Research Jeroen Famaey

Abstract

Extended Reality (XR) continues to gain more traction, with an ever-expanding array of both consumer and business applications. When designing such applications, one can choose between tethered, wirelessly connected or fully standalone Head-Mounted Displays (HMDs). These result in constrained user freedom, compression artifacts, or limited visual fidelity respectively. In this project, we aim to enable a best-of-all-worlds solution, where wireless Millimeter-Wave (mmWave) links are leveraged for consistent extremely high-quality and low-latency data delivery. Current mmWave solutions behave poorly under motion, with link degradation and even interruptions being commonplace. In this project, we will investigate avenues for enabling interactive mobile multi-user XR through mmWave. Consistent room-wide coverage will require multiple Access Points (APs), so we will investigate their optimal placement along with dynamic, proactive assignment of HMDs to APs, including practical zero-latency handovers. Furthermore, we will design real-world proactive receive-side beamforming for HMDs, as to maintain consistently high-quality links during rapid rotational motion. Data rate and reliability will be improved through both current-day solutions such as MU-MIMO, and future solutions such as Reconfigurable Intelligent Surfaces and Distributed Antenna Arrays. All this will be evaluated through a novel testbed along with simulation. Testbed design and simulation tools will be open source.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Struye Jakob

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Greenhouse gas emission is causing the Earth's climate to deteriorate at an alarming rate. Greenhouse gas traps the heat in the atmosphere, causing global warming, extreme weather conditions and environmental changes such as rising sea levels. Agriculture is a significant contributor to greenhouse gas emission, with a contribution of around one-third of total emissions. Considering this, many recent sustainability regulations such as the Flemish Nitrogen Decree and EU Green Deal try to tackle the emission from agriculture. A major portion of agricultural emissions arise from the unscientific use of fertilizers which release greenhouse gases into the atmosphere. As a result, farmers are urged to follow sustainable agriculture practices and reduce emission. However, implementing sustainable farming requires allowing farmers to determine the optimum measurement of both soil nutrient content and emission in real time. But there is a lack of cost-effective devices that can measure both soil nitrogen content and emission in real time and can assist farmers in deciding on optimum fertilizer application. Such a device should be of low cost and with limited maintenance requirements, putting no extra financial pressure on farmers. Moreover, they should be deploy-and-forget architecture so that no maintenance and management is required from the farmers. This POC proposal Sustainable and Energy Neutral Soil Sensing (SENSS) aims to fill this gap by innovating novel soil sensing devices that work seamlessly in agricultural environments. The device will incorporate novel energy harvesting and energy-aware techniques along with low-power wireless connectivity and onboard intelligence to achieve long-term operation and in-device data processing and inference. The project will further leverage the ecology and environmental knowledge of the Global Change Ecology Center of Excellence and the low-power electronic and communication knowledge of IDLab.

Researcher(s)

• Promoter: Singh Ritesh Kumar
• Co-promoter: Famaey Jeroen
• Co-promoter: Janssens Ivan
• Co-promoter: Struyf Eric
• Co-promoter: Weyn Maarten

Research team(s)

• Internet Data Lab (IDLab)

Project website

Project type(s)

• Research Project

Abstract

The 6th generation of mobile network technology (6G) will be at the centre of a human-centric hyper-connected world. To enable this, 6G will not only have to offer unprecedented throughput, latency, and reliability but also accurate sensing of people and environments. This will enable novel spatially aware applications, such as extended reality, human-robot collaboration, and autonomous transportation. Achieving this vision requires the design of new perceptive radios, that can perform integrated sensing and communications (ISAC). Moreover, the required 6G performance and sensing accuracy can only be achieved by employing mmWave frequencies (i.e., 24-300 GHz). However, commercial-off-the-shelf mmWave devices do not offer the needed flexibility. As such, to go beyond simulation, and enable research into and prototyping of 6G mmWave perceptive radio systems, more flexible hardware, based on software-defined radios and programmable beamformers, is required. The goal of this project is to develop an indoor perceptive radio lab that offers such equipment, to enable the design of novel 6G ISAC solutions for future spatially aware cyber-physical applications. The lab will be equipped with a motion-capture system to collect ground truth data, which can be used to validate sensing accuracy and as input data for training AI algorithms. XR devices will be integrated to enable human-centric experimentation with realistic 6G applications. 1450 / 1500

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Berkvens Rafael
• Co-promoter: Halili Rreze

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The Flanders AI Research Program is a strategic basic research program with a consortium of eleven partners: the five Flemish universities (KU Leuven, University of Ghent, University of Antwerp, University of Hasselt, Vrije Universiteit Brussel) and six research centers (imec, Flanders Make, VIB, VITO, Sirris and ILVO). The program brings together 300+ researchers on new AI methods that can be used in innovative applications in health, industry, planet&energy and society. This way, the program contributes to a successful adoption of AI in Flanders. The ambition is for Flanders to occupy a strong international position in the field of strategic basic research in AI, and this within a strong and sustainable Flemish ecosystem. Five focus research themes have been selected: responsible AI, human-centered AI, sustainable AI (energy-efficient and high-performance), productive and data-efficient AI (systems that require little data, which perform by combining data with domain knowledge and experience of experts) and resilient and high-performant AI (robust against changes in the environment). The description of the work packages and their research tasks defines the aspects within these themes that will be investigated in the program. The AI solutions are demonstrated in real-life use cases. These results not only demonstrate the effectiveness, but also inspire companies for adoption and researchers for further research. The Flanders AI Research Program is part of the Flanders AI Policy Plan. More info: www.flandersairesearch.be

