论文标题

Min-Max公平资源分配框架,用于多租户O-Rans中的光学X-Haul和DU/CU

A Min-Max Fair Resource Allocation Framework for Optical x-haul and DU/CU in Multi-tenant O-RANs

论文作者

Mondal, Sourav, Ruffini, Marco

论文摘要

最近提出的开放式Radio访问网络(O-RAN)体系结构包含云化和网络功能虚拟化技术,以通过分离聚集的无线电单元(RUS),分布式单元(DUS)和集中式单元(CUS)执行基本频段函数处理。这使得云式视觉完全可以完整,其中移动网络运营商(MNOS)可以安装自己的RUS,但随后通过开放的X-HAUL界面从常见的开放式露头(O-Cloud)服务器中租用按需计算资源来处理DU和CU功能,这是由于负载变化而导致的。这创建了一个多租户方案,其中多个MNO共享网络和计算资源。在本文中,我们提出了一个框架,该框架会在具有Min-Max公平保证的多租户O-Ran生态系统中动态分配X-Haul和Du/Cu资源。该框架可确保最大数量的RU获得足够的资源,同时最大程度地减少其MNO的OPEX。此外,为了提供一个能够维持RUS和Edge计算设备之间低延节和高容量的访问网络体系结构,我们考虑了时间波长多路复用(TWDM)被动光学网络(PON)基于X-HAUL接口,其中PON虚拟技术用于在Endpoints之间提供直接的光学连接。这在所有节点之间创建了虚拟网格互连,以便可以将RUS连接到Macro-Cell RU位置的Edge-Clouds以及中央办公室位置的O-Cloud服务器。此外,我们通过提出的框架分析了系统性能,并表明MNO可以比基线贪婪资源分配更高的成本效率和统一的成本分配。

The recently proposed open-radio access network (O-RAN) architecture embraces cloudification and network function virtualization techniques to perform the base-band function processing by dis-aggregated radio units (RUs), distributed units (DUs), and centralized units (CUs). This enables the cloud-RAN vision in full, where mobile network operators (MNOs) could install their own RUs, but then lease on-demand computational resources for the processing of DU and CU functions from commonly available open-cloud (O-Cloud) servers via open x-haul interfaces due to variation of load over the day. This creates a multi-tenant scenario where multiple MNOs share networking as well as computational resources. In this paper, we propose a framework that dynamically allocates x-haul and DU/CU resources in a multi-tenant O-RAN ecosystem with min-max fairness guarantees. This framework ensures that a maximum number of RUs get sufficient resources while minimizing the OPEX for their MNOs. Moreover, in order to provide an access network architecture capable of sustaining low-latency and high capacity between RUs and edge-computing devices, we consider time-wavelength division multiplexed (TWDM) passive optical network (PON)-based x-haul interfaces where the PON virtualization technique is used to provide a direct optical connection between end-points. This creates a virtual mesh interconnection among all the nodes such that the RUs can be connected to the Edge-Clouds at macro-cell RU locations as well as to the O-Cloud servers at the central office locations. Furthermore, we analyze the system performance with our proposed framework and show that MNOs can operate with a better cost-efficiency than baseline greedy resource allocation with uniform cost-sharing.

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