arXiv subjects

Jarne Van Mulders

Publications and source records attributed to Jarne Van Mulders.

16 recordsLinked to original sources

arXiv2026

ARFT: A Synchronized Multimodal RF-Acoustic Dataset for Positioning in Distributed Environments

This paper documents the acoustic-radio fusion in Techtile (ARFT) dataset, a synchronized measurement campaign for distributed wireless sensing and positioning in the Techtile testbed. Ultrasonic and radio frequency (RF) signals are simultaneously transmitted and captured at multiple positions in a 2D spatial grid inside the Techtile testbed. Each acquisition cycle corresponds to one rover stop, one position sample, one acoustic recording and one RF snapshot. The RF modality is recorded as per-host pilot measurements and released as channel state information (CSI) tensors for 42 antennas mounted at the ceiling of the room. The acoustic chirp is recorded with 91 synchronized microphones and transmitted by a synchronized quasi omni-directional speaker. The campaign spans 5011 spatial position samples spanning a 5.57 m by 2.89 m area with complete RF and acoustic data. We detail how the measurements are recorded, quantify per-experiment coverage, describe the RF and acoustic data contents, and explain how the aligned modalities support RF-only, acoustic-only, and joint positioning workflows. Furthermore, a static acoustic positioning pipeline that performs anchor selection, pulse-compression ranging, and least squares (LS) localization is elaborated.

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arXiv2026

Testbed Evaluation of AI-based Precoding in Distributed MIMO Systems

Distributed MIMO (D-MIMO) has emerged as a key architecture for future sixth-generation (6G) networks, enabling cooperative transmission across spatially distributed access points (APs). However, most existing studies rely on idealized channel models and lack hardware validation, leaving a gap between algorithmic design and practical deployment. Meanwhile, recent advances in artificial intelligence (AI)-driven precoding have shown strong potential for learning nonlinear channel-to-precoder mappings, but their real-world deployment remains limited due to challenges in data collection and model generalization. This work presents a framework for implementing and validating an AI-based precoder on a D-MIMO testbed with hardware reciprocity calibration. A pre-trained graph neural network (GNN)-based model is fine-tuned using real-world channel state information (CSI) collected from the Techtile platform and evaluated under both interpolation and extrapolation scenarios before end-to-end validation. Experimental results demonstrate a 15.7% performance gain over the pre-trained model in the multi-user case after fine-tuning, while in the single-user scenario the model achieves near-maximum ratio transmission (MRT) performance with less than 0.7 bits/channel use degradation out of a total throughput of 5.19 bits/channel use on unseen positions. Further analysis confirms the data efficiency of real-world measurements, showing consistent gains with increasing training samples, and end-to-end validation verifies coherent power focusing comparable to MRT.

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arXiv2026

Experimental Evaluation of Geometry and Reciprocity-Based Beamforming with Large Arrays for RF Wireless Power Transfer

This paper experimentally investigates geometry-based multi-antenna RF wireless power transfer (WPT) using a large-scale distributed indoor transmit array measuring 8 m by 4 m. Geometry-based beamforming uses known transmitter and receiver positions to perform phase-only precoding, avoiding the need for explicit channel estimation or feedback. The experiments use a ceiling-mounted array of 41 phase-synchronized transmit antennas operating at 920 MHz. Geometry-based beamforming is compared with channel state information (CSI)-based beamforming. The spatial power delivery is evaluated through two-dimensional scans over an area of 1.25 m by 1.25 m. The harvested DC power is measured using an RF-to-DC energy profiler. Under line-of-sight (LoS) conditions, geometry-based beamforming achieves a power gain of 18.75 dB, which is within 0.82 dB of CSI-based beamforming. In obstructed LoS scenarios with reflections, the gain decreases to 16.7 dB, while CSI-based beamforming achieves 20.53 dB, resulting in a performance gap of 3.83 dB. These results quantify the trade-off between reduced system overhead and robustness to multipath propagation in geometry-driven WPT, and represent an initial step toward geometry-based wireless power transfer enabled by digital twins.

