Wireless sensing is an emerging technology with a wide range of applications, but most existing systems capture only the motion of a single point, such as in respiration monitoring. This limitation is critical for tasks requiring multi-point data, such as respiratory volume measurement, where different body points provide distinct information, and a single point cannot represent them all. In this paper, we propose LiSen, a smartphone-integrated LiDAR system for multi-point wireless sensing, and demonstrate its contact-free capability for measuring respiratory volume. LiSen uses smartphone LiDAR to track multiple chest and abdominal points, enabling the first ranging-based spirometer system that captures the full volume curve without new-user calibration. We leverage the unique feature of multi-point sensing to address challenges such as body interference, diverse breathing patterns, and pressure differences. Tests with 35 examinees show that LiSen accurately estimates both instantaneous forced expiratory and inspiratory volume, achieving mean absolute errors below 0.24 L and 0.30 L, respectively, and an 8.93% error for four common pulmonary function indices.

Low Earth Orbit (LEO) Synthetic Aperture Radar (SAR) satellites conventionally rely on dedicated communication links, which impose prohibitive hardware, spectrum, and power overhead as satellite constellations scale. This paper presents CommSAR, a novel system that reuses existing SAR imaging waveforms to enable bidirectional communication without modifying satellite hardware or compromising imaging performance. For the downlink, data are embedded by modulating the starting frequency offset of the imaging waveform, preserving the waveform structure and imaging quality. For the uplink, we propose a compact, low-cost programmable metasurface to replace conventional large, expensive antennas, significantly lowering the barrier for dense ground station deployment. To handle extreme satellite dynamics, we employ an opposite-slope waveform as a pilot to compensate for mobility-induced effects. We implement a ground station prototype of CommSAR and validate its performance using an in-orbit commercial SAR satellite and a UAV SAR platform. Experimental results show that CommSAR preserves imaging performance without degradation while achieving downlink and uplink data rates of up to 105 kbps and 112 kbps, respectively, significantly outperforming the state of the art and demonstrating utility-grade performance.

With global population growth, sustainable agriculture requires efficient soil moisture sensing for precise irrigation. While commercial soil moisture sensors are often limited by cost and durability, state-of-the-art RF-based sensing solutions require additional signal transmitter infrastructure, hindering widespread adoption. To fill this gap, we introduce GPSoil—a novel soil moisture sensing system that leverages pervasive Global Navigation Satellite System (GNSS) signals. On the hardware side, we employ two antennas along with a low-cost RF switch, enabling error mitigation for long propagation distances by comparing the signals captured from both antennas. On the software side, we leverage the inherent clock drift errors in commercial GNSS sensors and turn them into tools for fine-grained value extraction, enabling high-resolution sensing from otherwise coarse data. By integrating hardware and software innovations, we successfully achieve practical soil moisture sensing using GNSS signals. Built with off-the-shelf components, GPSoil achieves a soil moisture accuracy of 5.2% at a material cost of only $10.56, making it far more affordable than existing systems. GPSoil can sense moisture up to one meter underground, far surpassing other RF-based sensing systems and meeting the needs of most crops and irrigation systems. This work pioneers the use of GNSS signals in agriculture, offering a scalable, low-cost solution for advancing precision irrigation and promoting sustainable agriculture.

LoRa-based contact-free wireless sensing has attracted a lot of attention owing to its long sensing range, enabling wide-area sensing for the first time. While promising, existing LoRa sensing assumes there is no communication going on which is usually not true. We observe a severe degradation of sensing performance in real-world settings in the presence of communication. This issue hinders LoRa sensing from being adopted in real life and being integrated into the already established LoRa networking infrastructure. In this paper, we propose LSencom which takes the first step toward making LoRa-based wireless sensing work in the presence of communication. The key design is to employ the reversed chirp, i.e., downchirp, for sensing while keeping the original upchirp for communication. This design smartly leverages the orthogonality between downchirp and upchirp to mitigate the interference between communication and sensing. While the upchirp-downchirp design can remove most of the interference, we further adopt a novel chirp rotation method to deal with the remaining power leakage interference from upchirp to downchirp, enhancing the sensing performance. We implement LSencom on commodity LoRa nodes. Real-world experiments demonstrate that LSencom can reduce the communication-induced interference on sensing by 22.3 dB, and enable LoRa sensing even in the presence of multiple communication links.

