Peter Simons in the morning


Daily between 9 and 10 am, Peter Simons is your host on Radio 4 Brainport. After his studies at TU Eindhoven, Peter became an internationally renowned management consultant. Previously, he presented radio programs for Dutch public radio in Hilversum and for Capital Radio, a business news station in Madrid.

Radio with an instinct


Humans have been exploring the world from the depths of the oceans to the edges of the universe. Yet many environments remain inaccessible, even to modern cutting-edge technology. Therefore problems like exploring the status of waste water under the Fukushima reactor, or discover suitable sites for underground CO2 storage remain unsolved.

Peter Baltus explains how TU/e, RWTH Aachen and KU Leuven study ultra-low power wireless sensor networks. The aim is to investigate a new line of technology that will enable the exploration of difficult-to-access environments exploiting a risky, highly-novel approach called Phoenix.

Phoenix attempts to explore inaccessible environments with physical agents, say small radio nodes, that are extremely limited in size and resources, and can operate without direct control over software and hardware. Phoenix starts with processing a user question, then assesses available knowledge and initiates an evolutionary process involving two nested generational loops. In the outer loop Phoenix develops, deploys and retrieves physical agents capable of penetrating the inaccessible environment and gathering information. Based on this knowledge, a model of the unknown environment is developed and evaluated. This model is refined in the inner loop, where environmental models and abstract representations of the physical agents (virtual agents) co-evolve in a virtual world until an improved generation of physical agents is ready for deployment. The goal of this co-evolution is to maximize the information captured about the unknown environment by progressively optimized agents.

Tussen gigahertz radio en infrarood licht: de wereld van de terahertzen

FLUX at Tue

Electromagnetic waves at frequencies in between radio and infrared light: Terahertz waves offer great new possibilities: ultra high speed radio communication, but also the ability look “through” objects, to detect weapons, explosives, drugs, …. Detecting medical conditions in anon-invasive amnner or even from a distance….. Marion Matters at TU/e explores this exciting field.

Licht kun je beschouwen als radiogolven, maar dan wel van een zeer hoge frequentie, zo hoog dat de eigenschappen als radiogolven niet altijd meer herkenbaar zijn. Maar er zit nog een flink “gat” tussen de hoogste frequentie van de radiogolven die we nu gebruiken en het licht. Maar juist dat onontgonnen stuk van het spectrum, dus tussen Gigahertz radio en infrarood licht in, dat blijkt toch heel interessant. Dat is het domein van de terahertzen.

Met moderne elektronica lukt het maar net om dat soort golven en signalen te maken. Maar de belofte is groot: Het kan worden gebruikt voor extreem snelle radio verbindingen. Maar een even interessante eigenschap is dat allerlei stoffen in resonantie komen bij die terahertzen. En omdat elke molecuulstructuur eigen resonanties heeft kun je complexe stoffen heel precies analyseren. En dat analyseren kan ook op afstand.

Op luchthavens zie je al terahertz scanners, rond draaiende robotarmen in een hokje waar passagiers met armen boven het hoofd in staan om wapens of explosieven te detecteren. Maar er zijn ook toepassingen om door de verpakking heen te scannen hoe vers vlees in de supermarkt is. Of medische toepassingen, om gemakkelijk verschillende medische aandoeningen te herkennen.

De TU Eindhoven werkt hard aan het realiseren van technologie waarmee terahertz signalen kunnen worden gemaakt. Maar ook aan wat je er dan mee kunt doen.

In Studio Brainport, een interview met Marion Matters over de mogelijkheden met terahertzen, op Studio040 in een co-productie met Radio 4 Brainport, zaterdag van 9 tot 10 uur.

You can listen to the English version of the interviews at Radio 4 Brainport.

Latest Trends in Optical Wireless Communication

The Summer Topical Meeting in Los Angeles will provide a platform for debate about the capabilities of optical wireless communication, where their main strengths for application are, and how they can complement/substitute radio wireless techniques, e.g. in the upcoming 5G scenarios.