Researcher(s)

• Promoter: Mannens Erik
• Promoter: Oramas Mogrovejo José Antonio
• Co-promoter: Calders Toon
• Co-promoter: Daelemans Walter
• Co-promoter: Famaey Jeroen
• Co-promoter: Goethals Bart
• Co-promoter: Laukens Kris
• Co-promoter: Martens David
• Co-promoter: Mets Kevin
• Co-promoter: Sijbers Jan
• Co-promoter: Van Leekwijck Werner
• Co-promoter: Verdonck Tim

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The overarching objective of 6G-TWIN is to provide the foundation for the design, implementation and validation of an AI-native reference architecture for 6G systems that incorporates Network Digital Twins (NDT) as a core mechanism for the end-to-end, realtime optimisation, management and control of highly dynamic and complex network scenarios. To achieve this objective, 6G-TWIN will deliver methods, modelling and simulation solutions for the definition, creation and management of multi-layered virtual representations of future 6G systems, where heterogeneous domains (i.e., edge, fog and cloud) and communication technologies (e.g., cellular, optical and Non-Terrestrial Networks (NTN)) coexist. The project solutions will be demonstrated in two complementary use cases addressing mobility and energy-efficiency challenges, aligned with the expected use cases of 6G and the Key Performance Indicators (KPI) defined in previously funded projects (including SNS JU STREAM-C/D-2022). Finally, the participation of Small and Medium-sized Enterprises (SMEs) will ensure that the 6G-TWIN consortium pays particular attention to the replication, reengineering and exploitation of the project outcomes, regularly aligning the requirements of standardisation bodies with predicted market needs.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Camelo Botero Miguel

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The idea of Joint communication and sensing (JCS) capabilities is a revolutionary and innovative solution. A single system has the potential to offer significant advances in various fields, such as smart transportation, smart cities, smart homes, healthcare, security, and environmental monitoring. iSEE-6G extends beyond JCS and propose a Joint Communication, Computation, Sensing, and Power transfer (JCCSP) unified radio platform, which includes all support elements of the proposed solutions in future 6G networks. By integrating, exploiting, and supporting 6G key enabling technologies, iSEE-6G offers a) JCCSP-oriented novel intelligent reconfigurable surfaces (RIS) and agile beamforming array solutions; b) JCCSP-optimized physical layer design including waveform design, frame structure design, channel modeling, precoding/beamforming with respect to open radio access network (O-RAN) architectural paradigm; c) JCCSP-enabled cross-layer schemes design under new capabilities in terms of service-oriented network architecture; and d) JCCSPimplemented system-level solutions for providing new functionalities towards a cell-free 6G network. The iSEE-6G Proof-of-Concept (PoC) focuses in JCCSP use cases in aerial corridors, where UAVs with various roles providing different services coexist and coordinate with each other. In IMEC's testbed static distributed RUs, and vehicular UEs are additionally included for an emergency response incident. The UAVs monitor the area, estimate and report accurate positioning and provide situational awareness through integrated sensing. In ORO's testbed 5G waveforms based JCCSP exploit the KPI collection capabilities of it. The operation of the testbed will be extended at an outdoor venue, where UAVs and IoT devices will be deployed to test the Wireless Power Transfer (WPT) capabilities. Edge computational power is used for Public Protection and Desaster Relief (PPDR) monitoring and JCCSP-as-a-Service implementation.

Researcher(s)

• Promoter: Marquez-Barja Johann
• Co-promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Edge computing has emerged as a novel computing paradigm for the Internet of Things. Compared with the well-known cloud computing, edge computing migrates data computation or storage to the network ''edge,'' near the end users. This approach offers several advantages; it (1) reduces end-to-end latency, (2) reduces congestion and bandwidth consumption in the core network, (3) improves local load balancing capabilities and scalability, and (4) improves privacy and security. When pushing this model to the far edge, sensors and other computing devices have severely constrained capabilities (i.e., computational power, storage, and energy) compared to traditional edge or cloud servers. This significantly complicates the deployment and execution of machine learning (ML) algorithms at the edge, requiring so-called TinyML solutions, that operate in the milliwatt power range and below. To date, TinyML has focused on enabling basic ML on individual low-power sensors and other far edge devices. However, this does not allow the implementation of complex collaborative far edge applications, where many edge devices need to perform a set of coordinated sub-tasks to achieve a global objective. This project aims to address this gap, allowing resource-constrained sensors and far edge devices to collaboratively learn and make decisions. We will study scalable wireless data collection and aggregation techniques, making use of over-the-air computing. Moreover, we will design collaborative resource-aware scheduling and distributed intelligence methods that support adapting TinyML algorithm execution based on limited and variable available resources and energy.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Extended Reality (XR) has become the killer application for future wireless networks. XR is expected to be a major source of traffic for 6G. Use cases include education, health care, and gaming. XR requires accurate and real-time pose information (gesture recognition) to enable seamless experience. Recently, researchers have investigated the use of sub-6 GHz Wi-Fi signals for pose estimation and the results are very promising. Radio waves at these frequencies offer limited resolution due to low bandwidth. On the other hand, mmWave frequencies (>30 GHz) not only offer high data-rates but also high spatial resolution. The improved spatial resolution can benefit pose estimation in XR applications where accurate motion tracking is important for immersive and realistic experience. In this project, my aim is to leverage mmWave signals for pose estimation. This idea of using communications signals for sensing is known as Integrated Sensing and Communication (ISAC). To do this, I aim to collect an extensive and realistic dataset of gestures across several people and environments. I will then develop novel signal processing and deep learning-based algorithms for environment independent and multi-user sensing. Moreover, I will investigate a low power solution for pose estimation on the edge devices. Finally, I will develop a real-time prototype, which projects real-world movements onto the virtual world avatar of the user.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Berkvens Rafael
• Fellow: Bhat Nabeel Nisar