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arXiv2026

Experimental Study of Interference Suppression for Backscatter Communication in Distributed MIMO

Bistatic backscatter communication requires strong illumination of a backscatter device (BD), while a spatially separated reader detects the weak modulated reflection. In practice, the resulting direct link interference (DLI) at the reader can dominate the received backscattered signal and limit detection performance. This paper experimentally investigates transmit beamforming that jointly maximizes BD illumination and suppresses DLI at the reader in a distributed multiple-input multiple-output setup. We compare phase-only maximum ratio transmission (PO-MRT) with the proposed direct-link suppression (DLS) scheme, which enforces a spatial null at the reader under per-antenna power constraints. Measurements using a phase-coherent 42-element ceiling array at 920 MHz show that DLS reduces the DLI at the target reader and improves the signal-to-interference ratio by up to 31 dB compared to PO-MRT.

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arXiv2025

RF-Powered Batteryless Plant Movement Sensor for Precision Agriculture

Precision agriculture demands non-invasive, energy-efficient, and sustainable plant monitoring solutions. In this work, we present the design and implementation of a lightweight, batteryless plant movement sensor powered solely by RF energy. This sensor targets Controlled Environment Agriculture (CEA) and utilizes inertial measurements units (IMUs) to monitor leaf motion, which correlates with plant physiological responses to environmental stress. By eliminating the battery, we reduce the ecological footprint, weight, and maintenance requirements, transitioning from lifetime-based to operation-based energy storage. Our design minimizes circuit complexity while enabling flexible, adaptive readout scheduling based on energy availability and sensor data. We detail the energy requirements, RF power transfer considerations, integration constraints, and outline future directions, including multi-antenna power delivery and networked sensor synchronization.

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arXiv2025

Designing RF-Powered Battery-Less Electronic Shelf Labels With COTS Components

This paper presents a preliminary study exploring the feasibility of designing batteryless electronic shelf labels (ESLs) powered by radio frequency wireless power transfer using commercial off-the-shelf components. The proposed ESL design is validated through a dedicated testbed and involves a detailed analysis of design choices, including energy consumption, energy conversion, and storage solutions. A leaded aluminium electrolytic capacitor is selected as the primary energy storage element, balancing cost and performance while maintaining compactness. Experimental evaluations demonstrate that an ESL can update its display within 4 to 120 minutes, depending on input power and RF frequency, with harvester efficiencies reaching up to 30 %. Challenges such as low harvester efficiency, extended update times, and hardware constraints are identified, highlighting opportunities for future optimizations. This work provides valuable insights into system design considerations for RF-powered ESLs and establishes a foundation for further research in energy-neutral Internet of Things applications.

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arXiv2025

GNN-based Precoder Design and Fine-tuning for Cell-free Massive MIMO with Real-world CSI

Cell-free massive MIMO (CF-mMIMO) has emerged as a promising paradigm for delivering uniformly high-quality coverage in future wireless networks. To address the inherent challenges of precoding in such distributed systems, recent studies have explored the use of graph neural network (GNN)-based methods, using their powerful representation capabilities. However, these approaches have predominantly been trained and validated on synthetic datasets, leaving their generalizability to real-world propagation environments largely unverified. In this work, we initially pre-train the GNN using simulated channel state information (CSI) data, which incorporates standard propagation models and small-scale Rayleigh fading. Subsequently, we finetune the model on real-world CSI measurements collected from a physical testbed equipped with distributed access points (APs). To balance the retention of pre-trained features with adaptation to real-world conditions, we adopt a layer-freezing strategy during fine-tuning, wherein several GNN layers are frozen and only the later layers remain trainable. Numerical results demonstrate that the fine-tuned GNN significantly outperforms the pre-trained model, achieving an approximate 8.2 bits per channel use gain at 20 dB signal-to-noise ratio (SNR), corresponding to a 15.7 % improvement. These findings highlight the critical role of transfer learning and underscore the potential of GNN-based precoding techniques to effectively generalize from synthetic to real-world wireless environments.

