- ing estimators, respectively. Orthogonal frequency division multiplexing (OFDM) technique is well suited for wideband wireless systems. However, OFDM receivers require high performance car-rier and timing synchronization. A new coarse synchronization scheme is proposed for efficient carrier frequency offset and timing acquisition. Also, a novel highly accurate decision-directed algorithm is proposed to track and compensate the residual phase and timing errors after the coarse synchronization step. Both theoretical analysis and computer simulations indicate that the proposed algorithms greatly improve the performance of OFDM receivers. The results of an in-depth study show that a narrowband interference (NBI) could cause serious performance loss in multiband OFDMbased ultra-wideband (UWB) sys- tems. A novel NBI mitigation scheme, based on a digital NBI detector and adaptive analog notch filter bank, is proposed to reduce the effects of NBI in UWB systems. Simulation results show that the proposed NBI mitigation scheme improves signifi- cantly the performance of a standard UWB receiver (this improvement manifests as a signal-to-noise ratio (SNR) gain of 9 dB).

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Despite the inherent resistance to narrowband signal interference afforded by GPS spread spectrum modulation, the low level of GPS signals makes them susceptible to narrowband interference. This paper discusses the application of a pre-correlation adaptive temporal filter for stationary and nonstationary narrowband interference suppression. Various adaptive algorithms are studied and implemented. Comparison of the convergence and tracking behavior of various algorithms is made.

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Impulse-based Ultra Wideband (UWB) radio technology has recently gained significant research attention for various indoor ranging, sensing and communications applications due to the large amount of allocated bandwidth and desirable properties of UWB signals (e.g., improved timing resolution or multipath fading mitigation). However, most of the applications have focused on indoor environments where the UWB channel is characterized by tens to hundreds of resolvable multipath components. Such environments introduce tremendous complexity challenges to traditional radio designs in terms of signal detection and synchronization. Additionally, the extremely wide bandwidth and shared nature of the medium means that UWB receivers must contend with a variety of interference sources. Traditional interference mitigation techniques are not amenable to UWB due to the complexity of straight-forward translations to UWB bandwidths. Thus, signal detection, synchronization and interference mitigation are open research issues that must be met in order to exploit the potential benefits of UWB systems. This thesis seeks to address each of these three challenges by first examining and accurately characterizing common approaches borrowed from spread spectrum and then proposing new methods which provide an improved trade-off between complexity and performance. / Ph. D.

The direct sequence (DS) code division multiple access (CDMA) is one of the most promising multiplexing technologies for wireless communications. It is also a core technology used in the wideband CDMA (WCDMA) system for the third generation (3G) wireless communication systems. In practice, in the CDMA systems the incomplete orthogonal of the spreading codes between users may introduce the so-called multiple access interference (MAI). Usually, the near-far problem exists when the interfering users are assigned powers much higher than the desired user. Such that the system performance might degrade, dramatically, and thus limits the system capacity. To circumvent the above-mentioned problems many effective adaptive multiuser detectors, based on the minimum mean square error (MMSE) and the minimum output energy (MOE) criteria subject to certain constraints have been proposed. In addition, to mitigate multipath fading effect, RAKE receiver was adopted due to the advantages of path diversity, thus, enhances the system performance. To implement the blind adaptive multiuser detector the linearly constrained minimum variance (LCMV), which is the constrained version of MOE, has been suggested. Further, the LCMV-based receivers exhibit high sensitivity to the channel mismatch caused by the unreliable estimation. To deal with this problem the constant modulus (CM) criterion was considered. In this dissertation, to deal with diverse phenomena encountered in practical channels, we first propose new blind adaptive multi-user detectors, based on the Min/Max criterion associated with the LCCM approach. For implementation the LC exponential window (EW) recursive least-square (RLS) algorithm is derived, and is referred to as the EW LCCM-RLS receiver. It can be used to effectively suppress the MAI and ISI, simultaneously, over multipath fading channels and are robust to mismatch problem caused by inaccuracies in the acquisition of timing and spreading code of the desired user. To reduce the complexity of the above-mentioned blind adaptive multi-user receiver with the LCCM-RLS algorithm, the so-called generalized sidelobe-canceller (GSC) structure is adopted, results in obtaining new CM-GSC-RLS algorithm. Moreover, to further improve the system performance for multipath fading and time-varying channel, the sliding window (SW) LCCM-RLS and SW CM-GSC-RLS algorithms are developed. It can be employed for multipath fading channel with the rapidly changing strong narrowband interference (NBI), which is joined suddenly to the CDMA systems. To look more inside the effect of selecting the initial value of the input signals autocorrelation matrix, some theoretical analyses for the SW LC-RLS as well as EW LC-RLS are provided. Since, unfortunately, the LCCM criterion is known to highly depend on the exact knowledge of the desired user amplitude that is not known exactly at receiver. In the final of this dissertation, a novel linearly constrained adaptive constant modulus RLS (LC-ACM-RLS) algorithm for blind DS-CDMA receiver is proposed. With this new proposed LC-ACM-RLS algorithm, the amplitude variation of the desired user, due to changing characteristics of the channel, can be tracked adaptively. Thus, better performance achievement, in terms of output signal-to-interference-plus-noise ratio (SINR) and bit error rate (BER), over the conventional LCCM-LMS and LCCM-RLS algorithms can be expected.

