MAC Optimization Based on the Radio Resource Allocation in a 5G eMBB System Simulated in the MmWave Model

Ismail Angri, A. Najid, Mohammed Mahfoudi
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Abstract

5G NR (new radio) systems support multiple use cases, namely enhanced mobile broadband (eMBB), ultra-reliable and low latency communications (URLLC), and massive machine-type communications (mMTC), to meet the needs of different types of applications. The multi users-downlink packet scheduling (MU-DLPS) is used for the 5G NR radio resource management (RRM). In this paper, the authors show that the radio resource scheduling algorithms, which have been applied to 4G, are also efficient and can be used in 5G networks. In this objective, the authors simulated scheduling schemes in a 5G eMBB environment. The algorithms were developed in C++ for the first time and were simulated using the mmWave model of the NS-3 simulator. Mobility scenarios with fixed and mobile nodes have been implemented. The comparison was made using python programs, newly and specifically developed for the data extraction. The results show that five strategies achieve remarkable values in terms of system throughput and downlink latency.
基于毫米波模型仿真的5G eMBB系统无线资源分配MAC优化
5G新空口(新无线电)系统支持增强型移动宽带(eMBB)、超可靠低延迟通信(URLLC)和大规模机器型通信(mMTC)等多种用例,以满足不同类型应用的需求。MU-DLPS (multi - user -downlink packet scheduling)用于5G NR的RRM (radio resource management)。在本文中,作者证明了已经应用于4G网络的无线电资源调度算法也是高效的,可以用于5G网络。为此,作者模拟了5G eMBB环境下的调度方案。该算法首次在c++语言中开发,并使用NS-3模拟器的毫米波模型进行了仿真。已实现固定节点和移动节点的移动场景。使用专门为数据提取而开发的新python程序进行比较。结果表明,五种策略在系统吞吐量和下行链路延迟方面取得了显著的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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