Jean-Paul Linnartz will give a keynote speech on Wireless Optical Communication in illumination systems. In particular the aspect of power consumption and Energy per Bit


There is an exploding need for wireless communication capacity, driven by the booming amounts of smart mobile devices (tablets, laptops, smart phones, …), the Internet of Things/Everything, connectivity to the Cloud, etc. etc. Radio spectrum is getting seriously congested, radio-based devices are interfering with each other, and are consuming more and more power to surmount the connectivity problems. After optical fiber to the home has solved the copper access network bottlenecks, indoor optical wireless techniques are getting ready to solve the indoor radio network bottlenecks. This Topical Meeting will address the latest research in visible light communication, where data communication is piggy-backed on the LED lighting making quick entry into our buildings, as well as in infrared communication with beam-steered connection techniques for dedicated high data rate connections.

source: Conference announcement

PhD position on Data Analytics for Building Management Services

Project Context

Eindhoven University of Technology (TU/e) is an internationally renowned technical university located in the vibrant technological heart of the Netherlands with high tech companies such as Philips, ASML, NXP and DAF Trucks. The TU/e has an excellent reputation in collaboration with industry proven among other things by the fact that it is the number one university in the world with respect to joint scientific publications with industrial partners.
The TU/e Intelligent Lighting Institute (ILI) was established in 2010 to investigate novel intelligent lighting so-lutions that will become within our reach by the large-scale introduction of LED technology, with a special emphasis on how these new solutions might affect people. It is a collaboration between several departments of the TU/e and industrial partners. ILI has a long-term strategic cooperation with Philips Research Eindhoven. The vacant PhD position is part of a program of 70 PhD students supported by joint funding from the TU/e and Philips, of which 20 PhD students work on Lighting-related topics. These students, together with re-searchers from the TU/e and Philips, form a strong research community working together on scientific and industrial challenges.
The Signal Processing Systems group in the Faculty of Electrical Engineering is internationally recognized for with advanced techniques for signal- and data analysis, SPS has a strong connection to industrial partners which allowes to the group to position its research on the forefront of relevant societal challenges such as improved medical applications and energy-saving yet comfortable control lighting. Its outlook on relevant topics not only contributed to 8 start-up ventures, but also sharpened and focussed its internationally re-warded scientific ambition. The reputation, for instance by 7 awarded Fellow Grade Memberships of IEEE, AES, and OSA in signal processing, is unmatched by any other group in the Netherlands, and only by few oth-er groups in the world.
In the project the candidate will be positioned at Philips Research at the High Tech Campus in Eindhoven. As a global leader in illumination, looking for opportunities to make their lighting products more human centric. Philips Research works closely with global academic and industrial partners to meet people’s needs. By com-bining innovative forces a greater number of innovations are more effective and find a faster way to the market.
Light plays an important role in our lives. Appropriate light settings appear effective to improve our experi-ence in public spaces, in the office, at home, etc. The LED as a light source is reaching technological maturity. This paves the way for a next wave of innovation, in how we experience light and how we can dynamically adapt our environment to improve our wellbeing. LEDs allow a finer granularity of lighting control. Not only the intensity but also other parameters such as color temperature can be set and adapted during the day. Thereby LEDs can enable improvements to health and wellbeing. However, in practice it turns out to be very difficult to capture these benefits.

The lighting infrastructure provides opportunities to support a wide range of applications and services, includ-ing building management and support of the work flows that are used by the organization in the building. Big data is seen as a next revolution in the digital age. This project aims at the use of data from practical installa-tions, the extraction of useful features from sensor measurements, and the analysis of these features in re-lation to relevant building performance indicators. These can include user comfort preferences, wellbeing or efficiency and effectiveness criteria that are relevant to the facility manager.
The project will use data from a fully connected lighting system from which data is gathered in every luminaire in the ceiling. In this project, we approach the problem as much as possible as a characterization and parameter estimation problem wherever adequate models exist (exploiting prior insights and quantified model in a white box approach), and exploit these in model-based data analytics and machine learning methods. We are interested comparing the merits of analysis of Building data for instance by searching for (non-) linear relations, activity estimation by Hidden Markov Chains, preference elicitation algorithms, machine learning, and Context Tree Weighting.

