6G networks are expected to revolutionize connectivity, offering significant improvements in speed, capacity, and smart automation. However, existing network designs will struggle to handle the demands of 6G, which include much faster speeds, a huge increase in connected devices, lower energy consumption, extremely quick response times, and better mobile broadband. To solve this problem, incorporating the artificial intelligence (AI) technologies has been proposed. This idea led to the concept of Knowledge-Defined Networking (KDN). KDN promises many improvements, such as resource management, routing, scheduling, clustering, and mobility prediction. The main goal of this study is to optimize resource management using Reinforcement Learning.

翻译：6G网络有望彻底变革连接方式，在传输速率、网络容量和智能自动化方面实现显著提升。然而，现有网络架构将难以满足6G网络的严苛需求，这些需求包括：更快的传输速率、海量连接设备、更低的能耗、极低的时延以及更优的移动宽带性能。为解决这一挑战，学术界提出了融合人工智能（AI）技术的解决方案，由此催生了知识定义网络（KDN）的概念。KDN有望在资源管理、路由选择、调度策略、集群优化和移动性预测等多个维度实现性能跃升。本研究的主要目标是通过强化学习技术实现资源管理的最优化。