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Swarm robotics enables large groups of robots to collaborate on complex tasks. An important barrier that prevents real-world applicability is that robots are generally battery-powered, resulting in an autonomy of a few hours at best. Existing solutions to this problem, such as autonomous charging stations, powered surfaces, and wireless power transfer, rely on the presence of a power grid. This makes them unsuitable and impractical in many situations, where robots are deployed in an ad-hoc manner, or in hard-to-reach locations. In AmbientSwarms, we propose an alternative solutions, where robots are powered using ambient energy harvesting to achieve multi-year autonomy. The major downside of ambient energy, is its variability and unpredictability. As a result, ambiently-powered robots will inevitable suffer from power failures, and intermittently turn on and off. This significantly complicates computing and communication among collaborative robots. In the AmbientSwarms project, we will develop novel methods for intermittently powered swarm robots to communicate with each other and collaboratively perform tasks. Moreover, we will study how mobile recharging stations can be used to improve the task completion success rate of the swarm. To evaluate our solution, both a simulation tool and testbed with hardware prototypes will be developed.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Lemoine Wouter

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Low-power wireless technology tends to be used today for simple monitoring applications, in which raw sensor data is reported periodically to a server for analysis. The ambition of the OpenSwarm project is to trigger the next revolution in these data-driven systems by developing true collaborative and distributed smart nodes, through groundbreaking R&I in three technological pillars: efficient networking and management of smart nodes, collaborative energy-aware Artificial Intelligence (AI), and energy-aware swarm programming. Results are implemented in an open software package called "OpenSwarm", which is verified in our labs on two 1,000 node testbeds. OpenSwarm is then validated in five real-world proof-of-concept use cases, covering four application domains: Renewable Energy Community (Cities & Community), Supporting Human Workers in Harvesting (Environmental), Ocean Noise Pollution Monitoring (Environmental), Health and Safety in Industrial Production Sites (Industrial/Health), Moving Networks in Trains (Mobility). A comprehensive dissemination, exploitation, and communication plan (including a diverse range of activities related to standardization, educational and outreach, open science, and startup formations) amplifies the expected impacts of OpenSwarm, achieving a step change enabling novel, future energy-aware swarms of collaborative smart nodes with wide range benefits for the environment, industries, and society.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project website

Project type(s)

• Research Project

Abstract

Virtual and augmented reality (VR/AR) has arisen as the killer application for future wireless networks. Such applications are expected to require up to several gigabits per second (Gbps) of throughput, as well as millisecond end-to-end latency to enable interactivity. Current wireless local area networking (WLAN) technologies, such as Wi-Fi, cannot attain such high throughputs. However, increasing the radio transmission frequency up to the millimeter-wave (mmWave) band (i.e., 30-300 gigahertz), would support network throughputs up to tens or even hundreds of Gbps. One important hurdle needs to be overcome though: mmWave transmission suffers from high propagation loss and heavy attenuation by obstacles (e.g., walls, people). As such, latency and throughput are highly variable due to user movement and obstacles. In WaveVR we aim to address this issue, and make mmWave technology suitable for future interactive VR/AR applications with mobile devices. We will achieve stable throughput and millisecond latency by introducing the novel concept of context-awareness to mmWave networks. User, network and environmental context (e.g., user location and movement, detected obstacles) will be used to optimize protocols from the data link to the application layer, and enable seamless multi access point transmissions to avoid obstacles. A novel evaluation approach, combining technical metrics with user perception is envisioned.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Lemic Filip

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Swarm robotics enables large groups of robots to collaborate on complex tasks, which requires low latency many-to-many wireless communication among them. Enabling such communication is still an open issue and is complicated by the fact that robots need to rely on unpredictable ambient energy harvesting for long-term autonomy. Traditionally, multi-hop wireless networks rely on packet-based store-and-forward protocols, where packets are fully transmitted to the next hop, temporarily stored, and then forwarded further towards the destination. Such protocols require a lot of coordination among nodes, are energy hungry, and have a high latency. This makes them ill-suited to satisfy the requirements of mobile and ambiently-powered robot swarms. We instead propose a radically different solution, based on symbol-synchronous wireless transmission, where nodes forward each received data symbol immediately. This allows all nodes in the network to transmit the packet in parallel, reducing latency by several orders of magnitude. This project is the first attempt to apply symbol-synchronous transmissions in a highly mobile environment with severe energy constraints. We will design two energy efficient symbol-synchronous transceivers, based on infrared (IR) and radio frequency (RF) waves respectively. Additionally, we will investigate energy efficient symbol-synchronous network protocols for ambiently-powered robot swarms and develop a robot prototype using both the IR and RF transceivers.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Weyn Maarten