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arXiv2024

Experimental Study on the Effect of Synchronization Accuracy for Near-Field RF Wireless Power Transfer in Multi-Antenna Systems

Wireless power transfer (WPT) technologies hold promise for enhancing device autonomy, particularly for energy-limited IoT systems. This paper presents experimental results on coherent and non-coherent transmit diversity approaches for WPT, tested in the near field using the Techtile testbed. We demonstrate that a fully synchronized beamfocusing system achieves a 14 dB gain over non-coherent transmission, consistent with the theoretical 14.9 dB gain for a 31-element array. Additionally, phase alignment errors below 20° result in less than 1 dB of gain loss, while errors exceeding 40° lead to losses over 3 dB. These findings suggest that phase coherency requirements for WPT can be relaxed, and that scaling the number of antennas is a promising strategy for improving power transfer efficiency.

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arXiv2024

Single versus Multi-Tone Wireless Power Transfer with Physically Large Array

Distributed beamforming is a key enabler to provide power wirelessly to a massive amount of energy-neutral devices (ENDs). However, without prior information and fully depleted ENDs, initially powering these devices efficiently is an open question. This work investigates and assesses the feasibility of harvesting sufficient energy to transmit a backscatter pilot signal from the END, which can be then used for coherent downlink transmission. We experimentally evaluated adaptive single-tone and multi-tone signals during initial charging. The results indicate that the response time for ENDs with unknown locations can extend to several tens of seconds. Notably, the adaptive single-tone excitation shows, among others, better performance at lower transmit power levels, providing a faster response. These findings underscore the potential of adaptive single-tone signals in optimizing power delivery to END in future networks.

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arXiv2024

How to Perform Distributed Precoding to Wirelessly Power Shelf Labels: Signal Processing and Measurements

Wireless power transfer (WPT) has garnered increasing attention due to its potential to eliminate device-side batteries. With the advent of (distributed) multiple-input multiple-output (MIMO), radio frequency (RF) WPT has become feasible over extended distances. This study focuses on optimizing the energy delivery to Energy Receivers (ERs) while minimizing system total transmit power. Rather than continuous power delivery, we optimize the precoding weights within specified time slots to meet the energy requirements of the ERs. Both unsynchronized (non-coherent) and synchronized (coherent) systems are evaluated. Our analysis indicates that augmenting the number of antennas and transitioning from an unsynchronized to asynchronized full phase-coherent system substantially enhances system performance. This optimization ensures precise energy delivery, reducing overshoots and overall energy consumption. Experimental validation was conducted using a testbed with84 antennas, validating the trends observed in our numerical simulations.

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arXiv2024

UAV-Based Solution for Extending the Lifetime of IoT Devices: Efficiency, Design and Sustainability

Internet of Things (IoT) technology is named as a key ingredient in the evolution towards digitization of many applications and services. A deployment based on battery-powered remote Internet of Things (IoT) devices enables easy installation and operation, yet the autonomy of these devices poses a crucial challenge. A too short lifespan is undesirable from a functional, economical, and ecological point of view. This paper presents a unmanned aerial vehicle (UAV)-based approach to recharge remote Internet of Things (IoT) nodes. An in-depth study of the charging efficiency and optimization of key parameters, and measurements-based verification, is reported on. An actual corresponding design and implementation of the full UAV-based charging system and its proof-of-concept validation are presented. Finally, the sustainability of the proposed solution is discussed. The results presented in this paper hence confirm that the proposed UAV-based approach and design are functionally successful and efficient charging can be achieved, provided the constraints and challenges coming with the approach are adequately dealt with. Moreover, it comes with an overall reduction in ecological footprint for IoT applications relying on battery-powered nodes in need of medium energy and/or considerable lifetime expectation (5 years or more).

