论文标题
5G路由干扰环境
5G Routing Interfered Environment
论文作者
论文摘要
5G是下一代蜂窝网络技术，其目的是满足容纳高密度用户所需的带宽的关键需求。它采用灵活的体系结构来容纳高密度。 MMWave Communication启用了5G，该通信的频率为30至300 GHz。本文介绍了5G路由干扰环境（5Grie）的设计，这是一种基于Python的环境，基于健身房的方法。环境可以使用公式的干涉模型运行不同的算法，以使用源和目标对路由数据包。可以在其中运行深层增强学习算法，这些学习算法使用稳定的生物线3以及基于启发式的算法（如随机或贪婪）。盈利是提供的算法。
5G is the next-generation cellular network technology, with the goal of meeting the critical demand for bandwidth required to accommodate a high density of users. It employs flexible architectures to accommodate the high density. 5G is enabled by mmWave communication, which operates at frequencies ranging from 30 to 300 GHz. This paper describes the design of the 5G Routing Interfered Environment (5GRIE), a python-based environment based on Gym's methods. The environment can run different algorithms to route packets with source and destination pairs using a formulated interference model. Deep Reinforcement Learning algorithms that use Stable-Baselines 3, as well as heuristic-based algorithms like random or greedy, can be run on it. Profitable is an algorithm that is provided.
