论文标题
演示：基于增强学习的柔性双工系统，用于B5G，低于6 GHz
Demo: A Reinforcement Learning-based Flexible Duplex System for B5G with Sub-6 GHz
论文作者
论文摘要
在本文中，我们提出了一个基于增强学习的灵活双链系统，用于B5G，低于6 GHz。该系统结合了完整的无线电和动态光谱访问，以最大程度地提高光谱效率。我们通过实现基于FPGA的实时测试台来验证该方法的可行性。此外，我们将所提出的算法与通过系统级评估得出的结果进行了比较。
In this paper, we propose a reinforcement learning-based flexible duplex system for B5G with Sub-6 GHz. This system combines full-duplex radios and dynamic spectrum access to maximize the spectral efficiency. We verify this method's feasibility by implementing an FPGA-based real-time testbed. In addition, we compare the proposed algorithm with the result derived from the numerical analysis through system-level evaluations.
