et 4248 Introduction to micro-electronics

Introduction

The course gives an introduction to each of the micro-electronics research groups. On this page, we only show the presentations on Circuits and Systems.

The challenges posed by modern circuits and systems are the mastery of complexity and the clever utilization of physical properties. The distinguishing property of 'circuits' such as VLSI circuits is their ability to realize complex functions using intricate interconnection patterns, while the distinguishing property of a system is its ability to hold and use information. Research in circuits and Systems concentrates on the clever utilization of these properties for signal processing and chip design purposes. The field is dominated by applied mathematics and in particular algebra as a tool for synthesis (design) and analysis (verification).

Presentations (2009)

Introduction to the signal processing part of the group (18 MB)
Introduction to the VLSI design part of the group (1.8 MB)

Presentations (2006)

General introduction to the group

Signal processing for communication (UWB) Array signal processing for radio astronomy System on chip design and automation Electronic design automation and physical IC verification The design of intelligent systems

Essay topics (2008)

Towards flexible spectrum management

Increased demand for radio allocations plus new technological developments (cognitive radio, UWB) motivate changes in the way the radio spectrum is managed. Several governments are considering liberalization, by providing additional licence-free bands and/or allowing "underlays" by secondary users.

1. J. Scott Marcus e.a., "Towards more flexible spectrum regulation", study for the Federal Network Agency, Wik-Consult, Dec. 2005.
2. S. Srinivasa and S.A. Jafar, "Cognitive radios for dynamic spectrum access - The throughput potential of cognitive radio: a theoretical perspective", IEEE Communications Magazine Volume 45, Issue 5, pp. 73-79, May 2007.

Localization using Ultra-Wideband

Localization with centimeter accuracy is a very hot topic recently, with applications in tracking and tracing, telemetry, rescue operations and so on. The wideband character of ultra-wideband (UWB) signals allows for the required accuracy and is robust to all kinds of distortions in the propagation medium (unlike GPS). In [1], an overview of localization methods using UWB are described. Since localization is generally based on synchronization, [2] gives a more detailed look at a practical synchronization algorithm for UWB.

1. S. Gezici, Zhi Tian, G. B. Giannakis, H. Kobayashi, A. F. Molisch, H. V. Poor, and Z. Sahinoglu, "Localization via Ultra-Wideband Radios: A Look at Positioning Aspects for Future Sensor Networks," IEEE Signal Processing Magazine, Vol. 22, No. 4, pp. 70-84, July 2005.
2. Zhi Tian and G. B. Giannakis, "A GLRT Approach to Data-Aided Timing Acquisition in UWB Radios-Part I: Algorithms," IEEE Trans. on Wireless Communications, Vol. 4, No. 6, pp. 2956-2967, November 2005.

Wireless Communications over Time-Varying Channels

Most existing wireless communications systems have been designed assuming that the channel can be regarded as constant over a block of data. Nonetheless market studies predict a rapid growth of high mobility applications, such as wireless gaming, mobile video broadcasting, underwater communications and so on. In that case, existing systems have to be adapted. In [1], this problem is introduced. An example of a solution to solve the problem is addressed in [2].

1. G. Matz and F. Hlawatsch, "Time-Varying Communication Channels: Recent Trends and Open Problems," in Proc of the 14th European Signal Processing Conference, Florence, Italy, September, 2006.
2. L. Rugini, P. Banelli, and G. Leus, "Low-Complexity Banded Equalizers for OFDM Systems in Doppler Spread Channels," EURASIP Journal on Applied Signal Processing, Vol. 2006, Article ID 67404, 2006.

Distributed Signal Processing in Sensor Networks

Sensor networks will become a part of everyday life in the near future. Think for instance about environmental monitoring, health monitoring, space exploration, intelligent transportation, and so on. Different sensor devices will have to collaborate among themselves to create a network for distributed sensing. This is achieved by distributed signal processing algorithms. In [1] and [2], two different approaches are reviewed.

1. Jin-Jun Xiao, A. Ribeiro, Zhi-Quan Luo, and G. B. Giannakis, "Distributed Compression-Estimation Using Wireless Sensor Networks," IEEE Signal Processing Magazine, Vol. 23, No. 4, pp. 27-41, July 2006.
2. J. B. Predd, S. B. Kulkarni, and H. V. Poor, "Distributed Learning in Wireless Sensor Networks," IEEE Signal Processing Magazine, Vol. 23, No. 4, pp. 56-69, July 2006.

Future Large Radio Telescopes (LOFAR and SKA)

In future, radio telescopes will not consist of large dishes, but of large numbers of small antennas which are electronically combined. Because the antennas are not selective, they are sensitive to interference; because the antennas are geographycally distributed, calibration of the ionosphere above each sensor "station" is needed. Two papers that describe current directions are [1] and [2].

1. J.D. Bregman, "Concept design for a low frequency array", Proceedings of SPIE -- Volume 4015, Radio Telescopes, Harvey R. Butcher, Editor, July 2000, pp. 19-32
2. Steven w. Ellingson, "RFI mitigation and the SKA", Experimental Astronomy 2004, 17:261-267, Springer.

|  29 Sep 2008   |