Ultrawideband and cognitive radio are two of the most important approaches that are shaping the future of wireless communication systems. At a first glance, the aims of UWB and cognitive radio do not seem to be overlapping significantly, however, there is a strong synergy between the capabilities of UWB and the goals of cognitive radio. One of the objectives of this thesis is to shed the first light on the marriage of these two important approaches.Ultrawideband (UWB) is a promising technology for future short-range, high-data rate wireless communication networks. Along with its exciting features including achieving high data rates, low transmission power requirement, and immunity to multipath effects, UWB is unique in its coexistence capability with narrowband systems.In this thesis, the details of practical UWB implementation are provided. Regarding the coexistence of UWB with licensed narrowband systems, narrowband interference (NBI)avoidance and cancelation techniques in the literature are investigated. It is aimed to emphasize that UWB is a strong candidate for cognitive radio, and this fact is proven by providing two different approaches in which ultrawideband is combined with cognitive radio to maximize the performance of unlicensed communications.

Compressed sensing has been a very active area of research and several elegant algorithms have been developed for the recovery of sparse signals in the past few years. However, most of these algorithms are either computationally expensive or make some assumptions that are not suitable for all real world problems. Recently, focus has shifted to Bayesian-based approaches that are able to perform sparse signal recovery at much lower complexity while invoking constraint and/or a priori information about the data. While Bayesian approaches have their advantages, these methods must have access to a priori statistics. Usually, these statistics are unknown and are often difficult or even impossible to predict. An effective workaround is to assume a distribution which is typically considered to be Gaussian, as it makes many signal processing problems mathematically tractable. Seemingly attractive, this assumption necessitates the estimation of the associated parameters; which could be hard if not impossible. In the thesis, we focus on this aspect of Bayesian recovery and present a framework to address the challenges mentioned above. The proposed framework allows Bayesian recovery of sparse signals but at the same time is agnostic to the distribution of the unknown sparse signal components. The algorithms based on this framework are agnostic to signal statistics and utilize a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. In the thesis, we propose several algorithms based on this framework which utilize the structure present in signals for improved recovery. In addition to the algorithm that considers just the sparsity structure of sparse signals, tools that target additional structure of the sparsity recovery problem are proposed. These include several algorithms for a) block-sparse signal estimation, b) joint reconstruction of several common support sparse signals, and c) distributed estimation of sparse signals. Extensive experiments are conducted to demonstrate the power and robustness of our proposed sparse signal estimation algorithms. Specifically, we target the problems of a) channel estimation in massive-MIMO, and b) Narrowband interference mitigation in SC-FDMA. We model these problems as sparse recovery problems and demonstrate how these could be solved naturally using the proposed algorithms.

Instantaneous Frequency (IF) estimation based on time-varying autoregressive (TVAR) modeling has been shown to perform well in practical scenarios when the IF variation is rapid and/or non-linear and only short data records are available for modeling. A challenging aspect of implementing IF estimation based on TVAR modeling is the efficient computation of the time-varying coefficients by solving a set of linear equations referred to as the generalized covariance equations. Conventional approaches such as Gaussian elimination or direct matrix inversion are computationally inefficient for solving such a system of equations especially when the covariance matrix has a high order. We implement two recursive algorithms for efficiently inverting the covariance matrix. First, we implement the Akaike algorithm which exploits the block-Toeplitz structure of the covariance matrix for its recursive inversion. In the second approach, we implement the Wax-Kailath algorithm that achieves a factor of 2 reduction over the Akaike algorithm in the number of recursions involved and the computational effort required to form the inverse matrix. Although a TVAR model works well for IF estimation of frequency modulated (FM) components in white noise, when the model is applied to a signal containing a finitely correlated signal in addition to the white noise, estimation performance degrades; especially when the correlated signal is not weak relative to the FM components. We propose a decorrelating TVAR (DTVAR) model based IF estimation and a DTVAR model based linear prediction error filter for FM interference rejection in a finitely correlated environment. Simulations show notable performance gains for a DTVAR model over the TVAR model for moderate to high SIRs. / Master of Science

