This paper is included in the Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation. Enabling IoT Self-Localization Using Ambient 5G Signals
This paper is included in the Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation. Enabling IoT Self-Localization Using Ambient 5G Signals
复制标题
本文收录于第 19 届 USENIX 网络系统设计与实现研讨会论文集。
DOI：
--
复制
发表时间：
--
期刊：
影响因子：
--
通讯作者：
N. Hori
中科院分区：
文献类型：
--
作者：
S. Ito;N. Hori
-本文介绍了Isla，这是一个使低功率物联网节点能够使用环境5G信号进行自我定位的系统，而无需与基站进行任何协调。ISLA仅通过监听传输的5G分组来运行，并利用5G中使用的大带宽来计算信号的高分辨率fl时间。捕获大的5G带宽耗电很大。为了解决这个问题，ISLA利用MEMS声学谐振器的最新进展，设计了一种RFfi，它可以将有效定位带宽扩展到100兆赫兹，同时使用6.25兆赫兹接收器，将测距分辨率提高16倍。我们在三个大型室外试验台上实施和评估了ISLA，并显示出高定位精度，可以与拥有完整的100 MHz带宽相媲美。
– This paper presents ISLA , a system that enables low power IoT nodes to self-localize using ambient 5G signals without any coordination with the base stations. ISLA operates by simply overhearing transmitted 5G packets and leverages the large bandwidth used in 5G to compute high-resolution time of flight of the signals. Capturing large 5G bandwidth consumes a lot of power. To address this, ISLA leverages recent advances in MEMS acoustic resonators to design a RF filter that can stretch the effective localization bandwidth to 100 MHz while using 6.25 MHz receivers, improving ranging resolution by 16 × . We implement and evaluate ISLA in three large outdoors testbeds and show high localization accuracy that is comparable with having the full 100 MHz bandwidth.