On the performance of practical ultra-dense networks: The major and minor factors

Ming Ding, D. López-Pérez
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引用次数: 42

Abstract

In this paper, we conduct performance evaluation for Ultra-Dense Networks (UDNs), and identify which modelling factors play major roles and minor roles. From our study, we draw the following conclusions. First, there are 3 factors/models that have a major impact on the performance of UDNs, and they should be considered when performing theoretical analyses: i) a multi-piece path loss model with line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions; ii) a non-zero antenna height difference between base stations (BSs) and user equipments (UEs); iii) a finite BS/UE density. Second, there are 4 factors/models that have a minor impact on the performance of UDNs, i.e., changing the results quantitatively but not qualitatively, and thus their incorporation into theoretical analyses is less urgent: i) a general multi-path fading model based on Rician fading; ii) a correlated shadow fading model; iii) a BS density dependent transmission power; iv) a deterministic BS/user density. Finally, there are 5 factors/models for future study: i) a BS vertical antenna pattern; ii) multi-antenna and/or multi-BS joint transmissions; iii) a proportional fair BS scheduler; iv) a non-uniform distribution of BSs; v) a dynamic time division duplex (TDD) or full duplex (FD) network. Our conclusions can guide researchers to down-select the assumptions in their theoretical analyses, so as to avoid unnecessarily complicated results, while still capturing the fundamentals of UDNs in a meaningful way.
实用超密集网络的性能:主要和次要因素
在本文中,我们对超密集网络(udn)进行了性能评估,并确定了哪些建模因素起主要作用和次要作用。从我们的研究中,我们得出以下结论。首先,有3个因素/模型对udn的性能有重大影响,在进行理论分析时应考虑这些因素/模型:i)具有视距(LoS)和非视距(NLoS)传输的多片路径损耗模型;ii)基站与用户设备之间的天线高度差不为零;iii)有限的BS/UE密度。其次,有4个因素/模型对udn的性能影响较小,即定量改变结果而不是定性改变结果,因此将其纳入理论分析的紧迫性较低:1)基于fourier衰落的通用多径衰落模型;Ii)相关阴影衰落模型;iii)与BS密度相关的传输功率;iv)确定的BS/用户密度。最后,有5个因素/模型可供未来研究:1)BS垂直天线方向图;ii)多天线和/或多bs联合传输;iii)一个比例公平的BS调度程序;iv) BSs分布不均匀;v)动态时分双工(TDD)或全双工(FD)网络。我们的结论可以指导研究者在进行理论分析时减少假设的选择,从而避免不必要的复杂结果,同时仍能以有意义的方式捕捉到udn的基本原理。
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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