Towards Deep Learning Augmented Robust D-Band Millimeter-Wave Picocell Deployment

被引:0
|
作者
Regmi H. [1 ]
Sur S. [1 ]
机构
[1] Computer Science and Engineering, University of South Carolina, Columbia
来源
Performance Evaluation Review | 2023年 / 50卷 / 04期
关键词
5G mobile communication systems - Deep learning;
D O I
10.1145/3595244.3595266
中图分类号
学科分类号
摘要
D-band millimeter-wave, a key wireless technology for beyond 5G networks, promises extremely high data rate, ultra-low latency, and enables new Internet of Things applications. However, massive signal attenuation, complex response to building structures, and frequent non-availability of the Line-Of-Sight path make D-band picocell deployment challenging. To address this challenge, we propose a deep learning-based tool, that allows a network deployer to quickly scan the environment from a few random locations and predict Signal Reflection Profiles everywhere, which is essential to determine the optimal locations for picocell deployment. © 2023 Copyright is held by the owner/author(s).
引用
收藏
页码:62 / 64
页数:2
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