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Currently, my research interests are in future wireless networks and connected applications. I am particularly interested in zero-energy computing and communications to enable a more sustainable Internet of Things, as well as challenging connected applications enabled by future wireless network technologies, such as networked extended reality, collaborative robot swarms, and distributed edge computing.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The IOF consortium IDLab is composed of academic supervisors at the IDLab Research Group, a UAntwerp research group with members from the Faculty of Science and the Faculty of Applied Engineering. IDLab develops innovative digital solutions in the area of two main research lines: (1) Internet technologies, focusing on wireless networking and Internet of Things (IoT), and (2) Data science, focussing on distributed intelligence and Artificial Intelligence (AI). The mission of the IDLab consortium is to be the number one research and innovation partner in Flanders and leading partner worldwide, in the above research areas, especially applied in a city and its metropolitan surroundings (industry, ports & roads). To realize its mission, IDLab looks at integrated solutions from an application and technology perspective. From an application point of view, we explicitly provide solutions for all stakeholders in metropolitan areas aiming to cross-fertilize these applications. From a technological point of view, our research includes hardware prototyping, connectivity and AI, enabling us to provide a complete integrated solution to our industrial partners from sensor to software. Over the past years, IDLab has been connecting the city and its surroundings with sensors and actuators. It is time to (1) reliably and efficiently connect the data in an integrated way to (2) turn them into knowledgeable insights and intelligent actions. This perfectly matches with our two main research lines that we want to extensively valorise the upcoming years. The IDLab consortium has a unique position in the Flemish eco-system to realize this mission as it is strategically placed across different research and innovation stakeholders: (1) IDLab is a research group embedded in the Strategic Research Centre imec, a leading research institute in the domain of nano-electronics, and more recently through groups such as IDLab, in the domain of digital technology. (2) IDLab has a strategic link with IDLab Ghent, a research group at Ghent University. While each group has its own research activities, we define a common strategy and for the Flemish ecosystem, we are perceived as the leading partner in the research we are performing. (3) IDLab is the co-founder of The Beacon, an Antwerp-based eco-system on innovation where start-ups, scale ups, etc. that work on IoT and AI solutions for the city, logistics, mobility and industry 4.0 come together. (4) Within the valorisation at UAntwerp, IDLab contributes to the valorisation within the domain 'Metropolitanism, Smart City and Mobility'. To realize our valorisation targets, IDLab will define four valorisation programs: VP1: Emerging technologies for next-generation IoT; VP2: Human-like artificial Intelligence; VP3: Learning at the edge; VP4: Deterministic communication networks. Each of these valorisation programs is led by one of the (co-)promoters of the IDLab consortium, and every program is composed of two or three innovation lines. This way, the IDLab research will be translated into a clear program offer towards our (industrial) partners, allowing us to build a tailored offer. Each valorisation program will contribute to the different IOF objectives, but in a differentiated manner. Based on our current experience, some valorisation programs are focusing more on local partners, while others are mainly targeting international and EU funded research projects.

Researcher(s)

• Promoter: Hellinckx Peter
• Promoter: Latré Steven
• Promoter: Mannens Erik
• Promoter: Weyn Maarten
• Co-promoter: Famaey Jeroen
• Co-promoter: Hellinckx Peter
• Co-promoter: Latré Steven
• Co-promoter: Mannens Erik
• Co-promoter: Marquez-Barja Johann
• Co-promoter: Mercelis Siegfried
• Co-promoter: Mets Kevin
• Co-promoter: Oramas Mogrovejo José Antonio
• Co-promoter: Saldien Jelle
• Co-promoter: Verdonck Tim
• Co-promoter: Weyn Maarten
• Fellow: Braem Bart
• Fellow: Braet Olivier

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

BEL6GICA is a concerted action that combines the contributions of the best academic research groups and institutes in this field across Belgium to map the landscape, identify specific needs, review complementarities and gaps, and establish a roadmap to maximize the impact and opportunities for Belgium in a future world where a region's competitiveness will depend heavily on the frictionless use of artificial intelligence (both centrally and at the edge of the network among citizens, government and businesses), the associated public and private data flows, the link between the physical and virtual worlds, and the know-how around it. Moreover, we will take in account both sustainability for 6G and 6G for sustainability. As Nokia's CEO said: "There is no green without digital". This is the world of 6G.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

To deliver on our European 6G vision for the 2030s, and to tackle opportunities and challenges of increasing magnitude, e.g.,sustainability, trustworthiness, green deal efficiency, digital inclusion, there is need for a flagship project, towards the elaboration of aholistic 6G network platform and system. To fill this need, Hexa-X-II is proposed with the ambition of being this flagship project, andof inspiring the world for digital transformation through novel 6G services. Hexa-X-II will work, beyond enabler-oriented research, tooptimized systemization, early validation, and proof-of-concept; work will progress from the 6G key enablers that connect the human,physical, and digital worlds, as explored in Hexa-X, to advanced technology readiness levels, including key aspects of modules /protocols / interfaces / data.Hexa-X II includes: (a) the provision of advanced / refined use cases, services, and requirements, ensuring value for society; (b) thedelivery of the 6G platform blueprint, which will encompass enhanced connectivity for 6G services, mechanisms realizing the"networks beyond communications" vision (sensing, computing, trustworthy AI), efficient network management schemes; (c) therealization of extended validation at system and component level; (d) actions for global impact, while assuring strategic autonomy incritical areas for the EU.Europe is starting from the pole position with 6G research and is leading wireless network technologies today. Now is the time toleverage our joint research ambition with a flagship project that will lead the R&D effort towards end-to-end systemization andvalidation. The Hexa-X-II flagship is a unique effort and a holistic vision, of a 6G system of integrated technology enablers, whichaccomplish "beyond the sum of the parts", and of a "network beyond communications" platform for disruptive economic /environmental / societal impact; these are vital for establishing the European 6G technology leadership!

