Resource allocation for uplink non-orthogonal multiple access in virtualized wireless networks
Notice bibliographique
Résumé
Wireless networks are strained by an exponential growth in mobile network traffic and new applications, such as the internet-of-things (IoT) paradigm and smart cities, are amplifying the problem as the density of networks increases. At the same time, network providers are faced with increasing infrastructure and service deployment costs which are not being offset by increased revenues. Multi-carrier non-orthogonal multiple access (NOMA) and virtualized wireless networks (VWN) are being positioned as promising techniques to jointly meet the needs of future network users and service providers by promoting the mutualization of network hardware and sharing of spectrum resources. With NOMA, sub-carriers can be shared by several users concurrently, with resulting reduction in spectrum requirements via increased spectral efficiency and re-use, increased power efficiency, and network density. Under VWN, hardware and radio resources are shared by several service providers with groups of users isolated from one another by minimum quality of service guarantees. The use of NOMA in VWNs has not been extensively studied and, due to the nature of wireless channels and user mobility, careful dynamic resource allocation is required to maintain system and user performance.The purpose of this work is to study NOMA-based VWNs and propose efficient resource allocation algorithms to leverage the available gains for users and service and infrastructure providers. Specifically, the use of NOMA for uplink transmissions is examined due to the many proposed use-cases, such as distributed sensor networks, for which uplink traffic far outweighs downlink and the greater capability of base stations in processing concurrent user signals. Initially, performance of NOMA VWN in single-input single-output channels with perfect processing of received signals is examined. With the goal of minimizing required transmit power for battery-dependent devices, an efficient iterative algorithm is presented. The proposed algorithm is then extended to multiple-input multiple-output systems and a sensitivity analysis to increased interference from imperfect processing of received signals is presented. Since many of the proposed use-cases support critical applications such as health and public safety monitoring, we then examine the use of NOMA VWN subject to reliability constraints. The resource allocation problem is mapped to its robust counterpart and the techniques of chance-constrained robust optimization are used to develop an efficient iterative algorithm which minimizes required transmit power subject to user rate and outage constraints. In each of these scenarios, simulation results are presented demonstrating the performance of the proposed algorithms and the improvement compared to traditional orthogonal multiple access is evaluated.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| 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 | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, pas un consensus.
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