基于多命理的5G NR系统信道感知和qos感知下行资源分配

Luciano Miuccio, D. Panno, P. Pisacane, Salvatore Riolo
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引用次数: 2

摘要

支持异构5G使用场景所需的多功能性和灵活性涉及引入基于多数字命数学的5G新无线电(NR)系统,其中具有不同子载波间距的多个帧结构共存于同一无线电频谱中。虽然这种方法能够有效地满足多种业务需求,但它在不同的非正交数字系统之间引入了无线电资源分配的新问题。这项工作引入了一个新的服务质量(QoS)感知无线电资源管理(RRM)框架,该框架调度需要不同优先级的保证比特率(GBR)服务或非GBR服务的用户设备(ue)。为了最大限度地提高频谱效率,从而提高系统吞吐量,该框架由两个通道感知控制级别组成。第一级在各种数字命理学之间提供频谱的动态细分,而第二级将物理资源块(PRBs)调度到属于同一数字命理学的ue。在本文中,我们提出了一种新的第一级分配算法,称为通道感知的多数字资源分配(CARAM),该算法旨在最大限度地提高系统吞吐量和满足用户的数量,同时考虑优先级。作为第二级控制,我们利用了著名的调度算法。我们通过几个系统级模拟,在不同的流量负载和信道条件下,将我们的方法与其他现有的一级分配算法进行基准测试。对比分析表明,我们的RRM框架在系统吞吐量方面优于参考方案,同时保证了大量高优先级的GBR服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Channel-Aware and QoS-Aware Downlink Resource Allocation for Multi-numerology Based 5G NR Systems
The versatility and flexibility needed to support heterogeneous 5G usage scenarios involves the introduction of multi-numerology based 5G New Radio (NR) systems, where multiple frame structures with different sub-carrier spacing coexists in the same radio spectrum. Although this approach is efficient to cater a wide variety of services, it introduces a new issue in the radio resource allocation among the different non-orthogonal numerologies. This work introduces a new Quality of Service (QoS) aware Radio Resource Management (RRM) framework which schedules User Equipments (UEs) requiring Guaranteed Bit Rate (GBR) services with different priorities, or non-GBR services. In order to maximize the spectral efficiency and, consequently, the system throughput, this framework consists of two channel-aware control levels. The first level provides a dynamic subdivision of the spectrum among the various numerologies, while the second one schedules the Physical Resource Blocks (PRBs) to the UEs belonging to the same numerology. In this paper, we propose a new 1st level allocation algorithm, called Channel-Aware Resource Allocation for Multi-numerology (CARAM), which aims to maximize the system throughput and the amount of satisfied users, taking into account the priority. As 2nd control level, we exploit well-known scheduling algorithms. We benchmark our approach against other existing 1st level allocation algorithms via several system-level simulations, under different traffic loads and channel conditions. The comparative analysis shows that our RRM framework outperforms the reference schemes in terms of system throughput, while guaranteeing a larger number of GBR services with high priority.
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