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Marquez-Barja Johann
• Co-promoter: Weyn Maarten

Research team(s)

• Internet Data Lab (IDLab)

Project website

Project type(s)

• Research Project

Abstract

In recent years, edge computing has emerged as a novel computing paradigm for the Internet of Things (IoT). It reduces end-to-end latency, congestion, bandwidth consumption, and improves local load balancing capabilities and scalability in terms of resource and energy consumption. On the other hand, when pushing this model to the far edge, sensors and other computing devices have severely constrained capabilities (i.e., computational power, storage, and energy) compared to traditional edge or cloud servers. This significantly complicates the deployment and execution of machine learning (ML) algorithms at the edge. This problem is being addressed by the TinyML community, by allowing individual low-power sensors and other far edge devices to run basic ML algorithms. However, this progress is insufficient to implement complex far edge applications, where edge device is in an environment or context that slowly changes over time. At the same time, due to the massive increase in IoT devices, more and more materials and batteries are being used. The combination of these two trends will require new methods to continue processing sensor data in an optimal way without further burdening the earth and the environment. The IOF POC Saints project aims to fill this gap by enabling sensors and peripherals with limited resources (materials, energy, and environmental impact) to learn and make decisions by aligning their activities with the availability of computing and energy sources on sensor equipment with limited resources. This by bringing together various innovations that have been developed within IDLab, applying them to these application domains and taking the first steps to valorize this in various domains.

Researcher(s)

• Promoter: Weyn Maarten
• Co-promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The idea that humans learn by doing forms the basis of modern training methodologies, which prioritize practice over theory. However, practical training requires inexperienced students to operate expensive and possibly dangerous equipment under the constant supervision of an expert trainer. Advances in virtual reality (VR) provide a potentially much safer and cost-effective practical training solution. Current VR systems, however, do not allow lifelike interactions among multiple users, and can thus not support collaborative virtual learning. Several barriers stand in the way of a new generation of interactive multi-user VR experiences: (i) the use of wired VR headsets, (ii) unintuitive virtual avatar control, and (iii) cybersickness due to desynchronization. INTERACT aims to break these barriers by developing a flexible wireless network solution for VR headsets connected to an edge-cloud VR training platform that keeps the user's actions and movements synchronized in both space and time.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The standard management capabilities of commercially available devices in a combined wired/wireless (Ethernet, WiFi, Bluetooth) environment does not allow to meet the strict requirements for end-to-end (E2E) delays and jitter. VELOCe will make improvements and add extensions to the latest WiFi 6/6E and LE Audio standards and benchmark these. Specifically, VELOCE E2E, will develop compatible mechanisms to reduce delays caused by communication and full control and verification of audio processing, and real-time device and network settings adaptable based on E2E performance measurements.

Researcher(s)

• Promoter: Marquez-Barja Johann
• Co-promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

5G is the most energy-hungry mobile technology yet, reaching the limit of what the planet and society can environmentally and practically afford. There is already plenty of research towards sustainable and zero-energy end-devices, but huge gains in the energy efficiency and sustainability of the power-hungry network infrastructure behind them are still to be achieved. SAMBAS' project vision represents a holistic approach in driving a significantly more sustainable beyond-5G wireless communications network, where joint considerations of radical innovations at radio, network, and service levels will lead to critically reduced power needs. SAMBAS contributes towards this goal by developing an innovative sustainable millimetre wave (mmWave) micro base station (μBS) that makes effective use of renewable energy harvesting in combination with extremely energy-efficient hardware, and communications protocols to reduce power consumption. At the networking level, we aim to reduce signalling overhead and energy requirements by an order of magnitude through distributed in-band context dissemination and energy-aware networking. Finally, through joint energy-aware network and cloud resource optimization, a sustainable end-to-end mmWave-based system will be developed. We target beyond-5G performance in terms of latency, ultra-high capacity data rates, reliability, and range, while targeting a significant reduction in the reliance on non-renewable energy sources. An integrated prototype will be validated via a multi-user indoor interactive virtual reality application, and an outdoors vehicular communications application.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The Internet of Things (IoT) vision has enabled the wireless connection of billions of battery-powered devices to the Internet. However, batteries are expensive, bulky, cause pollution and degrade after a few years. Replacing and disposing of billions of dead batteries every year is costly and unsustainable. We posit the vision of a sustainable Internet of Battery-Less Things (IoBaLeT). We imagine battery-less devices storing small amounts of energy in capacitors, harvested from their environment or obtained through simultaneous wireless information and power transfer (SWIPT). Using this energy, these intermittently-powered devices are able to cooperatively perform sensing, actuation and communication tasks. Existing battery-less technology has many shortcomings. Such devices, usually based on passive RFID and backscatter, only support simple sensing, unable to handle more complex application logic. Networks do not scale, have a short range and a very low throughput. The goal of IoBaLeT is to bring battery-less technology to the next level. We envision battery-less devices and networks that support complex sensing and actuation applications, and offer throughput, scalability and range on-par with their battery-powered counterparts. To achieve this, we propose a novel battery-less IoT device design that relies on a combination of SWIPT, hybrid energy harvesting, active transmissions and wake-up radios. The project will innovate in terms of SWIPT efficiency, battery-less networking protocols, and distributed intermittent computing paradigms and scheduling algorithms. Leaving batteries behind will enable IoT applications at an unprecedented scale, with a significantly extended lifetime and in hard-to-reach places.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Delgado Carmen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Nanotechnology is paving the way toward nanodevices that will enable several groundbreaking healthcare applications. Nanodevices are expected to flow through the human body, perform actions at certain locations, and communicate monitoring results to the outside world. There is, therefore, a need to enable two-way communication between the nanodevices and the outside world, as well as their localization inside the body. These functionalities should be supported while simultaneously maintaining tiny form factors and a low energy consumption profile of a potentially vast number of nanodevices. In the ScaLeITN project, I will utilize wireless signals in the terahertz (THz) frequencies for enabling both localization and communication capabilities. Localization will be enabled through THz backscattering, which is an unexplored paradigm that promises low energy and high precision nanoscale localization. The constrained communication range characteristic for in-body propagation will be mitigated through multi-hopping, where only a selected subset of nanodevices in the multi-hop route will be awoken. Selection of relays will be based on their location estimates and energy lifecycle characterizations. This is again a novel paradigm that promises enabling low power and scalable nanocommunication. The main outcome is to develop a pioneering prototype of an in-body THz nanonetwork with both localization and two-way communication capabilities.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Lemic Filip

