arXiv subjects

Jeroen Famaey

Publications and source records attributed to Jeroen Famaey.

At least 37 records · Page 2Linked to original sources

arXiv2025

A2P: A Scalable OFDMA Polling Algorithm for Time-Sensitive Wi-Fi Networks

Over the years, advancements such as increased bandwidth, new modulation and coding schemes, frame aggregation, and the use of multiple antennas have been employed to enhance Wi-Fi performance. Nonetheless, as network density and the demand for low-latency applications increases, contention delays and retransmissions have become obstacles to efficient Wi-Fi deployment in modern scenarios. The introduction of Orthogonal Frequency-Division Multiple Access (OFDMA) in the IEEE 802.11 standard allows simultaneous transmissions to and from multiple users within the same transmission opportunity, thereby reducing the contention. However, the AP must efficiently manage the resource allocation, particularly in uplink scenarios where it lacks prior knowledge of users' buffer statuses, thus making polling a critical bottleneck in networks with a high number of users with sporadic traffic pattern. This paper addresses the polling problem and introduces the A2P algorithm, designed to enable scalable and efficient polling in high-density OFDMA-based time sensitive Wi-Fi networks. Simulation results show that A2P outperforms the alternative schemes by maintaining significantly lower delay and packet loss in dense time-sensitive teleconferencing scenario.

cs.NI↗

arXiv2025

Can Millimeter-Wave Support Interactive Extended Reality Under Rapid Rotational Motion?

Using Millimeter-Wave (mmWave) wireless communications is often named as the prime enabler for mobile interactive Extended Reality (XR), as it offers multi-gigabit data rates at millisecond-range latency. To achieve this, mmWave nodes must focus their energy towards each other, which is especially challenging in XR scenarios, where the transceiver on the user's XR device may rotate rapidly. To evaluate the feasibility of mmWave XR, we present the first throughput and latency evaluation of state-of-the-art mmWave hardware under rapid rotational motion, for different PHY and MAC-layer parameter configurations. We show that this parameter configuration has a significant impact on performance, and that specialized beamforming approaches for rapid rotational motion may be necessary to enable uninterrupted, high-quality mobile interactive XR experiences.

cs.NI↗

arXiv2025

Opportunities and Challenges for Virtual Reality Streaming over Millimeter-Wave: An Experimental Analysis

Achieving extremely high-quality and truly immersive interactive Virtual Reality (VR) is expected to require a wireless link to the cloud, providing multi-gigabit throughput and extremely low latency. A prime candidate for fulfilling these requirements is millimeter-wave (mmWave) communications, operating in the 30 to 300 GHz bands, rather than the traditional sub-6 GHz. Evaluations with first-generation mmWave Wi-Fi hardware, based on the IEEE 802.11ad standard, have so far largely remained limited to lower-layer metrics. In this work, we present the first experimental analysis of the capabilities of mmWave for streaming VR content, using a novel testbed capable of repeatably creating blockage through mobility. Using this testbed, we show that (a) motion may briefly interrupt transmission, (b) a broken line of sight may degrade throughput unpredictably, and (c) TCP-based streaming frameworks need careful tuning to behave well over mmWave.

cs.NI↗

arXiv2025

Generating Realistic Synthetic Head Rotation Data for Extended Reality using Deep Learning

Extended Reality is a revolutionary method of delivering multimedia content to users. A large contributor to its popularity is the sense of immersion and interactivity enabled by having real-world motion reflected in the virtual experience accurately and immediately. This user motion, mainly caused by head rotations, induces several technical challenges. For instance, which content is generated and transmitted depends heavily on where the user is looking. Seamless systems, taking user motion into account proactively, will therefore require accurate predictions of upcoming rotations. Training and evaluating such predictors requires vast amounts of orientational input data, which is expensive to gather, as it requires human test subjects. A more feasible approach is to gather a modest dataset through test subjects, and then extend it to a more sizeable set using synthetic data generation methods. In this work, we present a head rotation time series generator based on TimeGAN, an extension of the well-known Generative Adversarial Network, designed specifically for generating time series. This approach is able to extend a dataset of head rotations with new samples closely matching the distribution of the measured time series.

