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User association and resource allocation in 5G (AURA-5G): A joint optimization framework

机译:5G(Aura-5G)中的用户关联和资源分配:联合优化框架

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5G wireless networks will be extremely dense, given the projected increase in the number of users and access points (APs), as well as heterogeneous, given the different types of APs and the applications being accessed by the users. In such challenging environments, efficient mobility management (MM), and specifically user association, will be critical to assist the 5G networks in provisioning the Quality of Service (QoS) of diverse applications 5G targets to serve. Whilst determining the most suitable AP for the users, multiple constraints such as available backhaul capacity, link latency, etc., will need to be accommodated for. Hence, to provide an optimal user association solution, in this paper we present a joint optimization framework, namely AURA-5G. Under this framework we formulate our user association strategy as a Mixed Integer Linear Program (MILP) that aims to maximize the total sum rate of the network whilst optimizing the bandwidth assignment and access point selection. We analyze multiple active application profiles simultaneously, i.e. enhanced Mobile Broadband (eMBB) and massive Machine Type Communication (mMTC), in the network and study the performance of AURA-5G. Additionally, we provision a novel study on the multiple dual connectivity modes, wherein the user can be connected to either one macro cell and a possible small cell, or with any two favorable candidate access points. Utilizing the AURA-5G framework, we perform a novel comparative study of all the considered scenarios on the basis of total network throughput, performance against baseline scenario and system fairness. We show that the AURA-5G optimal solutions improve the performance of different network scenarios in terms of total network throughput (by 38x-690x) and system fairness as compared to the baseline scenario, which is a conventional user association solution. Further, we also present a fidelity analysis of the AURA-5G framework based on the backhaul utilization, latency compliance, convergence time distribution and solvability. And since, a given network cannot always guarantee to satisfy the future network loads and application constraints, we show that AURA-5G can be utilized by the operators/vendors to evaluate the myriad network re-dimensioning approaches for attaining a feasible and optimal solution. Henceforth, we then explore the possibility of network re-dimensioning and study its impact on system performance for scenarios where the performance of AURA-5G is severely impacted due to the extremely strict nature of the constraints imposed in the MILP.
机译:鉴于用户和接入点数(AP)的数量和访问点(AP)以及给定不同类型的AP和用户访问的应用程序,提供5G无线网络将非常密集。在这样的具有挑战性的环境中,有效的移动管理(MM)和专门的用户关联,对于协助5G网络提供提供各种应用5G目标的服务质量(QoS)来辅助5G网络是至关重要的。虽然确定用户最合适的AP,但需要适应多种约束,例如可用回程等,链接延迟等。因此,为了提供最佳的用户关联解决方案,本文介绍了联合优化框架,即Aura-5G。在此框架下,我们将用户关联策略制定为混合整数线性程序(MILP),该程序旨在最大限度地提高网络的总金额,同时优化带宽分配和接入点选择。我们同时分析多个活动应用程序配置文件,即,在网络中增强了移动宽带(embb)和大量机器类型通信(MMTC),研究了Aura-5G的性能。另外,我们为多个双连接模式提供了一种新的研究,其中用户可以连接到一个宏小区和可能的小小区,或者与任何两个有利的候选接入点连接。利用Aura-5G框架,我们在全网络吞吐量的基础上进行了对所有所考虑的情景的新比较研究,对基线情景和系统公平性能进行性能。我们表明,与基线场景相比,Aura-5G最优解决方案在总网络吞吐量(通过38X-690x)和系统公平方面,提高了不同网络方案的性能。此外,我们还基于回程利用率,延迟合规性,收敛时间分布和可解性来呈现Aura-5G框架的保真分析。并且,由于给定的网络不能始终保证满足未来的网络负载和应用限制,我们表明,操作员/供应商可以利用Aura-5G来评估Myriad网络的重大维度方法,以实现可行和最佳的解决方案。从此,我们探讨了网络重复尺寸的可能性,并研究其对系统性能的影响,因为由于在MILP中施加的限制的极其严格的性质,Aura-5G的性能受到严重影响的情况。

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