While out-vehicle sensing has achieved great success with the development of vehicle radar and Lidar systems, invehicle sensing attracts a lot of attention recently. However, the popular camera-based solutions raise privacy concerns and pose requirement on lighting conditions. Researchers recently utilize wireless signals for sensing. However, besides requiring dedicated hardware, the rich multipath in a small cabin space causes severe interference, degrading the sensing reliability. In this paper, we propose a new sensing modality for in-vehicle sensing, leveraging the leaked EM signals from electric vehicles. The key observation is that the human body can capture the leaked signals, and body motions affect the signal variation patterns. Our solution involves designing conductive cloth tags on the seat to effectively collect body-captured signals and adopting a reference tag to deal with interference. Through extensive experiments conducted over 100 hours, covering a driving distance of 4000 kilometers on various real roads, our system, EVLeSen, can achieve over 90% accuracy in recognizing body motions utilizing just the leaked ambient signals.

Wireless sensing is gaining increasing attention from both academia and industry. Various wireless signals, such as Wi-Fi, UWB, and acoustic signals, have been leveraged for sensing. While promising in many aspects, two critical limitations still exist: a) limited sensing coverage; and b) the requirement for dedicated sensing signals, which may interfere with the original function of the wireless technology. To address these issues, we propose to utilize GPS signals for sensing, as GPS signals are already pervasive and emitted from satellites 24/7 at pre-allocated frequency bands, causing no interference. To make GPS sensing possible, we reconstruct signals with amplitude and phase information which is critical for sensing using the raw measurements reported by commercial GPS receiver module. We also develop sensing models to tailor the unique properties of GPS signals such as extremely long transmission distance. Finally, we introduce the concept of distributed sensing and design signal processing methods to fuse signals from multiple satellites to improve sensing performance. With all these designs, we prototype the first GPS wireless sensing system on commercial GPS receiver modules. Comprehensive experiments demonstrate that the proposed system can realize meaningful sensing applications such as human activity sensing, passive trajectory tracking, and respiration monitoring.

The past decade has witnessed a surge of interest in human respiration sensing with various wireless signals to achieve at-home smart health. While promising in many aspects, two critical limitations still exist: a) dedicated sensing signal transmitters are needed; b) existing sensing schemes affect the original function of the wireless technology such as communication. In this demo, we present the GPSense Respiration system, a new kind of contact-free respiration sensing system that breaks the above limitations. GPSense Respiration operates by receiving and analyzing the GNSS signals reflected by the human body without additional pre-deployed signal transmitters. Also, GPSense Respiration system will not affect wireless communications because GNSS signals operate at different frequencies than communication signals. This demo enables respiration monitoring for different users in real-time without any calibration.

Since the first successful wireless transmission across the Bristol Channel in 1897, wireless technologies have revolutionized the way we live, work and interact with the world. Besides the traditional communication function (e.g., Wi-Fi), wireless signals are further utilized for other functions such as localization, sensing and even charging. While promising in many aspects, one critical issue associated with these new functions is that they require dedicated signal transmissions, which interfere the original communication function. Take popular Wi-Fi sensing as the example. 200-1000 dedicated Wi-Fi packets per second need to be transmitted to enable Wi-Fi sensing which significantly decrease the throughput of ongoing Wi-Fi communication.

In recent years, wireless sensing has attracted lots of research attention with a large range of applications enabled. However, several critical issues still hinder wireless sensing from being adopted in daily use: (a) requiring dedicated devices and (or) dedicated signals; (b) limited sensing coverage; and (c) affecting the original function of the wireless technology (e.g., communication). In this work, we propose a new sensing modality, i.e., leveraging the pervasive powerline leakage for sensing. The key observation is that human body can capture such leaked signals, and the received signals vary with body gestures. We design a cheap ring antenna to collect the powerline leaked signals at human body and establish a body-empowered model to sense body motions. We prototype the proposed system with designs spanning both hardware and software. Comprehensive experiments show that the proposed sensing modality can realize a large range of applications in a different way from existing sensing methods. We showcase the powerful capability of this sensing modality using three typical sensing applications: body gesture recognition, sleep posture sensing, and fall detection.

Radio-Frequency (RF) backscatter has emerged as a low-power communication technique. Backscatter systems either rely on active signal generators (spectrum efficient, but dedicated infrastructure) or existing ambient wireless transmissions (existing infrastructure, but spectrum inefficient). In this paper, we aim to make RF backscatter spectrum efficient and at the same time work with existing infrastructure. We propose to leverage the deployment of LiFi networks built upon LED bulbs for pervasive RF backscatter. We experimentally demonstrate that LiFi, which passively leaks RF signals, can be exploited as a radio carrier generator for low-power RF backscatter. We further design LeakageScatter, the first backscatter system operating in the ISM band and exploiting LiFi-leaked RF signals, without the need to actively generate the carrier wave. We customize the design of the loop at the LiFi transmitter, as well as the coil antennas at the tag and RF backscatter receiver, to optimize the system performance. We propose to opportunistically enable the oscillator of the backscatter tag in the software that could reduce the energy consumption on backscattering by up to 75%. Experimental results show that LeakageScatter achieves a backscattering distance up to 10 m and 18 m in indoor and outdoor scenarios, respectively, without using a dedicated RF carrier generator.

