5G动态点消隐的无线电环境图和深度q -学习

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI:10.23919/SoftCOM55329.2022.9911517

Marcin Hoffmann, P. Kryszkiewicz

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引用次数: 1

摘要

动态点消隐(DPB)是一种协调多点(CoMP)技术，其中一些基站(BSs)可以暂时静音，例如，以提高蜂窝边缘用户的吞吐量。本文提出了利用深度q -学习来获得提高蜂窝边缘用户吞吐量的静音模式。深度Q-Learning代理是根据位置相关数据进行训练的。仿真研究表明，该方案可将蜂窝边缘用户吞吐量提高约20.6%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Radio Environment Map and Deep Q-Learning for 5G Dynamic Point Blanking

Dynamic Point Blanking (DPB) is one of the Coordinated MultiPoint (CoMP) techniques, where some Base Stations (BSs) can be temporarily muted, e.g., to improve the cell-edge users throughput. In this paper, it is proposed to obtain the muting pattern that improves cell-edge users throughput with the use of a Deep Q-Learning. The Deep Q-Learning agent is trained on location-dependent data. Simulation studies have shown that the proposed solution improves cell-edge user throughput by about 20.6%.

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2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)

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