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

Marcin Hoffmann, P. Kryszkiewicz
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引用次数: 1

Abstract

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%.
5G动态点消隐的无线电环境图和深度q -学习
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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