Wireless sensing is capable of capturing rich information of human target without requiring sensors attached to the target. Although promising, two critical issues still exist, i.e., (i) limited sensing range, and (ii) severe interference in real-world settings. Recently, LoRa is employed to improve the sensing range. Although LoRa sensing is able to achieve a longer sensing range than WiFi and acoustic sensing, it is still limited to tens of meters. In this paper, we propose ChirpSen, which fully exploits the property of chirp signal to increase the sensing range. ChirpSen adopts a chirp concentration scheme to concentrate the power of all signal samples in a LoRa chirp at one timestamp, improving the signal power and accordingly boosting the sensing range. With a longer sensing range, the interference issue also becomes more severe. We propose a novel scheme to flexibly control the sensing coverage by tuning the LoRa chirp length in software. Real-world experiments show that ChirpSen is able to increase the detection range of a small size drone (12 cm × 10 cm × 8 cm) from 18 m to 160 m. ChirpSen is capable of monitoring a human's respiration rate at 138 m and tracking a human target's walking trajectory 210 m away.

Visible Light Communication (VLC) is widely considered a promising technology for the coming 6G networks. Recent studies show that a VLC transmitter not only emits visible light signals but also leaks RF signals during the transmission. In this work, we devote effort to harvesting the free leaked RF energy from VLC transmissions. We observe that the surrounding objects could help a coil antenna harvest significantly more RF energy. Based on this observation, we propose our system Bracelet+, which involves the human body in the harvesting system to increase the harvested power. After careful analysis of the influence of the human body on the harvested power, we prototype the coil antenna as a bracelet that achieves both high harvested power and convenience for wearing. The average power of the RF energy harvested by our design is 10× larger than that of the conventional coil antenna, without causing any interference to the communication of VLC systems. The harvested power can reach up to micro-watts in our tested scenarios. Such a micro-watt level of harvested energy has the potential to power up ultra-low-power sensors such as temperature sensors and glucose sensors.

Visible Light Communication (VLC) is considered a new paradigm for next-generation wireless communication. Recently, studies show that during the process of VLC transmission, besides the visible light signals, the transmitter also leaks out RF signals through a side channel. What is interesting is that the data transmitted in the VLC channel can be inferred from the leaked RF signals. Fundamentally, it means the leaked RF signals carry a copy of the same data in the VLC channel. In this work, we show for the first time that besides inferring the original VLC data, the leaked side channel can be smartly leveraged to carry new data, significantly increasing the data rate of current VLC systems. To realize this objective, we propose a system named RadioInLight, with designs spanning across hardware and software. Without any dedicated active RF transmission front-end which consumes power and hardware resources, RadioInLight is able to double the data rate of the VLC system by purely manipulating the free passively leaked RF signals without affecting the data rate of the original VLC transmissions.

Visible light communication (VLC) is gaining a significant amount of interest as a new paradigm to meet rapidly increasing demands on wireless capacity required by a digitalized world. VLC is considered as a secure wireless communication scheme because VLC signals can be easily constrained within physical boundaries. In this paper, for the first time, we show that VLC is not as secure as people thought: VLC can be sniffed through walls! The key principle behind this is that in VLC transmissions, a VLC transmitter not only emits visible light signals but also leaks out 'side channel RF signals'. The leaked RF signals can be sniffed by a receiver to decode the VLC transmissions even the receiver is blocked (e.g., by walls) from the VLC transmitter. In this work, we establish a theoretical model to quantify the amplitude of the leaked RF signal and verify the model with comprehensive experiments. We design and implement a VLC sniffing system including receiver coil design, signal processing and frame decoding, spanning across hardware and software. Field studies show that with a cheap receiver design, our system can simultaneously sniff transmissions from multiple VLC transmitters 6.4 meters away with a 14 cm concrete wall in between, where the distance exceeds the communication range of most state-of-the-art VLC systems. By simply twining a wired earphone on the arm, we can sniff the VLC transmission 1.9 meters away.

Visible Light Communication (VLC) is a promising technology for future wireless communications. By modulating the visible light---that has about 10,000x larger frequency band than that of radios---to transmit data, VLC has the potential to provide ultra-high-speed wireless connectivities. However, it also has limitations such as i) surrounding objects can easily block VLC links, and ii) intense ambient light can saturate the photodiodes of VLC receivers.