用于5G网络系统级仿真的新无线电物理层抽象
New Radio Physical Layer Abstraction for System-Level Simulations of 5G Networks
摘要：
物理层（PHY）抽象模型估计系统级仿真器中的PHY性能以加速仿真。本文提出了一种用于5G新无线电（NR）的PHY抽象模型，并将其集成到基于开源ns-3的NR系统级仿真器中。该模型利用指数有效信号干扰噪声比（SINR）映射（EESM），并考虑最新的NR规范。为了生成它，我们使用NR兼容的链路级模拟器来校准EESM方法，以及获得各种NR配置的SINR块出错率（BLER）查找表。我们还说明了开发的模型的可用性，通过端到端的仿真在ns-3，根据不同的NR设置的调制和编码方案，混合自动重传请求组合方法，和链路自适应方法。
英文摘要：
A physical layer (PHY) abstraction model estimates the PHY performance in system-level simulators to speed up the simulations. This paper presents a PHY abstraction model for 5G New Radio (NR) and its integration into an open-source ns-3 based NR system-level simulator. The model capitalizes on the exponential effective signal-to-interference-plus-noise ratio (SINR) mapping (EESM) and considers the latest NR specification. To generate it, we used an NR-compliant link-level simulator to calibrate the EESM method as well as to obtain SINR-block error rate (BLER) lookup tables for various NR configurations. We also illustrate the usability of the developed model through end-to-end simulations in ns-3, under different NR settings of modulation and coding schemes, hybrid automatic repeat request combining methods, and link adaptation approaches.
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