Space-time diversity for CDMA systems over frequency-selective fading channels
Notice bibliographique
Résumé
Supporting the expected high data rates required by wireless Internet and high-speed multimedia services is one of the basic requirements in broadband mobile wireless systems. However, the achievable capacity and data rate of wireless communication systems are limited by the time-varying nature of the channel. Efficient techniques for combating the time-varying effects of wireless channels can be achieved by utilizing different forms of diversity. In recent years, transmit diversity based on space-time coding (STC) has received more attention as an effective technique for combating fading. On the other hand, most existing space-time diversity techniques have been developed for flat-fading channels. Given the fact that wireless channels are generally frequency-selective, in this thesis, we aim to investigate the performance of space-time diversity schemes for wideband code-division multiple-access (WCDMA) systems over frequency-selective fading channels. The proposed receiver in this case is a rake-type receiver, which exploits the path diversity inherent to multipath propagation. Then, a decorrelator detector is used to mitigate the multiple access interference (MAI) and the known near-far problem. We derive the bit error rate (BER) expression over frequency-selective fading channels considering both the fast and slow fading cases. Finally, we show that our proposed receiver achieves the full system diversity through simulation and analytical results. Most of the work conducted in this area considers perfect knowledge of the channel at the receiver. Hence, channel identification brings significant challenges to multiple-input multiple-output (MIMO) CDMA systems. In light of this, we propose a channel estimation and data detection scheme based on the superimposed training-based approach. The proposed scheme enhances the performance by eliminating the MAI from both the channel and data estimates by employing two decorrelators; channel and data decorrelators. The performance of the proposed estimation technique is investigated over frequency-selective slow fading channels where we derived a closed-form expression for the BER as a function of the number of users, K , the number resolvable paths, L , and the number of receive antennas, V . Finally, our proposed scheme is shown to be more robust to channel estimation errors. Furthermore, both the analytical and simulation results indicate that the full system diversity is achieved. Considering that training estimation techniques suffer either from low spectral efficiency (i.e., conventional training approach) or from high pilot power consumption (i.e., superimposed training-based approach), in the last part of the thesis, we present an iterative joint detection and estimation (JDE) using the expectation-maximization (EM) algorithm for MIMO CDMA systems over frequency-selective fading channels. We also derive a closed-form expression for the optimized weight coefficients of the EM algorithm, which was shown to provide significant performance enhancement relative to the conventional equal-weight EM-based signal decomposition. Finally, our simulation results illustrate that the proposed receiver achieves near-optimum performance with modest complexity using very few training symbols.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».