cs.CV↗

arXiv2025

Toward Interactive Multi-User Extended Reality Using Millimeter-Wave Networking

Extended Reality (XR) enables a plethora of novel interactive shared experiences. Ideally, users are allowed to roam around freely, while audiovisual content is delivered wirelessly to their Head-Mounted Displays (HMDs). Therefore, truly immersive experiences will require massive amounts of data, in the range of tens of gigabits per second, to be delivered reliably at extremely low latencies. We identify Millimeter-Wave (mmWave) communications, at frequencies between 24 and 300 GHz, as a key enabler for such experiences. In this article, we show how the mmWave state of the art does not yet achieve sufficient performance, and identify several key active research directions expected to eventually pave the way for extremely-high-quality mmWave-enabled interactive multi-user XR.

cs.NI↗

arXiv2025

Multi-Gigabit Interactive Extended Reality over Millimeter-Wave: An End-to-End System Approach

Achieving high-quality wireless interactive Extended Reality (XR) will require multi-gigabit throughput at extremely low latency. The Millimeter-Wave (mmWave) frequency bands, between 24 and 300GHz, can achieve such extreme performance. However, maintaining a consistently high Quality of Experience with highly mobile users is challenging, as mmWave communications are inherently directional. In this work, we present and evaluate an end-to-end approach to such a mmWave-based mobile XR system. We perform a highly realistic simulation of the system, incorporating accurate XR data traffic, detailed mmWave propagation models and actual user motion. We evaluate the impact of the beamforming strategy and frequency on the overall performance. In addition, we provide the first system-level evaluation of the CoVRage algorithm, a proactive and spatially aware user-side beamforming approach designed specifically for highly mobile XR environments.

cs.NI↗

arXiv2025

CoVRage: Millimeter-Wave Beamforming for Mobile Interactive Virtual Reality

Contemporary Virtual Reality (VR) setups often include an external source delivering content to a Head-Mounted Display (HMD). "Cutting the wire" in such setups and going truly wireless will require a wireless network capable of delivering enormous amounts of video data at an extremely low latency. The massive bandwidth of higher frequencies, such as the millimeter-wave (mmWave) band, can meet these requirements. Due to high attenuation and path loss in the mmWave frequencies, beamforming is essential. In wireless VR, where the antenna is integrated into the HMD, any head rotation also changes the antenna's orientation. As such, beamforming must adapt, in real-time, to the user's head rotations. An HMD's built-in sensors providing accurate orientation estimates may facilitate such rapid beamforming. In this work, we present coVRage, a receive-side beamforming solution tailored for VR HMDs. Using built-in orientation prediction present on modern HMDs, the algorithm estimates how the Angle of Arrival (AoA) at the HMD will change in the near future, and covers this AoA trajectory with a dynamically shaped oblong beam, synthesized using sub-arrays. We show that this solution can cover these trajectories with consistently high gain, even in light of temporally or spatially inaccurate orientational data.

cs.NI↗

arXiv2025

Placement, Orientation, and Resource Allocation Optimization for Cell-Free OIRS-aided OWC Network

The emergence of optical intelligent reflecting surface (OIRS) technologies marks a milestone in optical wireless communication (OWC) systems, enabling enhanced control over light propagation in indoor environments. This capability allows for the customization of channel conditions to achieve specific performance goals. This paper presents an enhancement in downlink cell-free OWC networks through the integration of OIRS. The key focus is on fine-tuning crucial parameters, including transmit power, receiver orientations, OIRS elements allocation, and strategic placement. In particular, a multi-objective optimization problem (MOOP) aimed at simultaneously improving the network's spectral efficiency (SE) and energy efficiency (EE) while adhering to the network's quality of service (QoS) constraints is formulated. The problem is solved by employing the $ε$-constraint method to convert the MOOP into a single-objective optimization problem and solving it through successive convex approximation. Simulation results show the significant impact of OIRS on SE and EE, confirming its effectiveness in improving OWC network performance.