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arXiv2024

Keeping Energy-Neutral Devices Operational: a Coherent Massive Beamforming Approach

Keeping the batteries on the shelf: this is the holy grail for low-cost Internet of Things (IoT) nodes. In this paper we study the potential of radio frequency (RF)-based wireless power transfer implementing coherent beamforming with many antennas to realize this ambitious target. We optimize the deployment of the antennas to charge electronic shelf labels (ESLs), considering actual regulatory constraints. The results confirm the feasibility to create power spots that are sufficient to keep the high density of battery-less devices operational.

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arXiv2022

IoT with a Soft Touch: A Modular Remote Sensing Platform for STE(A)M Applications

Besides wide attraction in the industry, IoT is being used to advance STEM and STEAM education across a range of education levels. This work presents a remote sensing platform, named IoT with a Soft Touch, developed to achieve two goals. First, it aims to lower the technicality, stimulating the students to do STE(A)M. Second, the technology is to be used in `softer' applications (e.g., environmental and health care), thereby aiming to attract a more diverse set of student profiles. Students can easily build a wireless sensing device, with a specific application in mind. The modular design of the platform and an intuitive graphical configurator tool allows them to tailor the device's functionality to their needs. The sensor's data is transmitted wirelessly with LoRaWAN. The data can be viewed and analyzed on a dashboard, or the raw data can be extracted for further processing, e.g., as part of the school's STE(A)M curriculum. This work elaborates on the low-power and modular design challenges, and how the platform is used in education.

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arXiv2022

Techtile -- Open 6G R&D Testbed for Communication, Positioning, Sensing, WPT and Federated Learning

New concepts for next-generation wireless systems are being developed. It is expected that these 6G and beyond systems will incorporate more than only communication, but also sensing, positioning, (deep) edge computing, and other services. The discussed measurement facility and approach, named Techtile, is an open, both in design and operation, and unique testbed to evaluate these newly envisioned systems. Techtile is a multi-functional and versatile testbed, providing fine-grained distributed resources for new communication, positioning and sensing technologies. The facility enables experimental research on hyper-connected interactive environments and validation of new algorithms and topologies. The backbone connects 140~resource units equipped with edge computing devices, software-defined radios, sensors, and LED sources. By doing so, different network topologies and local-versus-central computing can be assessed. The introduced diversity of i) the technologies (e.g., RF, acoustics and light), ii) the distributed resources and iii) the interconnectivity allows exploring more degrees and new types of diversity, which can be investigated in this testbed.

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arXiv2022

Aerial Energy Provisioning for Massive Energy-Constrained IoT by UAVs

Autonomy of devices is a major challenge in many Internet of Things (IoT) applications, in particular when the nodes are deployed remotely or difficult to assess places. In this paper we present an approach to provide energy to these devices by Unmanned Aerial Vehicles (UAVs). Therefore, the two major challenges, finding and charging the node are presented. We propose a model to give the energy constrained node an unlimited autonomy by taken the Wireless Power Transfer (WPT) link and battery capacity into account. Selecting the most suitable battery technology allows a reduction in battery capacity and waste. Moreover, an upgrade of existing IoT nodes is feasible with a limited impact on the design and form factor.

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arXiv2021

A Primer on Techtile: An R&D Testbed for Distributed Communication, Sensing and Positioning

The Techtile measurement infrastructure is a multi-functional, versatile testbed for new communication and sensing technologies relying on fine-grained distributed resources. The facility enables experimental research on hyper-connected interactive environments and validation of new wireless connectivity, sensing and positioning solutions. It consists of a data acquisition and processing equipment backbone and a fabric of dispersed edge computing devices, Software-Defined Radios, sensors, and LED sources. These bring intelligence close to the applications and can also collectively function as a massive, distributed resource. Furthermore, the infrastructure allows exploring more degrees and new types of diversity, i.e., scaling up the number of elements, introducing `3D directional diversity' by deploying the distributed elements with different orientations, and `interface diversity' by exploiting multiple technologies and hybrid signals (RF, acoustic, and visible light).

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