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In this paper, we introduce a low-power wide-area cellular localization system, called LiTEfoot. The core architecture of the radio carefully applies non-linear transform of the entire cellular spectrum to obtain a systematic superimposition of the synchronization signals at the baseband. The system develops methods to simultaneously identify all the base stations that are active at any cellular band from the transformed signal. The radio front end uses a simple envelop detector to realize the non-linear transformation. We build on this low-power radio to implement a self-localization system leveraging ambient 4G-LTE signals. We show that the core system can also be extended to other cellular technologies like 5G-NR and NB-IoT. The prototype achieves a median localization error of 22 meters in urban areas and 50 meters in rural areas. It can sense a 3GHz wideband LTE spectrum in 10ms using non-linear intermodulation while consuming 0.9 mJ of energy for a PCB-based implementation and 40 𝜇J for CMOS simulation. In other words, LiTEfoot tags can last for 11 years on a coin cell while continuously estimating location every 5 seconds. We believe that LiTEfoot will have widespread implications in city-scale asset tracking and other location-based services. The radio architecture can be useful beyond low-power self-localization and can find application in synchronization and communication on battery-less platforms.
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This content will become publicly available on December 4, 2025
Demo: Scalable and Sustainable Asset Tracking with NextG Cellular Signals
This demonstration presents LiTEfoot, an ultra-low power localization system leveraging ambient cellular signals. To address the limitations of traditional GPS-based tracking systems in terms of power consumption and latency, LiTEfoot employs a non-linear transformation of the cellular spectrum to achieve efficient self-localization. Our design uses a simple envelope detector to realize spectrum folding, enabling the identification of multiple active base stations.
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- Award ID(s):
- 2238433
- PAR ID:
- 10589896
- Publisher / Repository:
- ACM MobiCom
- Date Published:
- ISBN:
- 9798400704895
- Page Range / eLocation ID:
- 1719 to 1721
- Format(s):
- Medium: X
- Location:
- Washington D.C. DC USA
- Sponsoring Org:
- National Science Foundation
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