Stefan Michael Moser: Catalogue data in Spring Semester 2015 |
Name | Prof. Dr. Stefan Michael Moser (Professor National Yang Ming Chiao Tung University (until 2021 National Chiao Tung University) - Hsinchu) |
Name variants | Stefan M. Moser |
Address | Inst. f. Signal-u.Inf.verarbeitung ETH Zürich, ETF E 104 Sternwartstrasse 7 8092 Zürich SWITZERLAND |
Telephone | +41 44 632 36 24 |
moser@isi.ee.ethz.ch | |
URL | https://moser-isi.ethz.ch/ |
Department | Information Technology and Electrical Engineering |
Relationship | Lecturer |
Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|
227-0104-00L | Communication and Detection Theory | 6 credits | 4G | S. M. Moser | |
Abstract | This introduction to Detection and Communication Theory offers a glimpse at analog communication, but mainly focuses on the foundations of modern digital communications. Topics include the geometry of the space of energy-limited signals; the baseband representation of passband signals, spectral efficiency and the Nyquist Criterion; the power and power spectral density of PAM and QAM; hypothes | ||||
Objective | This is an introductory class to the field of wired and wireless communication. It offers a glimpse at classical analog modulation (AM, FM), but mainly focuses on aspects of modern digital communication, including modulation schemes, spectral efficiency, power budget analysis, block and convolu- tional codes, receiver design, and multi- accessing schemes such as TDMA, FDMA and Spread Spectrum. | ||||
Content | - Analog Modulation (AM, FM, DSB). - A block diagram of a digital cellular mobile phone system. - The Nyquist Criterion for no ISI and the Matched Filter. - Counting bits/dimension, bits/sec, bits/sec/Hz in base-band. - Power Spectral Density, and the "energy- per-bit" parameter. - Passband communication (QAM). - Detection in white Gaussian noise. - Sufficient statistics. - The Chernoff and Bhattacharyya bounds. - Signals as a vector space: continuous time Inner products and the Gram-Schmidt algorithm. - Block and Convolutional Codes for the Gaussian channel. - Multi-accessing schemes such as FDMA, TDMA, and CDMA | ||||
Lecture notes | n/a | ||||
Literature | A. Lapidoth, A Foundation in Digital Communication, Cambridge University Press 2009 | ||||
227-0420-00L | Information Theory II | 6 credits | 2V + 2U | S. M. Moser | |
Abstract | This course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory. | ||||
Objective | The course has two objectives: to introduce the students to the key information theoretic results that underlay the design of communication systems and to equip the students with the tools that are needed to conduct research in Information Theory. | ||||
Content | Differential entropy, maximum entropy, the Gaussian channel and water filling, the entropy-power inequality, Sanov's Theorem, Fisher information, the broadcast channel, the multiple-access channel, Slepian-Wolf coding, and the Gelfand-Pinsker problem. | ||||
Lecture notes | n/a | ||||
Literature | T.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006 |