一种基于跨层算法和深度学习的MAC调度方法

Zhiming Liu, Shuangfeng Han
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引用次数: 0

摘要

MAC调度对无线通信系统的性能和用户间的公平性有着重要的影响。近年来,针对日益复杂的场景,提出了大量的算法。本文设计了一种基于跨层数学算法和多层感知机(MLP)深度学习的智能6G无线网络MAC调度算法。我们将跨层数学算法部分定义为HI (Human Intelligence)引擎,将深度学习部分定义为AI (Artificial Intelligence)引擎。并分别设计了两个引擎的协调机制、所需数据、各自的工作流程和具体算法。为了证明我们提出的方法在性能方面的优势,在各种流量场景下对用例进行了仿真分析,并与传统解决方案进行了性能比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel MAC Scheduling Based on Cross-layer Algorithm and Deep Learning
MAC scheduling plays an important role in affecting the performance of wireless communication system and the fairness among users. A significant number of algorithms have been put forward for increasingly complex scenarios in recent years. In this paper, we designed a novel MAC scheduling algorithm for intelligent 6G wireless network based on cross-layer mathematical algorithm and deep learning with Multi-Layer Perceptron (MLP). We define the cross-layer mathematical algorithm part as HI (Human Intelligence) engine and the deep learning part as AI (Artificial Intelligence) engine. Also, we respectively designed the coordination mechanism, required data, respective workflows and specific algorithms for the two engines. To demonstrate the superior performance gains of our proposed methodology, the use case was analyzed with simulation in various traffic scenarios and made performance comparison with traditional solution.
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