eess.SP↗

arXiv2024

Toward Standardized Performance Evaluation of Flow-guided Nanoscale Localization

Nanoscale devices with Terahertz (THz) communication capabilities are envisioned to be deployed within human bloodstreams. Such devices will enable fine-grained sensing-based applications for detecting early indications (i.e., biomarkers) of various health conditions, as well as actuation-based ones such as targeted drug delivery. Associating the locations of such events with the events themselves would provide an additional utility for precision diagnostics and treatment. This vision yielded a new class of in-body localization coined under the term "flow-guided nanoscale localization". Such localization can be piggybacked on THz communication for detecting body regions in which biological events were observed based on the duration of one circulation of a nanodevice in the bloodstream. From a decades-long research on objective benchmarking of "traditional" indoor localization, as well as its eventual standardization (e.g., ISO/IEC 18305:2016), we know that in early stages the reported performance results were often incomplete (e.g., targeting a subset of relevant performance metrics), carrying out benchmarking experiments in different evaluation environments and scenarios, and utilizing inconsistent performance indicators. To avoid such a "lock-in" in flow-guided localization, in this paper we propose a workflow for standardized performance evaluation of such localization. The workflow is implemented in the form of an open-source simulation framework that is able to jointly account for the mobility of the nanodevices, in-body THz communication between with on-body anchors, and energy-related and other technological constraints (e.g., pulse-based modulation) at the nanodevice level. Accounting for these constraints, the framework is able to generate the raw data that can be streamlined into different flow-guided localization solutions for generating standardized performance benchmarks.

cs.NI↗

arXiv2024

CSI4Free: GAN-Augmented mmWave CSI for Improved Pose Classification

In recent years, Joint Communication and Sensing (JC&S), has demonstrated significant success, particularly in utilizing sub-6 GHz frequencies with commercial-off-the-shelf (COTS) Wi-Fi devices for applications such as localization, gesture recognition, and pose classification. Deep learning and the existence of large public datasets has been pivotal in achieving such results. However, at mmWave frequencies (30-300 GHz), which has shown potential for more accurate sensing performance, there is a noticeable lack of research in the domain of COTS Wi-Fi sensing. Challenges such as limited research hardware, the absence of large datasets, limited functionality in COTS hardware, and the complexities of data collection present obstacles to a comprehensive exploration of this field. In this work, we aim to address these challenges by developing a method that can generate synthetic mmWave channel state information (CSI) samples. In particular, we use a generative adversarial network (GAN) on an existing dataset, to generate 30,000 additional CSI samples. The augmented samples exhibit a remarkable degree of consistency with the original data, as indicated by the notably high GAN-train and GAN-test scores. Furthermore, we integrate the augmented samples in training a pose classification model. We observe that the augmented samples complement the real data and improve the generalization of the classification model.

cs.CV↗

arXiv2024

Low-latency Symbol-Synchronous Communication for Multi-hop Sensor Networks

Wireless sensor networks (WSNs) have received great interest due to their scalability, energy efficiency, and low-cost deployment. By utilizing multi-hop communication, WSNs can cover a wide area using low transmission power without the need for any communication infrastructure. Traditionally, WSNs rely on store-and-forward routing protocols and Time Division Multiple Access (TDMA)-based schedules that avoid interference between different wireless nodes. However, emerging challenging scenarios, such as the industrial Internet of Things (IoT) and robotic swarms, impose strict latency and reliability requirements, which traditional approaches cannot fulfill. In this paper, we propose a novel symbol-synchronous transmission design that provides reliable low-latency communication with a reasonable data rate on classical sub-6GHz RF frequency bands (e.g., the 2.4GHz ISM band). Instead of avoiding overlapping transmissions, the proposed scheme benefits from concurrent transmissions. Using simulation in MATLAB, we prove that the proposed design allows achieving a wire-like delay of 5ms for a 512-bit packet over multiple hops with only a 0.3% latency increase per extra hop and a low bit error rate (BER) of 0.04%. Compared to similar state-of-the-art approaches it can achieve a significantly higher data rate of 100kbps, which is expected to increase further with future improvements of the system.

