论文标题
无线电环境图和5G动态点抛光的深度Q学习
Radio Environment Map and Deep Q-Learning for 5G Dynamic Point Blanking
论文作者
论文摘要
动态点隐蔽（DPB）是协调的多点（COMP）技术之一，其中某些基站（BSS）可以暂时静音，例如改善细胞边缘用户的吞吐量。在本文中，建议通过使用深Q学习来获得改善细胞边缘用户吞吐量的突变模式。深Q学习剂对位置依赖性数据进行了训练。仿真研究表明，提出的解决方案将细胞边缘用户吞吐量提高了约20.6％。
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%.
