Contribution à la mise en oeuvre de récepteurs et de techniques d'estimation de canal pour les systèmes mobiles de DS-CDMA multi-porteuse

Ce mémoire traite du développement de récepteurs et de techniques déstimation de canal pour les systèmes mobiles sans fil de type DS-CDMA multi-porteuse. Deux problèmes principaux doivent être pris en compte dans ce cas. Premièrement, l'Interférence d'Accès Multiple (IAM) causée par d'autres utilisateurs. Deuxièmement, les propriétés des canaux de propagation dans les systèmes radio mobiles. Ainsi, dans la première partie du manuscrit, nous proposons deux structures adaptatives (dites détection séparée et détection jointe) pour la mise en oeuvre de récepteurs minimisant lérreur quadratique moyenne (MMSE), fondés sur un Algorithme de Projection Affine (APA). Ces récepteurs permettent de supprimer les IAM, notamment lorsque le canal d'évanouissement est invariant dans le temps. Cependant, comme ces récepteurs nécessitent les séquences d'apprentissage de chaque utilisateur actif, nous développons ensuite deux récepteurs adaptatifs dits aveugles, fondés sur un algorithme de type projection affine. Dans ce cas, seule la séquence d'étalement de l'utilisateur désiré est nécessaire. Quand les séquences d'étalement de tous les utilisateurs sont disponibles, un récepteur reposant sur le décorrélateur est aussi proposé et permet d'éliminer les IAM, sans qu'une période pour l'adaptation soit nécessaire. Dans la seconde partie, comme la mise en oeuvre de récepteurs exige léstimation du canal, nous proposons plusieurs algorithmes pour léstimation des canaux d'évanouissement de Rayleigh, variables dans le temps et produits dans les systèmes multi-porteuses. A cette fin, les canaux sont approximés par des processus autorégressifs (AR) d'ordre supérieur à deux. Le premier algorithme repose sur deux filtres de Kalman interactifs pour léstimation conjointe du canal et de ses paramètres AR. Puis, pour nous affranchir des hypothèses de gaussianité nécessaires à la mise en oeuvre d'un filtre optimal de Kalman, nous étudions la pertinence d'une structure fondée sur deux filtres H1 interactifs. Enfin, léstimation de canal peut ^etre vue telle un problème déstimation fondée sur un modèle à erreur- sur-les-variables (EIV). Les paramètres AR du canal et les variances de processus générateur et du bruit d'observation dans la représentation de léspace d'état du système sont dans ce cas estimés conjointement à partir du noyau des matrices d'autocorrélation appropriées.This dissertation deals with the development of receivers and channel estimation techniques for multi-carrier DS- CDMA mobile wireless systems. Two major problems should be taken into account in that case. Firstly, the Multiple Access Interference (MAI) caused by other users. Secondly, the multi-path fading of mobile wireless channels. In the first part of the dissertation, we propose two adaptive structures (called separate and joint detection) to design Minimum Mean Square Error (MMSE) receivers, based on the Affine Projection Algorithm (APA). These receivers are able to suppress the MAI, particularly when the fading channel is time-invariant. However, as they require a training sequence for every active user, we then propose two blind adaptive multiuser receiver structures based on a blind APA-like multiuser detector. In that case, only the knowledge of the spreading code of the desired user is required. When the spreading codes of all users are available, a decorrelating detector based receiver is proposed and is able to completely eliminate the MAI without any training. In the second part, as receiver design usually requires the estimation of the channel, we propose several training-based algorithms for the estimation of time-varying Rayleigh fading channels in multi-carrier systems. For this purpose, the fading channels are approximated by autoregressive (AR) processes whose order is higher than two. The first algorithm makes it possible to jointly estimate the channel and its AR parameters based on two-cross-coupled Kalman filters. Nevertheless, this filtering is based on restrictive Gaussian assumptions. To relax them, we investigate the relevance of a structure based on two-cross-coupled H1 filters. This method consists in minimizing the influence of the disturbances such as the additive noise on the estimation error. Finally, we propose to view the channel estimation as an Errors-In-Variables (EIV) issue. In that case, the channel AR parameters and the variances of both the driving process and the measurement noise in the state-space representation of the system are estimated from the null space of suitable correlation matrices

Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods

The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS). Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements

Exploiting the spatio-temporal channel properties of multiple antenna systems

The spatio-temporal channel properties of multiple antenna systems are exploited to obtain new approaches to localization and channel prediction. It is shown that a mobile station can be localized in multipath environments under the explicit consideration of scatterers. Thus, unlike conventional localization systems, the scatterers are used as an aid in localization. Moreover, it is shown that channel prediction in multiple antenna systems can be performed using linear prediction filters. This result is used to propose optimal and computationally inexpensive suboptimal channel predictors

Spectrum sensing and occupancy prediction for cognitive machine-to-machine wireless networks