cs.NI↗

arXiv2024

Dedicated Restricted Target Wake Time for Real-Time Applications in Wi-Fi 7

Real-time applications (RTA) tend to play a crucial role in people's everyday life. Such applications are among the key use cases for the next generations of wireless technologies. RTA applications are characterized by strict guaranteed delay requirements (in the order of a few milliseconds). One of the pillars of enabling RTA in next-generation Wi-Fi standards is Restricted Target Wake Time (R-TWT), which provides Wi-Fi stations exclusive channel access within negotiated service periods (SPs). If each RTA data flow uses dedicated SPs for data transmission, they are completely isolated from each other and do not experience any contention. To ensure the satisfaction of RTA QoS requirements while minimizing the channel airtime consumption, it is important to properly select the R-TWT parameters, namely the duration of SPs and the period between SPs. In this paper, we develop a mathematical model that estimates the delay probability distribution and packet loss probability for a given set of network, traffic and R-TWT parameters. Using this model, the access point can select the optimal R-TWT parameters for the given QoS requirements. The high accuracy of the model is proven by means of simulation.

cs.NI↗

arXiv2024

Zero-energy Devices for 6G: Technical Enablers at a Glance

Low-cost, resource-constrained, maintenance-free, and energy-harvesting (EH) Internet of Things (IoT) devices, referred to as zero-energy devices (ZEDs), are rapidly attracting attention from industry and academia due to their myriad of applications. To date, such devices remain primarily unsupported by modern IoT connectivity solutions due to their intrinsic fabrication, hardware, deployment, and operation limitations, while lacking clarity on their key technical enablers and prospects. Herein, we address this by discussing the main characteristics and enabling technologies of ZEDs within the next generation of mobile networks, specifically focusing on unconventional EH sources, multi-source EH, power management, energy storage solutions, manufacturing material and practices, backscattering, and low-complexity receivers. Moreover, we highlight the need for lightweight and energy-aware computing, communication, and scheduling protocols, while discussing potential approaches related to TinyML, duty cycling, and infrastructure enablers like radio frequency wireless power transfer and wake-up protocols. Challenging aspects and open research directions are identified and discussed in all the cases. Finally, we showcase an experimental ZED proof-of-concept related to ambient cellular backscattering.

eess.SP↗

arXiv2024

Battery-Less LoRaWAN Communications using Energy Harvesting: Modeling and Characterization

Billions of IoT devices are deployed worldwide and batteries are their main power source. However, these batteries are bulky, short-lived and full of hazardous chemicals that damage our environment. Relying on batteries is not a sustainable solution for the future IoT. As an alternative, battery-less devices run on long-lived capacitors charged using energy harvesters. The small energy storage capacity of capacitors results in an intermittent on-off behaviour. LoRaWAN is a popular Low Power Wide Area Network technology used in many IoT devices and can be used in these new scenarios. In this work, we present a Markov model to characterize the performance of battery-less LoRaWAN devices for uplink and downlink transmissions and we evaluate their performance in terms of the parameters that define the model (i.e., device configuration, application behaviour and environmental conditions). Results show that LoRaWAN battery-less communications are feasible if choosing the proper configuration (i.e., capacitor size, turn-on voltage threshold) for different application behaviour (i.e., transmission interval, UL/DL packet sizes) and environmental conditions (i.e., energy harvesting rate). Since downlink in the second reception window highly affects the performance, only small DL packet sizes should be considered for these devices. Besides, a 47 mF capacitor can support 1 Byte $SF7$ transmissions every 60 s at an energy harvesting rate of 1 mW. However, if no DL is expected, a 4.7 mF capacitor could support 1 Byte $SF7$ transmissions every 9~s.

cs.NI↗

arXiv2024

On the Feasibility of Battery-Less LoRaWAN Communications using Energy Harvesting