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The Internet of Things (IoT) is largely powered by batteries. This poses significant challenges for its sustainability and longevity, as batteries are short-lived, bulky and polluting. To overcome this problem, we posit the vision of a battery-less IoT network, where devices are powered by energy harvesting and tiny long-lived capacitors. However, such devices often run out of power, resulting in intermittent on-off behavior. Traditional static sequential applications cannot handle such behavior, as they lose forward progress. This problem can be solved with task-based applications, consisting of a chain of interconnected tasks. Each task performs some atomic function, and its output is saved in non-volatile memory after it successfully completes. This allows the application to ensure forward progress in face of frequent power failures. Optimally scheduling the execution of such tasks, in face of the specific behavior of various energy harvesters, as well as the capacitor, and given extremely constrained resources of battery-less devices, is non-trivial. In this project, we propose a novel task scheduler that takes these aspects, as well as the deadline of tasks into account.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Delgado Carmen
• Co-promoter: Hellinckx Peter
• Co-promoter: Mercelis Siegfried

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The Internet of Things (IoT) vision has enabled the wireless connection of billions of battery-powered devices to the Internet. However, batteries are expensive, bulky, cause pollution and degrade after a few years. Replacing and disposing of billions of dead batteries every year is costly and unsustainable. We posit the vision of a sustainable Internet of Battery-Less Things. We imagine battery-less devices storing small amounts of energy in capacitors, harvested from their environment. Using this energy, these intermittently-powered devices can cooperatively perform sensing, actuation and communication tasks. Existing battery-less technology has many shortcomings. Such devices, usually based on passive RFID and backscatter, only support simple sensing, unable to handle more complex application logic. The goal of this project is to bring battery-less technology to the next level. We envision battery-less devices and networks that support complex sensing and actuation applications. To achieve this, we will investigate a novel energy-aware task scheduler for intermittent devices that intelligently decides which application and network tasks to execute at which time, considering task deadlines, data freshness, expected energy consumption of interconnected tasks and available and expected harvested energy. To further improve performance, cooperative task scheduling extensions to support offloading of computing tasks to powered cloud edge devices will also be investigated.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Hellinckx Peter

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The project aims to realize an autonomous management system for smart buildings that communicate based on the BLEv5 (Bluetooth Low Energy version 5) specification for mesh networks. The system includes (battery-free) devices that harvest energy, a mesh network that provides connectivity offers with the support of quality guarantees and can transfer energy wirelessly, and the connection to application-specific platforms in the Cloud. It will connect devices support them throughout their entire lifespan and thereby, in a demonstrable way, to their meet the required quality guarantees.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project website

Project type(s)

• Research Project

Abstract

Nowadays, predictive maintenance, remote monitoring of machinery, real-time communication between employees, etc. is considered essential for efficient operation and management of industrial environments. However, metal-containing ship & harbor environments such as ship compartments, remote control rooms of factories and individual stacked containers, still lack internet coverage, often due to the presence of large blocking metal const ruct ions. This challenge is tackled by the Internet of Shipping (IoS) project, which uses multi-hop sub-GHz wireless mesh network extensions together with locally available wired and wireless technology (e.g., satellite, Wi-Fi, PLC, Ethernet), to provide connectivity and positioning services in challenging shipping environments. The IoS connectivity services will be optimized for (i) safety operations (health monitoring, possibility to trigger alarms), (ii) track and tracing of goods, equipment and employees, (iii) communication between employees (voice calls from remote compartments & locations), and (iv) remote monitoring of machinery operations.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Berkvens Rafael

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Existing wireless technologies often exhibit poor performance in very dense networks, where hundreds or even thousands of stations need to connect to the same access point. This is mostly caused by the increased probability of two devices transmitting data at the same time, which causes the data packets to collide and be lost. Recently, station grouping has been proposed as a new method for collision-free data transmission in these dense environments. The basic idea is that stations are split into groups and each group is given a specific time interval during which only its members can transmit. This limits the maximum simultaneous transmissions, and therefore potential collisions. A station grouping configuration has many degrees of freedom: the number of groups, their duration, and which stations belong to each group. Several algorithms have been proposed to determine the optimal configuration as a function of the number of stations and their traffic demand. However, they all have several shortcomings that we aim to address in this project: they assume very specific and static traffic patterns, they do not optimise the trade-off between energy consumption and performance, and they cannot avoid interference among multiple overlapping networks. In this project, we will develop novel accurate mathematical models, based on Markov chains and supervised machine learning, that accurate estimate the energy consumption and throughput performance of specific station grouping configurations. This will be used to develop real-time station grouping algorithms that can handle heterogeneous stations and traffic, and adapt to changes in the traffic patterns. Finally, the algorithm will be extended to multiple access points, and used to implement interference avoidance mechanisms. The resulting solution will be evaluated using simulation to assess scalability, and will be implemented on real hardware to assess real-time execution time constraints.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Santi Serena

