LIDAR Data for Deep Learning-Based mmWave Beam-Selection

Klautau Aldebaro; Gonzalez-Prelcic Nuria; Heath Robert W. Jr.

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LIDAR Data for Deep Learning-Based mmWave Beam-Selection

机译：用于基于深度学习的毫米波光束选择的LIDAR数据

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Millimeter wave (mmWave) communication systems can leverage information from sensors to reduce the overhead associated with link configuration. Light detection and ranging (LIDAR) is one sensor widely used in autonomous driving for high resolution mapping and positioning. This letter shows how LIDAR data can be used for line-of-sight detection and to reduce the overhead in mmWave beam-selection. In the proposed distributed architecture, the base station broadcasts its position. The connected vehicle leverages its LIDAR data to suggest a set of beams selected via a deep convolutional neural network. Co-simulation of communications and LIDAR in a vehicle-to-infrastructure (V2I) scenario confirm that LIDAR can help configuring mmWave V2I links.

机译：毫米波（mmWave）通信系统可以利用来自传感器的信息来减少与链路配置相关的开销。光检测和测距（LIDAR）是一种广泛用于自动驾驶的传感器，用于高分辨率地图和定位。这封信显示了如何将LIDAR数据用于视线检测并减少mmWave波束选择的开销。在提出的分布式体系结构中，基站广播其位置。所连接的车辆利用其LIDAR数据来建议通过深层卷积神经网络选择的一组光束。在车辆到基础设施（V2I）场景中，通信和LIDAR的协同仿真证实LIDAR可以帮助配置mmWave V2I链接。

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来源
《Wireless Communications Letters, IEEE》 |2019年第3期|909-912|共4页
作者
Klautau Aldebaro; Gonzalez-Prelcic Nuria; Heath Robert W. Jr.;
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作者单位

Univ Fed Para, Comp & Telecommun Dept, BR-66075 Belem, Para, Brazil;

Univ Texas Austin, Wireless Networking & Commun Grp, Austin, TX 78712 USA;

Univ Texas Austin, Wireless Networking & Commun Grp, Austin, TX 78712 USA;

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原文格式 PDF
正文语种 eng
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关键词
LIDAR; mmWave; machine learning; deep learning; convolutional networks;

机译：激光雷达;毫米波;机器学习;深度学习;卷积网络;

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2. A Deep Learning-Based Low Overhead Beam Selection in mmWave Communications [J] . Echigo Haruhi, Cao Yuwen, Bouazizi Mondher, IEEE Transactions on Vehicular Technology . 2021,第1期

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4. 5G MIMO Data for Machine Learning: Application to Beam-Selection Using Deep Learning [C] . Aldebaro Klautau, Pedro Batista, Nuria González-Prelcic, Information Theory and Applications Workshop . 2018

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LIDAR Data for Deep Learning-Based mmWave Beam-Selection

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