超密集网络的覆盖分析和标度律
Coverage Analysis and Scaling Laws of Ultra-Dense Networks
摘要：
在本文中，我们开发了一种创新的方法来定量表征超密集无线网络在过多的传播环境中的性能。所提出的框架有可能显着简化繁琐的程序分析的覆盖概率，并允许显着的统一，通过紧凑的表示单天线和多天线网络。通过利用这一关键功能，我们开发了一种新的统计机器来研究无线网络致密化的缩放规律，考虑到一般的信道功率分布，包括整个空间的多径和阴影模型，以及由于使用多个天线的相关波束成形增益。我们进一步制定网络密度，天线高度，天线阵列占有率和载波频率之间的关系，显示如何可以保持超致密化的覆盖概率。从系统设计的角度来看，我们提出了一个新的创新的理论发现，规定如果多个天线BS部署和移动到更高的频率，然后单调增加的覆盖概率通过超致密化是可能的，这不会降低天线高度。这一发现与现有研究中的结论完全不同，后者建议降低基站高度以利用网络致密化的潜力。仿真结果证实了利用网络致密化和天线部署和配置对路径损耗模型和信号噪声加干扰（SINR）阈值的性能趋势。
英文摘要：
In this paper, we develop an innovative approach to quantitatively characterize the performance of ultra-dense wireless networks in a plethora of propagation environments. The proposed framework has the potential of significantly simplifying the cumbersome procedure of analyzing the coverage probability and allowing the remarkable unification of single- and multi-antenna networks through compact representations. By harnessing this key feature, we develop a novel statistical machinery to study the scaling laws of wireless network densification considering general channel power distributions including the entire space of multipath and shadowing models as well as associated beamforming gain due to the use of multiple antenna. We further formulate the relationship between network density, antenna height, antenna array seize and carrier frequency showing how the coverage probability can be maintained with ultra-densification. From a system design perspective, we present a new innovative theoretical discovery stipulating that if multiple antenna BS are deployed and moved to higher frequencies, then monotonically increasing the coverage probability by means of ultra-densification is possible, and this without lowering the antenna height. Such findings are completely different from the conclusions in existing works, who suggest to lower the BS height as to leverage the potential of network densification. Simulation results substantiate performance trends leveraging network densification and antenna deployment and configuration against path loss models and signal-to-noise plus interference (SINR) thresholds.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