From the outset, batteries have been the main power source for the Internet of Things (IoT). However, replacing and disposing of billions of dead batteries per year is costly in terms of maintenance and ecologically irresponsible. Since batteries are one of the greatest threats to a sustainable IoT, battery-less devices are the solution to this problem. These devices run on long-lived capacitors charged using various forms of energy harvesting, which results in intermittent on-off device behaviour. In this work, we model this intermittent battery-less behaviour for LoRaWAN devices. This model allows us to characterize the performance with the aim to determine under which conditions a LoRaWAN device can work without batteries, and how its parameters should be configured. Results show that the reliability directly depends on device configurations (i.e., capacitor size, turn-on voltage threshold), application behaviour (i.e., transmission interval, packet size) and environmental conditions (i.e., energy harvesting rate).

cs.NI↗

arXiv2024

Optimal energy-aware task scheduling for batteryless IoT devices

Today's IoT devices rely on batteries, which offer stable energy storage but contain harmful chemicals. Having billions of IoT devices powered by batteries is not sustainable for the future. As an alternative, batteryless devices run on long-lived capacitors charged using energy harvesters. The small energy storage capacity of capacitors results in intermittent on-off behaviour. Traditional computing schedulers can not handle this intermittency, and in this paper we propose a first step towards an energy-aware task scheduler for constrained batteryless devices. We present a new energy-aware task scheduling algorithm that is able to optimally schedule application tasks to avoid power failures, and that will allow us to provide insights on the optimal look-ahead time for energy prediction. Our insights can be used as a basis for practical energy-aware scheduling and energy availability prediction algorithms. We formulate the scheduling problem as a Mixed Integer Linear Program. We evaluate its performance improvement when comparing it with state-of-the-art schedulers for batteryless IoT devices. Our results show that making the task scheduler energy aware avoids power failures and allows more tasks to successfully execute. Moreover, we conclude that a relatively short look-ahead energy prediction time of 8 future task executions is enough to achieve optimality.

cs.NI↗

arXiv2023

On the Energy Efficiency of THz-NOMA enhanced UAV Cooperative Network with SWIPT

This paper considers the energy efficiency (EE) maximization of a simultaneous wireless information and power transfer (SWIPT)-assisted unmanned aerial vehicles (UAV) cooperative network operating at TeraHertz (THz) frequencies. The source performs SWIPT enabling the UAV to receive both power and information while also transmitting the information to a designated destination node. Subsequently, the UAV utilizes the harvested energy to relay the data to the intended destination node effectively. Specifically, we maximize EE by optimizing the non-orthogonal multiple access (NOMA) power allocation coefficients, SWIPT power splitting (PS) ratio, and UAV trajectory. The main problem is broken down into a two-stage optimization problem and solved using an alternating optimization approach. In the first stage, optimization of the PS ratio and trajectory is performed by employing successive convex approximation using a lower bound on the exponential factor in the THz channel model. In the second phase, the NOMA power coefficients are optimized using a quadratic transform approach. Numerical results demonstrate the effectiveness of our proposed resource allocation algorithm compared to the baselines where there is no trajectory optimization or no NOMA power or PS optimization.

cs.IT↗

arXiv2023

Toward Energy Efficient Multiuser IRS-Assisted URLLC Systems: A Novel Rank Relaxation Method

This paper proposes an energy efficient resource allocation design algorithm for an intelligent reflecting surface (IRS)-assisted downlink ultra-reliable low-latency communication (URLLC) network. This setup features a multi-antenna base station (BS) transmitting data traffic to a group of URLLC users with short packet lengths. We maximize the total network's energy efficiency (EE) through the optimization of active beamformers at the BS and passive beamformers (a.k.a. phase shifts) at the IRS. The main non-convex problem is divided into two sub-problems. An alternating optimization (AO) approach is then used to solve the problem. Through the use of the successive convex approximation (SCA) with a novel iterative rank relaxation method, we construct a concave-convex objective function for each sub-problem. The first sub-problem is a fractional program that is solved using the Dinkelbach method and a penalty-based approach. The second sub-problem is then solved based on semi-definite programming (SDP) and the penalty-based approach. The iterative solution gradually approaches the rank-one for both the active beamforming and unit modulus IRS phase-shift sub-problems. Our results demonstrate the efficacy of the proposed solution compared to existing benchmarks.

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