Christoph Haugwitz | Searcharxiv

arXiv2026

Evaluating Acoustic Data Transmission Schemes for Ad-Hoc Communication Between Nearby Smart Devices

Acoustic data transmission offers a compelling alternative to Bluetooth and NFC by leveraging the ubiquitous speakers and microphones in smartphones and IoT devices. However, most research in this field relies on simulations or limited on-device testing, which makes the real-world reliability of proposed schemes difficult to assess. We systematically reviewed 31 acoustic communication studies for commodity devices and found that none provided accessible source code. After contacting authors and re-implementing three promising schemes, we assembled a testbed of eight representative acoustic communication systems. Using over 11000 smartphone transmissions in both realistic indoor environments and an anechoic chamber, we provide a systematic and repeatable methodology for evaluating the reliability and generalizability of these schemes under real-world conditions. Our results show that many existing schemes face challenges in practical usage, largely due to severe multipath propagation indoors and varying audio characteristics across device models. To support future research and foster more robust evaluations, we release our re-implementations alongside the first comprehensive dataset of real-world acoustic transmissions. Overall, our findings highlight the importance of rigorous on-device testing and underscore the need for robust design strategies to bridge the gap between simulation results and reliable IoT deployments.

cs.NI↗

arXiv2024

A tensor model for the calibration of air-coupled ultrasonic sensor arrays in 3D imaging

Arrays of ultrasonic sensors are capable of 3D imaging in air and an affordable supplement to other sensing modalities, such as radar, lidar, and camera, i.e. in heterogeneous sensing systems. However, manufacturing tolerances of air-coupled ultrasonic sensors may lead to amplitude and phase deviations. Together with artifacts from imperfect knowledge of the array geometry, there are numerous factors that can impair the imaging performance of an array. We propose a reference-based calibration method to overcome possible limitations. First, we introduce a novel tensor signal model to capture the characteristics of piezoelectric ultrasonic transducers (PUTs) and the underlying multidimensional nature of a multiple-input multiple-output (MIMO) sensor array. Second, we formulate and solve an optimization problem based on this model to obtain the calibrated parameters of the array. Third, we assess both our model and the commonly used analytic model using real data from a 3D imaging experiment. The experiment reveals that our array response model we learned with calibration data yields an imaging performance similar to that of the analytic array model, which requires perfect array geometry information.

eess.SP↗