Spelling suggestions: "subject:"adaptative modulation"" "subject:"daptative modulation""
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Indoor radio propagation modeling for system performance predictionLuo, Meiling 17 July 2013 (has links) (PDF)
This thesis aims at proposing all the possible enhancements for the Multi-Resolution Frequency-Domain ParFlow (MR-FDPF) model. As a deterministic radio propagation model, the MR-FDPF model possesses the property of a high level of accuracy, but it also suffers from some common limitations of deterministic models. For instance, realistic radio channels are not deterministic but a kind of random processes due to, e.g. moving people or moving objects, thus they can not be completely described by a purely deterministic model. In this thesis, a semi-deterministic model is proposed based on the deterministic MR-FDPF model which introduces a stochastic part to take into account the randomness of realistic radio channels. The deterministic part of the semi-deterministic model is the mean path loss, and the stochastic part comes from the shadow fading and the small scale fading. Besides, many radio propagation simulators provide only the mean power predictions. However, only mean power is not enough to fully describe the behavior of radio channels. It has been shown that fading has also an important impact on the radio system performance. Thus, a fine radio propagation simulator should also be able to provide the fading information, and then an accurate Bit Error Rate (BER) prediction can be achieved. In this thesis, the fading information is extracted based on the MR-FDPF model and then a realistic BER is predicted. Finally, the realistic prediction of the BER allows the implementation of the adaptive modulation scheme. This has been done in the thesis for three systems, the Single-Input Single-Output (SISO) systems, the Maximum Ratio Combining (MRC) diversity systems and the wideband Orthogonal Frequency-Division Multiplexing (OFDM) systems.
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Indoor radio propagation modeling for system performance prediction / Modélisation de la propagation radio en intérieur pour la prédiction des performances des systèmes radiosXie, Meiling 17 July 2013 (has links)
Cette thèse a pour but de proposer toutes les avancées possibles dans l’utilisation du modèle de propagation Multi-Resolution Frequency-Domain ParFlow (MR-FDPF). Etant un modèle de propagation radio déterministe, le modèle MR-FDPF possède un haut niveau de précision, mais souffre des limitations communes à tous les modèles déterministes. Par exemple, un canal radio réel n’est pas déterministe, mais un processus aléatoire à cause par exemple des personnes ou objets mobiles, et ne peut donc être décrit fidèlement par un modèle purement déterministe. Dans cette thèse, un modèle semi-déterministe est proposé, basé sur le modèle MR-FDPF, qui introduit une part stochastique pour tenir compte des aspects aléatoires du canal radio réaliste. La partie déterministe du modèle est composée du path loss (atténuation d’espace), et la partie stochastique venant du shadow fading (masquage) et du small scale fading (évanouissement). De même, de nombreux simulateurs de propagation radio ne proposent que la prédiction de la puissance moyenne. Mais pour une simulation précise de la propagation radio il convient de prédire également des informations de fading permettant dès lors une prédiction précise du taux d’erreur binaire (BER) potentiel. Dans cette thèse, l’information de fading est déduite des simulations MR-FDPF et par la suite des valeurs réalistes de BER sont données. Enfin, ces données réalistes de BER permettent d’évaluer l’impact de schémas de modulation adaptatifs. Des résultats sont présentés dans trois configurations : systèmes SISO (mono-antenne à l’émission et à la réception), systèmes à diversité de type MRC, et systèmes large bande de type OFDM. / This thesis aims at proposing all the possible enhancements for the Multi-Resolution Frequency-Domain ParFlow (MR-FDPF) model. As a deterministic radio propagation model, the MR-FDPF model possesses the property of a high level of accuracy, but it also suffers from some common limitations of deterministic models. For instance, realistic radio channels are not deterministic but a kind of random processes due to, e.g. moving people or moving objects, thus they can not be completely described by a purely deterministic model. In this thesis, a semi-deterministic model is proposed based on the deterministic MR-FDPF model which introduces a stochastic part to take into account the randomness of realistic radio channels. The deterministic part of the semi-deterministic model is the mean path loss, and the stochastic part comes from the shadow fading and the small scale fading. Besides, many radio propagation simulators provide only the mean power predictions. However, only mean power is not enough to fully describe the behavior of radio channels. It has been shown that fading has also an important impact on the radio system performance. Thus, a fine radio propagation simulator should also be able to provide the fading information, and then an accurate Bit Error Rate (BER) prediction can be achieved. In this thesis, the fading information is extracted based on the MR-FDPF model and then a realistic BER is predicted. Finally, the realistic prediction of the BER allows the implementation of the adaptive modulation scheme. This has been done in the thesis for three systems, the Single-Input Single-Output (SISO) systems, the Maximum Ratio Combining (MRC) diversity systems and the wideband Orthogonal Frequency-Division Multiplexing (OFDM) systems.
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