论文标题
用于建模室内5G毫米波传播的合并随机和物理框架
A Combined Stochastic and Physical Framework for Modeling Indoor 5G Millimeter Wave Propagation
论文作者
论文摘要
室内覆盖范围是5G毫米波（MMWaves）的主要挑战。在本文中，我们通过一个新颖的理论框架来解决这个问题，该框架将随机室内环境建模与先进的物理传播模拟相结合。这种方法特别适合研究室内到室内5G MMWAVE的传播。它的系统实现（所谓的Igeostat）生成了解释室内空间变化的参数化典型环境，然后根据电磁波和材料属性之间的物理相互作用模拟无线电传播。该框架不专门用于特定的环境，材料，频率或用例，旨在从统计上理解室内环境参数对MMWave传播属性的影响，尤其是覆盖范围和路径损失。它的实施提出了许多计算挑战，我们通过制定适应性的链接预算并设计新的内存优化算法来解决这些挑战。两个主要5G应用程序的第一个仿真结果通过测量数据验证，并显示Igeostat在合理量的时间和内存资源内模拟在现实环境中模拟多个扩散的效率。生成的输出图证实，扩散对室内MMWave的传播有关键影响，并且适当的物理建模对于生成相关的传播模型至关重要。
Indoor coverage is a major challenge for 5G millimeter waves (mmWaves). In this paper, we address this problem through a novel theoretical framework that combines stochastic indoor environment modeling with advanced physical propagation simulation. This approach is particularly adapted to investigate indoor-to-indoor 5G mmWave propagation. Its system implementation, so-called iGeoStat, generates parameterized typical environments that account for the indoor spatial variations, then simulates radio propagation based on the physical interaction between electromagnetic waves and material properties. This framework is not dedicated to a particular environment, material, frequency or use case and aims to statistically understand the influence of indoor environment parameters on mmWave propagation properties, especially coverage and path loss. Its implementation raises numerous computational challenges that we solve by formulating an adapted link budget and designing new memory optimization algorithms. The first simulation results for two major 5G applications are validated with measurement data and show the efficiency of iGeoStat to simulate multiple diffusion in realistic environments, within a reasonable amount of time and memory resources. Generated output maps confirm that diffusion has a critical impact on indoor mmWave propagation and that proper physical modeling is of the utmost importance to generate relevant propagation models.
