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 the 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 an RF filter that can stretch the effective localization bandwidth to 100 MHz while using 6.25 MHz receivers, improving ranging resolution by 16x. We implement and evaluate ISLA in three large outdoor testbeds and show high localization accuracy that is comparable with having the full 100 MHz bandwidth.
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Paper:
Enabling IoT Self-Localization Using Ambient 5G Signals
Suraj Jog, Junfeng Guan, Sohrab Madani, Ruochen Lu, Songbin Gong, Deepak Vasisht, Haitham Hassanieh
@inproceedings {278318,
author = {Suraj Jog and Junfeng Guan and Sohrab Madani and Ruochen Lu and Songbin Gong and Deepak Vasisht and Haitham Hassanieh},
title = {Enabling {IoT} {Self-Localization} Using Ambient 5G Signals},
booktitle = {19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22)},
year = {2022},
isbn = {978-1-939133-27-4},
address = {Renton, WA},
pages = {1011–1026},
url = {https://www.usenix.org/conference/nsdi22/presentation/jog},
publisher = {USENIX Association},
month = apr,
}