UW-OFDM: Non-linear Receivers

Abstract:

The engineering world is mostly made up from the reuse, reinvention or reapplication of old knowledge, rather than single groundbreaking new findings. Each small advance contributes to human knowledge with an impact that can’t be seen usually until many years later.

As an example, a research summary of non-linear receivers for Unique Word OFDM (orthogonal frequency division multiplexing) is presented, where several data detection techniques for MIMO (multi-antenna) communication systems are reused for a single-antenna setup. This is enabled by the UW-OFDM concept, which opens the range from Bayesian linear data estimation to maximum likelihood detection, opposing to the formerly dull data detection method for classical OFDM.

As an industry example, the limiting factors of the signal sensitivity in FMCW (frequency modulated continuous wave) Radar transceivers are addressed. The problem of on-chip leakage is an inherent problem of signal processing in MMICs (monolithic microwave integrated circuits). How it has been handled in communication ICs might be a clue for how to remarkably enhance FMCW Radar in the future.

Biography:

Alexander Onic is currently Concept Engineer for automotive Radar at Infineon Technologies in Linz, Austria. He received the doctoral degree from Alpen-Adria-Universität Klagenfurt in 2013, where he was part of the research team that invented Unique Word OFDM, a novel signaling scheme for digital communication. In 2007, he graduated with the Dipl.-Ing. degree from Friedrich-Alexander-Universität Erlangen-Nürnberg, after studying electrical engineering with an emphasis on information technology and signal processing. Alex‘ research interest in signal processing, communication engineering and estimation theory is consequently supplemented by the research cooperation of Infineon and Johannes-Kepler-Universität Linz on Radar signal processing topics.

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„BigMedia“: Multimedia goes Big Data

Abstract:

Ever more multimedia data gets produced, stored, and shared. This is a well-known phenomenon and quite common for information technology, one might say, but multimedia as a field of computing has always been aiming at humans rather than computers as ultimate consumers: computing was mostly an auxiliary on the path from media creation to human consumption. Despite increasing automation, human consumption is likely to remain the dominating multimedia use case. Since humans have rather fixed sensing and processing capabilities, the dramatic increase in multimedia data production and online availability poses particular “ multimedia big data“ challenges – the more so since the characteristics of multimedia make the well-known „four V“ of big data particularly virulent.

In light of the aforementioned development, the talk will look at big data challenges for multimedia and at upcoming approaches to meeting these challenges. The problem space will be structured according to an imaginary „processing pipeline“ that starts from media capturing via networking and storage/processing until presentation/consumption. Some nonfunctional aspects such as privacy will be addressed, too.

Biography:

Max Mühlhäuser is a Full Professor of Computer Science at Technische Universität Darmstadt, Germany, and head of the Telecooperation Lab. In 1986, he received his Doctorate from the University of Karlsruhe and soon afterwards founded the first European research center for Digital Equipment Corp. (DEC). Since 1989, he worked as either professor or visiting professor at universities in Germany, Austria, France, Canada, and the US. Max published more than 450 articles, co-authored and edited books about Ubiquitous Computing, E-learning, and distributed & multimedia software engineering. Max is deputy speaker of a nationally funded cooperative research center on the Future Internet and directorate member of the Center for Advanced SEcurity research Darmstadt (CASED).

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Privacy and Security Challenges in the Smart Grid User Domain

The term „smart grids“ is used to describe the next-generation intelligent energy systems. Smart grids employ state-of-the-art information and communication technology to control generation, distribution and consumption of energy. The degree of information needed on network status is vastly more accurate compared to traditional power networks, and needs to be available in fine granularity in near real-time. The availability of such fine-grained data raises severe privacy concerns in the end-user domain.  For example, the application of non-intrusive load monitoring techniques to high-resolution load profiles allows inferring details on user behavior such as presence, sleep-and-wake cycles and the brands of used appliances. Another challenge in the widespread adoption of smart grid technologies lies in the domain of security. Recent reports of smart meters that can easily be hacked and used to remotely control energy availability in the connected household have not helped to increase user trust. In this talk, the main challenges in the area of smart grid privacy and security from an end-user perspective will be reviewed. At the example of smart metering, selected solutions will be discussed in detail.

Dominik Engel is a professor at the Salzburg University of Applied Sciences in Austria, where he heads the Josef Ressel Center for User-Centric Smart Grid Privacy, Security and Control. He holds a PhD degree in Computer Science from the University of Salzburg. Prior to joining Salzburg University of Applied Sciences, Dominik Engel was a researcher at the Universities of Bremen and Salzburg and product manager at Sony DADC, where he was responsible for video content security. His research interests include smart grid security, multimedia security and technological methods for enhancing end-user trust.

 

 

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