A thesis submitted to the University of Bedfordshire, in partial fulfil ment of the requirements for the degree of Doctor of Philosophy (PhD)The rapid growth of the Internet of Things (IoT) introduces an additional challenge to the existing spectrum under-utilisation problem as large scale deployments of thousands devices are expected to require wireless connectivity. Dynamic Spectrum Access (DSA) has been proposed as a means of improving the spectrum utilisation of wireless systems. Based on the Cognitive Radio (CR) paradigm, DSA enables unlicensed spectrum users to sense their spectral environment and adapt their operational parameters to opportunistically access any temporally unoccupied bands without causing interference to the primary spectrum users. In the same context, CR inspired Machine-to-Machine (M2M) communications have recently been proposed as a potential solution to the spectrum utilisation problem, which has been driven by the ever increasing number of interconnected devices. M2M communications introduce new challenges for CR in terms of operational environments and design requirements. With spectrum sensing being the key function for CR, this thesis investigates the performance of spectrum sensing and proposes novel sensing approaches and models to address the sensing problem for cognitive M2M deployments. In this thesis, the behaviour of Energy Detection (ED) spectrum sensing for cognitive M2M nodes is modelled using the two-wave with dffi use power fading model. This channel model can describe a variety of realistic fading conditions including worse than Rayleigh scenarios that are expected to occur within the operational environments of cognitive M2M communication systems. The results suggest that ED based spectrum sensing fails to meet the sensing requirements over worse than Rayleigh conditions and consequently requires the signal-to-noise ratio (SNR) to be increased by up to 137%. However, by employing appropriate diversity and node cooperation techniques, the sensing performance can be improved by up to 11.5dB in terms of the required SNR. These results are particularly useful in analysing the eff ects of severe fading in cognitive M2M systems and thus they can be used to design effi cient CR transceivers and to quantify the trade-o s between detection performance and energy e fficiency. A novel predictive spectrum sensing scheme that exploits historical data of past sensing events to predict channel occupancy is proposed and analysed. This approach allows CR terminals to sense only the channels that are predicted to be unoccupied rather than the whole band of interest. Based on this approach, a spectrum occupancy predictor is developed and experimentally validated. The proposed scheme achieves a prediction accuracy of up to 93% which in turn can lead to up to 84% reduction of the spectrum sensing cost. Furthermore, a novel probabilistic model for describing the channel availability in both the vertical and horizontal polarisations is developed. The proposed model is validated based on a measurement campaign for operational scenarios where CR terminals may change their polarisation during their operation. A Gaussian approximation is used to model the empirical channel availability data with more than 95% confi dence bounds. The proposed model can be used as a means of improving spectrum sensing performance by using statistical knowledge on the primary users occupancy pattern

Traitement du signal pour les communications numériques au travers de canaux radio-mobiles