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

This project is part of the IMEC Frame Agreement and is being given as structural investment for fundamental research based on yearly set KPIs from the group to IMEC. This A-budget is defined within the IMEC Way of Working and part of the frame agreement of the University of Antwerp and IMEC.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Existing wireless technologies often exhibit poor performance in very dense networks, where hundreds or even thousands of stations need to connect to the same access point. This is mostly caused by the increased probability of two devices transmitting data at the same time, which causes the data packets to collide and be lost. Recently, station grouping has been proposed as a new method for collision-free data transmission in these dense environments. The basic idea is that stations are split into groups and each group is given a specific time interval during which only its members can transmit. This limits the maximum simultaneous transmissions, and therefore potential collisions. A station grouping configuration has many degrees of freedom: the number of groups, their duration, and which stations belong to each group. Several algorithms have been proposed to determine the optimal configuration as a function of the number of stations and their traffic demand. However, they all have several shortcomings that we aim to address in this project: they assume very specific types of traffic, they cannot be executed in real-time, they cannot handle changes in traffic demand, they cannot provide Quality of Service differentiation among stations, and they cannot optimise multiple overlapping networks. The resulting solution will be evaluated using simulation to assess scalability, and will be implemented on real hardware to assess execution time constraints.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Akbar Raja Usman
• Fellow: Sultania Ashish Kumar

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The goal of MAGICIaN is to overcome the limitations of out-of-the-box NB-IoT that prevent it from being used for mission-critical applications. Specifically, the standard does not natively support QoS differentiation or seamless handover mechanisms. We will design and develop an end-to-end network management solution that brings QoS guarantees on top of out-of-the-box best-effort NB-IoT networks. The MAGICIaN solution consists of two parts. The network controller interfaces and interacts with the NB-IoT access network (i.e., eNodeBs) and the different components in the Evolved Packet Core (EPC) to bring valueadded services on top of the best effort network.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Weyn Maarten

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

In the SPIDER ESA project of Antwerp Space, Imec gives technological advice on data link and network layer protocol design for small satellite constellations and implementation and simulation in the ns-3 event-based network simulator.

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The IoT domain is characterized by many applications that require low-bandwidth communications over a long range, at a low cost and at low power. This has given rise to novel 'SIM-less' radio technologies that try to fill in this existing market gap of low-power wide area IoT networks, often referred to as Low Power Wide Area Networks or LPWANs. Due to the use of sub-GHz radio frequencies (typically 433 or 868 MHz), a single LPWAN base station has a large coverage area, with typical transmission ranges in the order of 1 up to 50 kilometres. As a result, a single base station can support high numbers of connected devices (> 1000 per base station), allowing a broad range of new technology companies to easily enter the IoT market. Currently, several sub-GHz technologies are being promoted simultaneously, all of which use the same (limited) wireless spectrum. Notorious initiatives in this domain are LoRa, SigFox, IEEE802.15.4g and the upcoming IEEE 802.11ah (or "HaloW") standard. However, many of these technologies are still in their infancy, and optimizations regarding a.o. quality of service, roaming, and service management are still lacking. In addition, since the amount of available spectrum is much smaller and the propagation ranges much larger, these technologies will cause interference at much larger scale, leading to severe inter-technology and inter-operator interference. If left unchecked the unlicensed sub-1GHz bands will soon be congested and unreliable. To avoid this fate, the IDEAL-IoT project will design and develop advanced, highly configurable networking components, combined with a coordination framework to uniformly manage and optimize an ecosystem of coexisting wireless sub-GHz LPWANs. More specifically, the project will investigate and develop novel & scalable networking solutions at three levels. 1. At intra-technology level, IDEAL-IoT will improve the performance of existing LPWAN networks. This objective includes (i) increasing the scalability of existing networks through the design and optimization of advanced PHY and MAC protocols for LPWAN networks; (ii) designing intelligent solutions to support real-time LPWAN traffic with latencies below 100 msec and reliability higher than 99.99%; (iii) improving energy efficiency by a factor 2 through PHY&MAC co-design. 2. At inter-technology level, IDEAL-IoT will improve the performance of coexisting LPWAN networks from different operators as well as provide coexistence between different LPWAN technologies. This objective includes: (i) reducing packet loss due to interference by 50% through interference detection, interference mitigation strategies and inter-technology LPWAN communication, negotiation and optimization; (ii) providing inter-technology roaming and multi-hop communication. 3. At management level, IDEAL-IoT will realize technology agnostic solutions for virtualized LPWAN network management and intelligence. This objective includes: (i) technology-agnostic virtualized components and light-weight APIs for real-time creation of virtualized LPWANs, on-the-fly adjustment of SLAs and dynamic installation of virtualized functionalities to control and improve interactions over LPWAN networks; (ii) the design of a cloud repository capable of optimizing LPWAN settings 10 times faster than is currently the case; (iii) realizing fully reliable over-the-air, reconfigurations and partial software updates of large groups of devices with 50% lower latency and 80% less network overhead.

