No / Narrowband path loss measurements are reported for the vehicle-to-vehicle channel between a transmitting antenna 50 cm above the ground and a car-roof-mounted receiver array. Calibration procedures and measurement results are reported for typical urban, suburban and rural-motorway environments and compared with existing mobile channel models to give insight into the large-scale fading behavior in the vehicle-to-vehicle channel.

La performance de démodulation des signaux GNSS existants, GPS L1 C/A, L2C ou L5, est satisfaisante en environnements ouverts où le C/N0 disponible est assez élevé. Cependant, en milieu urbain, le niveau de C/N0 du signal reçu est souvent très bas et est affecté de variations rapides qui peuvent nuire la démodulation des messages GNSS. Donc, car les applications du marché de masse sont appelées à être déployées dans ces environnements, il est nécessaire d'étudier et de chercher des méthodes de démodulation/décodage qui améliorent la performance de démodulation des messages GNSS dans ces environnements. Il est aussi nécessaire de considérer les nouveaux signaux GPS L1C et GALILEO E1. Ces signaux doivent fournir un service de positionnement par satellite dans tout type d'environnement, et spécifiquement en milieu urbain. Ainsi, cette thèse analyse aussi les performances de démodulation des nouveaux signaux GNSS tels que définis dans les documents publics actuels. De plus, de nouvelles structures de message GALILEO E1 sont proposées et analysées afin d'optimiser la performance de démodulation ainsi que la quantité d'information diffusée. En conséquence, le but principal de cette thèse est d'analyser et améliorer la performance de démodulation des signaux GNSS ouverts au public, spécifiquement en milieu urbain, et de proposer de nouvelles structures de messages de navigation pour GALILEO E1. La structure détaillée des chapitres de cette thèse est donnée ci-après. En premier lieu, le sujet de cette thèse est introduit, ses contributions originales sont mises en avant, et le plan du rapport est présenté. Dans le 2ième chapitre, la thèse décrit la structure actuelle des signaux GNSS analysés, en se concentrant sur la structure du message de navigation, les codages canal implantés et leurs techniques de décodage. Dans le 3ième chapitre, deux types de modèles de canal de propagation sont présentés pour deux différents types de scénarios. D'un côté, un canal AWGN est choisi pour modéliser les environnements ouverts. De l'autre côté, le modèle mathématique de Perez-Fontan d'un canal mobile est choisi pour représenter les environnements urbains et indoor. Dans le 4ième chapitre, une tentative pour effectuer une prédiction binaire d'une partie du message de navigation GPS L1 C/A est présentée. La prédiction est essayée en utilisant les almanachs GPS L1 C/A, grâce à un programme de prédiction à long terme fourni par TAS-F, et des méthodes de traitement du signal: estimation spectrale, méthode de PRONY et réseau de neurones. Dans le 5ème chapitre, des améliorations à la performance de démodulation du message de GPS L2C et L5 sont apportées en utilisant leur codage canal de manière non traditionnelle. Deux méthodes sont analysées. La première méthode consiste à combiner les codages canal internes et externes du message afin de corriger davantage de mots reçus. La deuxième méthode consiste à utiliser les probabilités des données d'éphémérides afin d'améliorer le décodage traditionnel de Viterbi. Dans le 6ième chapitre, la performance de démodulation des messages de GPS L1C et du Open Service GALILEO E1 est analysée dans différents environnements. D'abord, une étude de la structure de ces deux signaux est présentée pour déterminer le C/N0 du signal utile reçu dans un canal AWGN. Puis, la performance de démodulation de ces signaux est analysée grâce à des simulations dans différents environnements, avec un récepteur se déplaçant à différentes vitesses et avec différentes techniques d'estimation de la phase porteuse du signal. / The demodulation performance achieved by any of the existing GPS signals, L1 C/A, L2C or L5, is satisfactory in open environments where the available C/N0 is quite high. However, in indoor/urban environments, the C/N0 level of the received signal is often very low and suffers fast variations which can further affect the GNSS messages demodulation. Therefore, since the mass-market applications being designed nowadays are aimed at these environments, it is necessary to study and to search alternative demodulation/decoding methods which improve the GNSS messages demodulation performance in these environments. Moreover, new GNSS signals recently developed, such as GPS L1C and GALILEO E1, must also be considered. These signals aim at providing satellite navigation positioning service in any kind of environment, giving special attention to indoor and urban environments. Therefore, the demodulation performances of the new GNSS signals as they are defined in the current public documents is also analysed. Moreover, new GALILEO E1 message structures are proposed and analysed in order to optimize the demodulation performance as well as the quantity of broadcasted information. Therefore, the main goal of this dissertation is to analyse and to improve the demodulation performance of the current open GNSS signals, specifically in indoor and urban environments, and to propose new navigation message structures for GALILEO E1. A detailed structure of this dissertation sections is given next. First, the subject of this thesis is introduced, original contributions are highlighted, and the outline of the report is presented. Second, this dissertation begins by a description of the current structure of the different analysed GNSS signals, paying special attention to the navigation message structure, implemented channel code and their decoding techniques. In the third section, two types of transmission channel models are presented for two different types of environments. On one hand, an AWGN channel is used to model the signal transmission in an open environments. On the other hand, the choice of a specific mobile channel, the Perez-Fontan channel model, is chosen to model the signal transmission in an urban environment. In the fourth section, a tentative to make a binary prediction of the broadcasted satellite ephemeris of the GPS L1 C/A navigation message is presented. The prediction is attempted using the GPS L1 C/A almanacs data, a long term orbital prediction program provided by TAS-F, and some signal processing methods: spectral estimation, the PRONY method, and a neural network. In the fifth section, improvements to the GPS L2C and GPS L5 navigation message demodulation performance are brought by using their channel codes in a non-traditional way. Two methods are inspected. The first method consists in sharing information between the message inner and outer channel codes in order to correct more received words. The second method consists in using the ephemeris data probabilities in order to improve the traditional Viterbi decoding. In the sixth section, the GPS L1C and GALILEO E1 Open Service demodulation performance is analysed in different environments. First, a brief study of the structure of both signals to determine the received C/N0 in an AWGN channel is presented. Second, their demodulation performance is analysed through simulations in different environments, with different receiver speeds and signal carrier phase estimation techniques.

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.