This manuscript of ''Habilitation à diriger les Recherches'' (Habilitation to conduct researches) gives me the opportunity to take stock of the last 14 years on my associate professor activities and on my research works in the field of signal processing for digital communications, particularly for radio-mobile communications. The purpose of this signal processing is generally to obtain a robust transmission, despite the passage of digital information through a communication channel disrupted by the mobility between the transmitter and the receiver (Doppler effect), the phenomenon of echoes (multi-path propagation), the addition of noise or interference, or by limitations in bandwidth, in transmitted power or in signal-to-noise ratio. In order to recover properly the digital information, the receiver needs in general to have an accurate knowledge of the channel state. Much of my work has focused on receiver synchronization or more generally on the dynamic estimation of the channel parameters (delays, phases, amplitudes, Doppler shifts, ...). We have developed estimators and studied their performance in asymptotic variance, and have compared them to minimum lower bound (Cramer-rao or Bayesian Cramer Rao bounds). Some other studies have focused only on the recovering of information (''detection'' or ''equalization'' task) by the receiver after channel estimation, or proposed and analyzed emission / reception schemes, reliable for certain scenarios (transmit diversity scheme for flat fading channel, scheme with high energy efficiency, ...).Ce mémoire de HDR est l'occasion de dresser un bilan des 14 dernières années concernant mes activités d'enseignant-chercheur et mes travaux de recherche dans le domaine du traitement du signal pour les communications numériques, et plus particulièrement les communications radio-mobiles. L'objet de ce traitement du signal est globalement l'obtention d'une transmission robuste, malgré le passage de l'information numérique au travers d'un canal de communication perturbé par la mobilité entre l'émetteur et le récepteur (effet Doppler), le phénomène d'échos, l'addition de bruit ou d'interférence, ou encore par des limitations en bande-passante, en puissance transmise ou en rapport-signal à bruit. Afin de restituer au mieux l'information numérique, le récepteur a en général besoin de disposer d'une connaissance précise du canal. Une grande partie de mes travaux s'est intéressé à l'estimation dynamique des paramètres de ce canal (retards, phases, amplitudes, décalages Doppler, ...), et en particulier à la synchronisation du récepteur. Quelques autres travaux se sont intéressés seulement à la restitution de l'information (tâches de ''détection'' ou d' ''égalisation'') par le récepteur une fois le canal estimé, ou à des schémas d'émission / réception spécifiques. La synthèse des travaux commence par une introduction générale décrivant les ''canaux de communications'' et leurs problèmes potentiels, et positionne chacun de mes travaux en ces termes. Une première partie s'intéresse aux techniques de réception pour les signaux à spectre étalé des systèmes d'accès multiple à répartition par codes (CDMA). Ces systèmes large-bande offrent un fort pouvoir de résolution temporelle et des degrés de liberté, que nous avons exploités pour étudier l'égalisation et la synchronisation (de retard et de phase) en présence de trajets multiples et d'utilisateurs multiples. La première partie regroupe aussi d'autres schémas d'émission/réception, proposés pour leur robustesse dans différents scénarios (schéma à diversité pour canaux à évanouissement plats, schéma à forte efficacité énergétique, ...). La seconde partie est consacrée à l'estimation dynamique Bayésienne des paramètres du canal. On suppose ici qu'une partie des paramètres à estimer exhibe des variations temporelles aléatoires selon une certaine loi à priori. Nous proposons d'abord des estimateurs et des bornes minimales d'estimation pour des modèles de transmission relativement complexes, en raison de la distorsion temporelle due à la forte mobilité en modulation multi-porteuse (OFDM), ou de la présence de plusieurs paramètres à estimer conjointement, ou encore de non linéarités dans les modèles. Nous nous focalisons ensuite sur le problème d'estimation des amplitudes complexes des trajets d'un canal à évolution lente (à 1 ou plusieurs bonds). Nous proposons des estimateurs récursifs (dénommés CATL, pour ''Complex Amplitude Tracking Loop'') à structure imposée inspirée par les boucles à verrouillage de phase numériques, de performance asymptotiques proches des bornes minimales. Les formules analytiques approchées de performances asymptotiques et de réglages de ces estimateurs sont établies sous forme de simples fonctions des paramètres physiques (spectre Doppler, retards, niveau de bruit). Puis étant donné les liens établis entre ces estimateurs CATL et certains filtres de Kalman (construits pour des modèles d'état de type marche aléatoire intégrée), les formules approchées de performances asymptotiques et de réglage de ces filtres de Kalman sont aussi dérivées

Channel Prediction for Mobile MIMO Wireless Communication Systems

Temporal variation and frequency selectivity of wireless channels constitute a major drawback to the attainment of high gains in capacity and reliability offered by multiple antennas at the transmitter and receiver of a mobile communication system. Limited feedback and adaptive transmission schemes such as adaptive modulation and coding, antenna selection, power allocation and scheduling have the potential to provide the platform of attaining the high transmission rate, capacity and QoS requirements in current and future wireless communication systems. Theses schemes require both the transmitter and receiver to have accurate knowledge of Channel State Information (CSI). In Time Division Duplex (TDD) systems, CSI at the transmitter can be obtained using channel reciprocity. In Frequency Division Duplex (FDD) systems, however, CSI is typically estimated at the receiver and fed back to the transmitter via a low-rate feedback link. Due to the inherent time delays in estimation, processing and feedback, the CSI obtained from the receiver may become outdated before its actual usage at the transmitter. This results in significant performance loss, especially in high mobility environments. There is therefore a need to extrapolate the varying channel into the future, far enough to account for the delay and mitigate the performance degradation. The research in this thesis investigates parametric modeling and prediction of mobile MIMO channels for both narrowband and wideband systems. The focus is on schemes that utilize the additional spatial information offered by multiple sampling of the wave-field in multi-antenna systems to aid channel prediction. The research has led to the development of several algorithms which can be used for long range extrapolation of time-varyingchannels. Based on spatial channel modeling approaches, simple and efficient methods for the extrapolation of narrowband MIMO channels are proposed. Various extensions were also developed. These include methods for wideband channels, transmission using polarized antenna arrays, and mobile-to-mobile systems. Performance bounds on the estimation and prediction error are vital when evaluating channel estimation and prediction schemes. For this purpose, analytical expressions for bound on the estimation and prediction of polarized and non-polarized MIMO channels are derived. Using the vector formulation of the Cramer Rao bound for function of parameters, readily interpretable closed-form expressions for the prediction error bounds were found for cases with Uniform Linear Array (ULA) and Uniform Planar Array (UPA). The derived performance bounds are very simple and so provide insight into system design. The performance of the proposed algorithms was evaluated using standardized channel models. The effects of the temporal variation of multipath parameters on prediction is studied and methods for jointly tracking the channel parameters are developed. The algorithms presented can be utilized to enhance the performance of limited feedback and adaptive MIMO transmission schemes

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems