利用环境5G毫米波信号实现物联网自我定位

Junfeng Guan, Suraj Jog, Sohrab Madani, Ruochen Lu, S. Gong, Deepak Vasisht, Haitham Hassanieh
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引用次数: 0

摘要

5G毫米波网络中的小蜂窝尺寸、宽带宽和MIMO天线阵列为物联网本地化提供了巨大的机会。然而,低功耗和低成本的物联网设备无法利用这些优势。我们提出了mm-ISLA系统,该系统使物联网节点能够使用环境5G毫米波信号进行自我定位,而无需与基站进行任何协调。mm-ISLA利用MEMS Spike-Train滤波器访问宽带5G信号,并估计与基站MIMO天线阵列的偏离角度,以准确定位物联网节点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enabling IoT self-localization using ambient 5G mmWave signals
The small cell size, wide bandwidth, and MIMO antenna arrays in 5G mmWave networks provide great opportunities for IoT localization. However, low-power and low-cost IoT devices are incapable of leveraging these benefits. We present mm-ISLA: a system that enables IoT nodes to localize themselves using ambient 5G mmWave signals without any coordination with the base stations. mm-ISLA leverages MEMS Spike-Train filters to access the wideband 5G signals and estimates the Angle of Departure from the base station MIMO antenna arrays to accurately localize the IoT nodes.
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