This paper presents LiTEfoot, an ultra-low power, wide-area localization system leveraging ambient cellular signals to address the limitations of traditional self-localization systems in terms of power consumption and latency. LiTEfoot uses a non-linear transformation of the cellular synchronization signal to efficiently achieve self-localization by systematically superimposing signals at the baseband. A simple envelope detector is used to realize this non-linear transformation, enabling the identification of multiple active base stations across any cellular band. The system is designed to operate with low power, consuming only 40 ๐Joules of energy per localization update, achieving a median localization error of 22 meters in urban areas.
more »
« less
This content will become publicly available on November 4, 2025
LiTEfoot: Ultra-low-power Localization using Ambient Cellular Signals
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 ๐J 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.
more »
« less
- Award ID(s):
- 2238433
- PAR ID:
- 10589162
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400706974
- Page Range / eLocation ID:
- 535 to 548
- Format(s):
- Medium: X
- Location:
- Hangzhou China
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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.more » « less
-
Mission-critical wireless networks are being upgraded to 4G long-term evolution (LTE). As opposed to capacity, these networks require very high reliability and security as well as easy deployment and operation in the field. Wireless communication systems have been vulnerable to jamming, spoofing and other radio frequency attacks since the early days of analog systems. Although wireless systems have evolved, important security and reliability concerns still exist. This paper presents our methodology and results for testing 4G LTE operating in harsh signaling environments. We use software-defined radio technology and open-source software to develop a fully configurable protocol-aware interference waveform. We define several test cases that target the entire LTE signal or part of it to evaluate the performance of a mission-critical production LTE system. Our experimental results show that synchronization signal interference in LTE causes significant throughput degradation at low interference power. By dynamically evaluating the performance measurement counters, the k-nearest neighbor classification method can detect the specific RF signaling attack to aid in effective mitigation.more » « less
-
Current cellular systems use pilot-aided statistical channel state information (S-CSI) estimation and limited feedback schemes to aid in link adaptation and scheduling decisions. However, in the presence of pulsed radar signals, pilot-aided S-CSI is inaccurate since interference statistics on pilot and nonpilot resources can be different. Moreover, the channel will be bimodal as a result of the periodic interference. In this paper, we propose a max-min heuristic to estimate the post-equalizer SINR in the case of non-pilot pulsed radar interference, and characterize its distribution as a function of noise variance and interference power. We observe that the proposed heuristic incurs low computational complexity, and is robust beyond a certain SINR threshold for different modulation schemes, especially for QPSK. This enables us to develop a comprehensive semi-blind framework to estimate the wideband SINR metric that is commonly used for S-CSI quantization in 3GPP Long-Term Evolution (LTE) and New Radio (NR) networks. Finally, we propose dual CSI feedback for practical radar-cellular spectrum sharing, to enable accurate CSI acquisition in the bimodal channel. We demonstrate significant improvements in throughput, block error rate and retransmission-induced latency for LTE-Advanced Pro when compared to conventional pilot-aided S-CSI estimation and limited feedback schemes.more » « less
-
Interferometry is a powerful tool for estimating the incident angle of electromagnetic (EM) waves by calculating the correlation of received signals at different antennas. Motivated by very-long-baseline interfereometry (VLBI) in radio astronomy, an interferometry based sensing scheme is proposed as integrated sensing and communications (ISAC). It reuses the communication signal from base stations (BSs), similarly to passive radars, which improves the sensing precision and spectrum efficiency. Different from the almost-perfect synchronization in VLBI realized by atomic clocks, the synchronization in BSs of cellular communication networks (usually based on GPS signals) could have significant errors. Therefore, algorithms for compensating for synchronization errors in both time and frequency are proposed. Numerical simulations demonstrate that the proposed algorithms can substantially alleviate the synchronization errors.more » « less
An official website of the United States government
