Resource Management in LADNs Supporting 5G V2X Communications

Ren Hung Hwang, Faysal Marzuk, Marek Sikora, Piotr Cholda, Ying Dar Lin

研究成果: Conference contribution同行評審

摘要

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].

原文English
主出版物標題2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728194844
DOIs
出版狀態Published - 十一月 2020
事件92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada
持續時間: 18 十一月 2020 → …

出版系列

名字IEEE Vehicular Technology Conference
2020-November
ISSN(列印)1550-2252

Conference

Conference92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
國家Canada
城市Virtual, Victoria
期間18/11/20 → …

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