Researcher(s)

• Promoter: Latré Steven
• Co-promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The goal of MuSCLe-IoT is to design the necessary algorithms and protocols for both IoT devices and backend systems to support such multimodal communication and localization. Key innovations are planned in terms of inter-technology load balancing and routing, as well as multimodal GPS-less accurate indoor and outdoor localization. Particular attention will be paid to restrict the resulting footprint, signaling overhead and application impact to a bare minimum. A prototype solution will demonstrate the combined use of Sigfox, LoRa, DASH7 and 802.15.4g

Researcher(s)

• Promoter: Weyn Maarten
• Co-promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project website

Project type(s)

• Research Project

Abstract

The Internet of Things is fostering more and more mission critical applications on top of the wireless infrastructure. An example of this is the control of drones, which requires ultra-reliable communication with ultra low latency guarantees and the ability to switch from one technology to the other. Current IoT networks are currently not suited for providing such guarantees as (i) each technology works independently of each other, (ii) applications sometimes have limited control over the devices that are part of the network and (iii) existing high performing management solutions (e.g., Software Defined Networking) only work with resource rich devices. In this project, I propose a way to reach the same level of flexibility in the management of IoT networks as these high performing management solutions offer, without losing the support for resource constrained nodes and third party devices. We do this through WHISPER, an approach that generates "small lies" (fabricated messages) about the network state with the goal of improving the overall network management and providing guarantees on the application delivery. These messages are used to fool the existing IoT MAC, network and transport protocols in such a way that WHISPER will take control over the full network. This includes routing, link and end-to-end communication. As such, WHISPER can be used to manage a multi-technology IoT environment, where mission-critical applications such as drones can be hosted.

Researcher(s)

• Promoter: Latré Steven
• Co-promoter: Famaey Jeroen
• Fellow: Mennes Ruben

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The High Impact project of IMEC aims at stimulating fundamental research that can benefit in the long term the valorization of the group. Within this project, the following research lines have been funded: - Appdaptive: configuring IoT networks based on application requirements - Participation in the DARPA Spectrum Collaboration challenge - Densenets: SDN-based network management of wireless networks (resulting in the ORCHESTRA framework) - SubWAN: management of new low power wide area wireless networks

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The CONAMO project aims at improving both the training towards and the experience at mass amateur cycling events by continously monitoring and analysing the stream of cycling sensor data generated by the rider and his friends. It does this by introducing both innovations at the network (long-range networks) and the data analysis (machine learning and medical feedback).

Researcher(s)

• Promoter: Latré Steven
• Co-promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Wireless sensor networks (WSNs) have become a very popular concept throughout the last decade, due to their wide applicability in monitoring and control applications (e.g. traffic control, environmental monitoring). They are composed of low-cost, battery-powered, constrained and failure-prone sensors and actuators, which are densely, randomly and redundantly deployed, communicating using wireless radio technologies. Recently, the concept of virtualization was proposed for WSNs. It has been applied to facilitate the creation of virtual sensors that provide more meaningful information by combining readings of multiple physical sensors and to support multi-tenancy and sensor hardware reuse by collocating multiple virtual onto a single physical sensor. The goal of this project is to uncover other, unexplored, benefits of WSN virtualization. Concretely, we will develop fully distributed solutions that allow physical sensors and actuators to self-organize into highly resilient and energy-efficient virtual sensing platforms. Resilience will be provided by exploiting redundancy of sensing hardware and network functions within virtual sensors. Energy-efficiency will be improved by intelligently disabling redundant functionality. Optimizing this trade-off dynamically is the main driver of this project proposal. The first two phases will respectively study control aspects within and between virtual sensors. The third phase will extend the solutions to the highly challenging and mostly unexplored field of mobile sensors.

Researcher(s)

• Promoter: Famaey Jeroen
• Co-promoter: Latré Steven
• Fellow: Mennes Ruben

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

Traditionally, the Internet was designed as a global communication network, allowing computers to exchange information. In the last decade, other types of devices, such as smartphones, have started connecting to the Internet. Currently, we are at the brink of another evolution, called the Internet of Things (IoT). It envisions connecting everyday appliances and devices to the Internet, such as washing machines, heart rate sensors and traffic lights. This evolution paves the way for society-benefiting applications, such as traffic lights that minimize car waiting time and remote monitoring of heart patients. However, connecting all these devices to the public Internet also carries great risk, as users with malicious intent can hack them to retrieve private information, or even worse, take control of them. To prevent this, and allow critical applications to be safely used in the IoT, the (often wireless) network that connects these devices to the Internet must be secured against hacking attempts and be made tolerant (i.e., resilient) against failures in case something does go wrong. However, this is a very challenging problem, since wireless communications can be easily intercepted or changed. Moreover, many devices are placed in public locations, making them susceptible to tampering. Finally, many envisioned IoT devices could move around (e.g., smartphones or implanted sensors), which further complicates things. The goal of this project is to make wireless IoT networks more secure and resilient. Three types of problems will be addressed: (i) internal attacks, (ii) external attacks and (iii) network failures. Internal attacks originate from a device that is already part of the network, caused by malicious (e.g., hackers that take control of a device) or selfish (e.g., users saving their own battery at the cost of others) behaviour. External attacks originate from outside the network and include hackers trying to find security holes. Finally, network failures are caused by unintentional errors, such as software bugs or malfunctioning hardware.

Researcher(s)

• Promoter: Famaey Jeroen
• Fellow: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project

Abstract

The High Impact project of IMEC aims at stimulating fundamental research that can benefit in the long term the valorization of the group. Within this project, the following research lines have been funded: - Appdaptive: configuring IoT networks based on application requirements - Participation in the DARPA Spectrum Collaboration challenge - Densenets: SDN-based network management of wireless networks (resulting in the ORCHESTRA framework) - SubWAN: management of new low power wide area wireless networks

Researcher(s)

• Promoter: Famaey Jeroen

Research team(s)

• Internet Data Lab (IDLab)

Project type(s)

• Research Project