Job qualifications
Candidates should:
• have a strong MSc in Electrical Engineering, Mathematics, Statistics, Computer Science, Physics, or a related discipline
• have a strong interest in data science and signal processing or control systems research
• be highly motivated, be rigorous and disciplined when developing algorithms and software according to high quality standards
• be a fast learner, autonomous and creative, show dedication and be hard working
• possess good communication capabilities and be an efficient team worker
• be fluent in English, both spoken and written
PhD students are expected to:
• perform scientific research in the domain described
• collaborate with other researchers in this project
• present results at (international) conferences
• publish results in scientific journals
• participate in activities of the group and department, at both sites
• assist in teaching undergraduate/graduate courses
• participate in EIT doctoral training on entrepreneurship and related topics
• be willing to work at two locations (TU/e campus and Philips High Tech Campus)
Appointment and salary
PhD students will be officially appointed at the Faculty of Electrical Engineering. Prof. J.P. Linnartz will act as prime PhD supervisor. The project runs in cooperation with the Faculty of Mathematics and Computer Sci-ences and with Philips Research.
We offer:
• a full-time temporary appointment for a period of 4 years, with an intermediate evaluation after 9 months
• a gross salary of € 2,083 per month in the first year increasing up to € 2,664 per month in the fourth year
• a holiday allowance of 8% and an end-of-year bonus of 8.3% (annually)
• assistance in finding accommodation (for foreign employees)
• the opportunity to perform research in a large-scale joint project from a leading technical university and a leading high-tech company
• support for your personal development and career planning including participation in the EIT doctoral training, courses, summer schools, conference visits, research visits to other institutes (both aca-demic and industrial), etc.
• a broad package of fringe benefits (including excellent technical infrastructure, child day care, savings schemes and excellent sport facilities).

Human Centric Lighting in Lighting Control Systems

The Dutch funding agency STW has approved the ILI project proposal Optilight. This project will strengthen the cooperation between various Lighting-oriented groups at TU/e. At the moment the project is searching PhD candidates who are interesting in mathematical optimization for human centric lighting.

From experiments to theory to algorithms

The project aims to make lighting control systems more centered towards the human user. This requires not only better insights in how humans experience light but also demands quantified models and optimization algorithms that are executed by automated lighting control systems. Despite the growing scientific understanding of the impact of light on, for instance, wellbeing, performance, circadian rhythms and sleep, benefits of this understanding cannot (yet) easily be harvested in practical systems. We lack scalable algorithms that can be used in automated systems and that can be deployed in different environments without extensive tuning by experienced lighting experts. Scalability towards broad deployment is a key sub goal of this project.

Humans want to experience light as a natural given. Having to adjust the light setting regularly is not attractive. Moreover, people are usually not aware of the longer-term effects of light so they don’t not necessarily select the optimal light setting. On the other hand, automatic controls often fail to offer a comfortable and unobtrusive natural experience and even tend to irritate people. Hence, there exists a huge gap between results obtained in controlled environments and practical deployment.

Capturing human perception in mathematical models

Although control theory and optimizations using statistical signal processing are well established areas, to date they not widely used for lighting control. Yet, in audio and video processing and in gaming, models on human factors are successfully being used by automated systems. Hence the team is confident that better models human on experience and perception can improve automatic control systems. However, it is not straightforward to capture human experience in equations. We believe that an important step is to better quantify the reliability of such expressions and to take this into account in probabilistic algorithms.


