Szczegóły publikacji
Opis bibliograficzny
Resource management in LADNs supporting 5G V2X communications / Ren-Hung Hwang, Faysal MARZUK, Marek SIKORA, Piotr CHOŁDA, Ying-Dar Lin // W: VTC2020-Fall [Dokument elektroniczny] : 2020 IEEE 92nd Vehicular Technology Conference : Victoria, Canada, 4–7 October 2020 : proceedings. — Wersja do Windows. — Dane tekstowe. — Piscataway : Institute of Electrical and Electronics Engineers, cop. 2020. — (IEEE Vehicular Technology Conference ; ISSN 1090-3038). — e-ISBN: 978-1-7281-9484-4. — S. [1–6]. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. [6], Abstr. — Publikacja dostępna online od: 2021-02-15
Autorzy (5)
- Hwang Ren-Hung
- AGHMarzuk Faysal
- AGHSikora Marek
- AGHChołda Piotr
- Lin Ying-Dar
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 132640 |
|---|---|
| Data dodania do BaDAP | 2021-02-24 |
| Tekst źródłowy | URL |
| DOI | 10.1109/VTC2020-Fall49728.2020.9348689 |
| Rok publikacji | 2020 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
| Konferencja | 2020 IEEE 92nd Vehicular Technology Conference |
| Czasopismo/seria | IEEE Vehicular Technology Conference |
Abstract
Local access data network (LADN) is a promising paradigm to reduce latency, enable lowering energy consumption, and improve quality of service (QoS) for the Fifth Generation (5G) radio access network (RAN) supporting vehicle to everything (V2X) communications. To achieve optimum resource allocation and save energy by minimizing the activation of LADN servers in Cloud-RAN, some remote radio heads (RRHs) can be turned on or off depending on the traffic demand. In this paper, we investigate the problem of how to realize effective resource management in 5G RAN supporting V2X communications. More precisely, we first propose a formulation of the resource management problem as an optimization problem with the objective of minimizing the number of RRHs to be turned on subject to the uplink bandwidth constraints. We then use a fully-fledged professional software to solve our optimization problem and propose a solution with heuristic algorithms to deal with the complexity of the problem for large scenarios. Moreover, we analyze the impact of the density of vehicles on the computation time and the influence of the uplink data rate and vehicle densities on the number of active RRHs. Our numerical results show that our proposed model can efficiently utilize the resources and provide optimum vehicles-to-RRHs associations which lead to energy-savings. For instance, to serve 100 vehicles with aggregated uplink data rate equal to 100 [Mbps], the optimal associations save about 70% of the energy comparing to the strongest-signal associations. Furthermore, we obtain optimal results for the small size problem in reasonable computation times, which are around 50 [ms].