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Xujun Ma

Publications and source records attributed to Xujun Ma.

5 recordsLinked to original sources

WiRainbow: Single-Antenna Direction-Aware Wi-Fi Sensing via Dispersion Effect

Recently, Wi-Fi signals have emerged as a powerful tool for contactless sensing. During the sensing process, obtaining target direction information can provide valuable contextual insights for various applications. Existing direction estimation methods typically rely on antenna arrays, which are costly and complex to deploy in real-world scenarios. In this paper, we present WiRainbow, a novel approach that enables single-antenna-based direction awareness for Wi-Fi sensing by leveraging the dispersion effect of frequency-scanning antennas (FSAs), which can naturally steer Wi-Fi subcarriers toward distinct angles during signal transmission. To address key challenges in antenna design and signal processing, we propose a coupled-resonator-based antenna architecture that significantly expands the narrow Field-of-View inherent in conventional FSAs, improving sensing coverage. Additionally, we develop a sensing signal-to-noise-ratio-based signal processing framework that reliably estimates target direction in multipath-rich environments. We prototype WiRainbow and evaluate its performance through benchmark experiments and real-world case studies, demonstrating its ability to achieve accurate, robust, and cost-effective direction awareness for diverse Wi-Fi sensing applications.

eess.SP

RF-Behavior: A Multimodal Radio-Frequency Dataset for Human Behavior and Emotion Analysis

Recent research has demonstrated the complementary nature of camera-based and inertial data for modeling human gestures, activities, and sentiment. Yet, despite its growing importance for environmental sensing as well as the advance of joint communication and sensing for prospective WiFi and 6G standards, a dataset that integrates these modalities with radio frequency data (radar and RFID) remains rare. We introduce RF-Behavior, a multimodal radio frequency dataset for comprehensive human behavior and emotion analysis. We collected data from 44 participants performing 21 gestures, 10 activities, and 6 sentiment expressions. Data were captured using synchronized sensors, including 13 radars (8 ground-mounted and 5 ceiling-mounted), 6 to 8 RFID tags (attached to each arm) and LoRa. Inertial measurement units (IMUs) and 24 infrared cameras are used to provide precise motion ground truth. RF-Behavior provides a unified multimodal dataset spanning the full spectrum of human behavior -- from brief gestures to activities and emotional states -- enabling research on multi-task learning across motion and emotion recognition. Benchmark results demonstrate that the strategic sensor placement is complementary across modalities, with distinct performance characteristics across different behavioral categories.

cs.DB

Characterizing random 1D media with an embedded reflector via scattered waves

We show in random matrix theory, microwave measurements, and computer simulations that the mean free path of a random medium and the strength and position of an embedded reflector can be determined from radiation scattered by the system. The mean free path and strength of the reflector are determined from the statistics of transmission. The statistics of transmission are independent of the position of the reflector. The reflector's position can be found, however, from the average dwell time for waves incident from one side of the sample.

cond-mat.dis-nn

Single-Parameter Scaling and Maximum Entropy inside Disordered One-Dimensional Systems: Theory and Experiment

The single-parameter scaling hypothesis relating the average and variance of the logarithm of the conductance is a pillar of the theory of electronic transport. We use a maximum-entropy ansatz to explore the logarithm of the energy density, $\ln {\cal W}(x)$, at a depth $x$ into a random one-dimensional system. Single-parameter scaling would be the special case in which $x=L$ (the system length). We find the result, confirmed in microwave measurements and computer simulations, that the average of $\ln {\cal W}(x)$ is independent of $L$ and equal to $-x/\ell$, with $\ell$ the mean free path. At the beginning of the sample, ${\rm var}[\ln {\cal W}(x)]$ rises linearly with $x$ and is also independent of $L$, with a sublinear increase near the sample output. At $x=L$ we find a correction to the value of ${\rm var}[\ln T]$ predicted by single-parameter scaling.

cond-mat.dis-nn