| Petar M. Djuric Stony Brook University (New York, USA) Place: Aula de grados Time: 10:00 h Title: RF-Based Analytics from Intelligent Backscattering in Passive Tag-to-Tag Networks Abstract: We are not far from a future where most physical objects will be cyber-connected and will be tagged for identification and tracking. These tags will also be able to sense activities and interactions around them thus forming context-aware, interactive smart environments possessing unprecedented ambient intelligence. We address a possible type of such tags that have no batteries, are RF-powered tags, and are similar to RFID tags but with more capabilities including tag-to-tag communication. Further, these tags have the capacity to ‘fingerprint’ their surroundings without any need for external active elements. We provide a description of the tags, the principles of their operation, and the various analytics one can derive from their operation. Such tags may have significant implications in future smart environments as the existence of a very large number of tags in the environment will enable a diverse, high granularity dataset for analytics without any need for high-power active radios. Biographical sketch: Petar M. Djuric received his B.S. and M.S. degrees in Electrical Engineering from the University of Belgrade, and earned his PhD degree in Electrical Engineering from the University of Rhode Island. He is a Professor in the Department of Electrical and Computer Engineering at Stony Brook University, New York, and he was also a Research Associate with the Institute of Nuclear Sciences, Vinca, Belgrade. His research interests are in the area of statistical signal processing. His primary interests are in the theory of modeling, detection, estimation, and time series analysis and its application to a wide variety of disciplines including wireless communications and biomedicine. Dr. Djuric is an Institute of Electrical and Electronics Engineers (IEEE) Fellow and associate editor of various international reviews. He was named Distinguished Lecturer of the IEEE, and was winner of the best article prize awarded by the IEEE Signal Processing Magazine in 2007. |
| Pau Closas Northeastern University (Boston, USA) Place: Auditorium Time: 11:30 h Title: Position, Navigation, and Timing in signal-degraded environments Abstract: Global Navigation Satellite Systems (GNSS) is the technology of choice for most position-related applications, when it is available. The term GNSS encompasses GPS, Galileo, GLONASS, or Beidou systems among others. A GNSS receiver relies on a constellation of satellites to estimate a set of range measures from which to compute its position. These distances are calculated estimating the propagation time that transmitted signals take from each satellite to the receiver. The main challenges of GNSS technology arise when operating in complex environments which are either naturally impaired by multipath or shadowing; or intentionally/unintentionally interfered by human-made signals. In the last decade, ushered by an ever increasing demand for availability, accuracy, and reliability, the mitigation of these challenges has steered intense research on advanced receiver design. In this talk we introduce the GNSS landscape and, motivated by its widespread use, highlight the need for securing and protecting GNSS infrastructure. The main threats and sources of interference are classified, along with their impact at various stages of a GNSS receiver. We will discuss recent developments in interference countermeasures, nurtured by advances in robust statistical signal processing and machine learning fields. Biographical sketch: Pau Closas is an assistant professor at the Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, since 2016. He received his MS and PhD in Electrical Engineering from the Universitat Politècnica de Catalunya (UPC) in 2003 and 2009, respectively. He also holds a MS degree in Advanced Mathematics and Mathematical Engineering from UPC since 2014. In 2003, he joined the Department of Signal Theory and Communications, UPC, as a Research Assistant. In 2008 he was Research Visitor at the Stony Brook University (SBU), NY, USA. In 2009 he joined the CTTC, where he was Senior Researcher and Head of the Statistical Inference for Communications and Positioning Department. His primary areas of interest include statistical and array signal processing, estimation and detection theory, stochastic filtering, robust statistics, and game theory, with applications to positioning systems, wireless communications, and mathematical biology. |