This project will bring together experts from Electrical Engineering, Architecture and Human Technology Interaction. Prof. Jean-Paul Linnartz of the Signal Processing and Systems group at EE will lead the overall project. PhD student in his team will apply proposed models of human experience to allow automated optimizations. Prof. Alexander Rosemann and his team studying the Built Environment (Architecture) will analyze data collected in real environments and compare this to data from fully controlled situations. Prof. Yvonne de Kort and Dr. Ingrid Vogels bring in expertise on the impact of light on human functioning and visual experience and comfort. Dr. Tanir Ozcelebi of System Architecture and Networking group in Computer Sciences brings in his expertise on programming intelligent and learning behaviour of smart space applications.


Contact: Prof. Jean-Paul Linnartz

j.p.linnartz (at)

EnLight wins ENIAC Innovation award


Participation in large European projects not only gives ILI first hand insights in the system architecture of future lighting control systems, it also is a good way transfer insights and knowledge to many industrial partners. This was particularly rewarding in the large EnLight project, with partners ranging from device suppliers, software and integration specialists to system developers. This project has been awarded with the ENIAC Innovation Award.

The EU applauded how EnLight was exemplary in bringing together key actors in a project of significant size (more than 41M€ R&D investment by 27 partners) to achieve results of genuinely high value to the partners. It highlights the importance of semiconductor technology as a core European competence, which fully delivers on its promise of innovation when taken up by leading actors along the full value chain.

In EnLight, the Signal Processing Systems group at TU/e EE cooperated closely with for instance Philips and NXP. The project had three technical objectives namely the optimization of LED lighting modules, the design of future luminaires and the use of new, intelligent lighting systems. As a result, the energy savings in office applications could be shown at 44% compared to LED retrofit and standard controlled lighting systems. The energy savings in hospitality could nearly be doubled and ended up at a figure of 81% energy reduction by using new luminary designs with intelligent controls. This motivated the journal LED-Professional to devote a full special issue to this project.

Decision rule engine

The EnLight project has given the TU/e PhD candidates Xin Wang and Amir Jalalirad an excellent view of the true problems in the future lighting installations. During the project they refined the initial specification of the rules and implemented the engine on the NXP Jennic platform. The insights they obtained in the requirements of lighting systems were augmented by the intelligent control implemented in the EnLight demonstrations in Oulu (VTT, Finland), Munich (Osram, Germany), and Eindhoven (Philips, The Netherlands).
Scientific Directions
Now in the final year of their PhD project, with the EnLight experience behind them, Xin and Amir are focusing on the next wave of innovation, particularly from the insights of data analytics and optimized control.

In EnLight, the industry has set the stage for an architecture that allows intelligent and energy saving applications to be executed. Prof. Jean-Paul Linnartz, advisor of the two PhD candidates in EnLight, sees the harmonization of a rule engine as a good step forward in EnLight. Particularly the option to adapt rules as the systems learns about its users and its environments enables further innovation towards self-adapting systems. “But in the long run, we may have to extent if-then-else rules with probabilistic optimizations”. “Practical systems will never have absolute knowledge about what human users are preferring. Hence these systems should optimize light setting according to a cost function, rather than make hard choices”. In some of his recent papers Xin Wang has worked this out by modelling of human satisfaction and, for instance, energy consumption in mathematical models. For the human experience that required the inclusion of uncertainty. This avoids to a large extent the annoying wrong decisions that current automatic systems make when sensors are not working perfectly.

Dr. Tjalling Tjalkens, also coaching the PhD candidates at the faculty of Electrical Engineering sees a clear connection between machine learning, information theory and future lighting control. Yet we have to advance the scientific state-of-art, because in well-functioning lighting control, the number of human interventions should be very minimal. Hence such system have only few learning opportunities, much less than academic machine learning algorithms typically require.




Wireless Communication course material


Starting with a U.C. Berkeley course on wireless communication in the early 90s, I collected material on radio communication principles and systems. It has been published as a multi-media CD-ROM by Kluwer and later by Springer, but is now also available on the Internet. Although admittedly some of the material on wireless systems is a bit outdated, the physics of propagation and multipath channels, as well as the basics of multiple access schemes remain highly relevant.