论文标题
用于系统级别评估5G异质蜂窝网络的空间索引
Spatial Indexing for System-Level Evaluation of 5G Heterogeneous Cellular Networks
论文作者
论文摘要
大型5G网络的系统级模拟对于评估和设计与网络问题（例如调度，移动性管理，干扰管理和细胞计划）相关的算法至关重要。在本文中，我们回顾了空间索引及其优势，应用和未来在加速大型5G网络模拟方面的想法。我们引入了基于多级继承的体系结构，该体系结构用于索引单个几何树上异质网络（HETNET）的所有元素。然后，我们定义空间查询以加速距离，方位角和高程的搜索。我们证明空间索引可以通过3个数量级加速基于位置的搜索。此外，提出的设计将作为一个自由使用的开源平台实现。
System level simulations of large 5G networks are essential to evaluate and design algorithms related to network issues such as scheduling, mobility management, interference management, and cell planning. In this paper, we look back to the idea of spatial indexing and its advantages, applications, and future potentials in accelerating large 5G network simulations. We introduce a multi-level inheritance based architecture which is used to index all elements of a heterogeneous network (HetNet) on a single geometry tree. Then, we define spatial queries to accelerate searches in distance, azimuth, and elevation. We demonstrate that spatial indexing can accelerate location-based searches by 3 orders of magnitude. Further, the proposed design is implemented as an open source platform freely available to all.