Les réseaux à l'origine métropolitains, ont connu une tendance à rétrécir pour aujourd'hui se concentrer autour de l'être humain. Avec des équipements de plus en plus miniatures et les utilisateurs désireux de disposer en permanence des services qui leur sont accessibles à domicile, le réseau est envisagé plus petit, plus proche du corps. On assiste alors à l'émergence du réseau corporel, le Body Area Network (BAN), qui est constitué d'éléments situés sur le corps, à l'intérieur ou encore à une courte distance. Ce réseau à portée du corps génère de nouvelles problématiques, notamment celles de la puissance rayonnée par les équipements, leur taille, leur poids...Les applications et usages envisagés pour un tel réseau sont variés et couvrent plusieurs domaines d'activités, en l'occurrence le secteur du médical, du sport, et le multimédia. Ce réseau doit donc reposer sur une couche physique qui s'adapte aux contraintes de ces diverses applications, tout en favorisant des équipements de faible taille, faible complexité et de forte autonomie. La technologie Ultra Large Bande impulsionnelle (UWB-IR) est porteuse de nombreuses promesses pour satisfaire en partie les besoins des réseaux BAN, car autorisant des débits aussi bien réduits qu'élevés, et les architectures d'émission et réception utilisables pour cette technologie rendent possibles des équipements à faible complexité et faible coût, et dont la consommation énergétique est réduite.Ce travail de thèse a débuté alors qu'un processus de normalisation sur les BAN était en cours. L'objectif des travaux menés était de pouvoir contribuer en partie à ce processus de normalisation par la proposition d'une couche physique basée sur la radio impulsionnelle UWB (UWB-IR). Ainsi notre étude a porté sur le paramétrage de cette couche physique à partir de l'analyse des contraintes et requis techniques d'un réseau BAN. Les performances de cette couche physique ont ensuite été évaluées dans un contexte de canal UWB BAN et suivant le type d'architecture en réception, en particulier pour le récepteur non-cohérent. Enfin, une attention a été apportée sur la robustesse de la liaison en présence d'interférences bande étroite. Dans l'ensemble, ce travail a permis d'étudier et d'évaluer la pertinence d'une couche physique UWB-IR dans le contexte du réseau BAN / Absence de résumé en anglais

Cette thèse a pour cadre les transmissions sur les réseaux CPL-BE et les réseaux de capteurs à faible capacité. L'état de l'art classique sur la protection de l'information dans la transmission par réseaux de capteurs fait référence à l'utilisation de codage distribué où les relais implémentent des opérations de parité (mélange des flux) sur les data issues des capteurs. Cependant, il est difficile, de par la nature variable de la qualité des liens en liaisons sans fil, de contrôler la qualité du codeur équivalent construit et de maintenir ses performances au cours du temps. C'est pourquoi nous nous sommes orientés dans cette thèse vers la recherche de schémas de codage différents qui résistent mieux à la variation de qualité des liaisons à travers le réseau. Notre choix s'est porté sur le codage par sous-espace inspiré des travaux de Gabidulin. Le but est de former un code qui utilise une métrique simple et résistante pour sécuriser les transmissions sur le réseau. Les codes à métrique de rang répondent bien à ce besoin car il n'y a qu'à contrôler le rang de la matrice obtenue en réception pour vérifier l'intégrité de la transmission. Les codes à métrique de rang et leur algorithme de décodage ont été étudiés dans un premier temps. Puis, les performances du code LRPC proposé concaténé avec les codes convolutifs sont testées dans des schémas de transmission des contextes différents. / This thesis considers the context of transmissions on CPL-BE networks and low-capacity sensor networks. The state of the art on information protection intransmission by sensor networks refers to the use of distributed coding, where therelays implement parity operations (mixing of streams) on data transmitted by thesensors. However, due to the varying nature of the quality of the wireless links, it is difficult to control the quality of the equivalent encoder constructed and to maintain its performance over time. Therefore, in this thesis, we have focused on the search for different coding schemes that are better resist the variation in the quality of the links across the network. Our choice was based on the sub-space coding inspired by Gabidulin's work. The goal is to form a code that uses a simple and resistant metric to secure transmission across the network. Rank metric codes respond well to this need because it only has to control the rank of the matrix obtained in reception to verify the integrity of the transmission. The rank metric codes and their decoding algorithm were studied in a first step. Then, the performance of the proposed LRPC code concatenated with the convolutional codes is tested in transmission schemes of different contexts.