Traffic Steering for eMBB and uRLLC Coexistence in Open Radio Access Networks

Fatemeh Kavehmadavani, Van-Dinh Nguyen, T. Vu, S. Chatzinotas
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引用次数: 5

Abstract

Existing radio access network (RAN) architectures are lack of sufficient openness, flexibility, and intelligence to meet the diverse demands of emerging services in beyond 5G and 6G wireless networks, including enhanced mobile broadband (eMBB) and ultra-reliable and low-latency (uRLLC). Open RAN (ORAN) is a promising paradigm that allows building a virtualized and intelligent architecture. In this paper, we focus on traffic steering (TS) scheme based on multi-connectivity (MC) and network slicing (NS) techniques to efficiently allocate heterogeneous network resources in “NextG” cellular networks. We formulate the RAN resource allocation problem to simultaneously maximize the weighted sum eMBB throughput and minimize the worst-user uRLLC latency subject to QoS requirements, and orthogonality, power, and limited fronthaul constraints. Since the formulated problem is categorized as a mixed integer nonlinear problem (MINLP), we first relax binary variables to continuous ones and develop an efficient iterative algorithm based on successive convex approximation technique. System-level simulation results demon-strate the effectiveness of the proposed algorithm, compared to several well-known benchmark schemes.
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开放无线接入网中eMBB和uRLLC共存的流量控制
现有RAN (radio access network)架构缺乏足够的开放性、灵活性和智能性,无法满足增强型移动宽带(eMBB)和超可靠低延迟(uRLLC)等5G和6G以外无线网络新兴业务的多样化需求。开放RAN (ORAN)是一种很有前途的范例,它允许构建虚拟化和智能架构。本文重点研究了基于多连接(MC)和网络切片(NS)技术的流量导向(TS)方案,以有效地分配“NextG”蜂窝网络中的异构网络资源。我们制定了RAN资源分配问题,在QoS要求、正交性、功率和有限前传约束下,同时最大化加权和eMBB吞吐量和最小化最差用户uRLLC延迟。由于该问题属于混合整数非线性问题(MINLP),我们首先将二元变量松弛为连续变量,并开发了一种基于连续凸逼近技术的高效迭代算法。系统级仿真结果证明了该算法的有效性,并与几种知名的基准方案进行了比较。
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