# Search result: Catalogue data in Spring Semester 2018

Electrical Engineering and Information Technology Master | ||||||

Major Courses A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval. | ||||||

Communication | ||||||

Core Subjects These core subjects are particularly recommended for the field of "Communication". | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |
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227-0111-00L | Communication Electronics | W | 6 credits | 2V + 2U | Q. Huang | |

Abstract | Electronics for communications systems, with emphasis on realization. Low noise amplifiers, modulators and demodulators, transmit amplifiers and oscillators are discussed in the context of wireless communications. Wireless receiver, transmitter and frequency synthesizer will be described. Importance of and trade offs among sensitivity, linearity and selectivity are discussed extensively. | |||||

Learning objective | Foundation course for understanding modern electronic circuits for communication applications. We learn how theoretical communications principles are reduced to practice using transistors, switches, inductors, capacitors and resistors. The harsh environment such communication electronics will be exposed to and the resulting requirements on the sensitivity, linearity and selectivity help explain the design trade offs encountered in every circuit block found in a modern transceiver. | |||||

Content | Accounting for more than two trillion dollars per year, communications is one of the most important drivers for advanced economies of our time. Wired networks have been a key enabler to the internet age and the proliferation of search engines, social networks and electronic commerce, whereas wireless communications, cellular networks in particular, have liberated people and increased productivity in developed and developing nations alike. Integrated circuits that make such communications devices light weight and affordable have played a key role in the proliferation of communications. This course introduces our students to the key components that realize the tangible products in electronic form. We begin with an introduction to wireless communications, and describe the harsh environment in which a transceiver has to work reliably. In this context we highlight the importance of sensitivity or low noise, linearity, selectivity, power consumption and cost, that are all vital to a competitive device in such applications. We shall review bipolar and MOS devices from a designer's prospectives, before discussing basic amplifier structures - common emitter/source, common base/gate configurations, their noise performance and linearity, impedance matching, and many other things one needs to know about a low noise amplifier. We will discuss modulation, and the mixer that enables its implementation. Noise and linearity form an inseparable part of the discussion of its design, but we also introduce the concept of quadrature demodulator, image rejection, and the effects of mismatch on performance. When mixers are used as a modulator the signals they receive are usually large and the natural linearity of transistors becomes insufficient. The concept of feedback will be introduced and its function as an improver of linearity studied in detail. Amplifiers in the transmit path are necessary to boost the power level before the signal leaves an integrated circuit to drive an even more powerful amplifier (PA) off chip. Linearized pre-amplifiers will be studied as part of the transmitter. A crucial part of a mobile transceiver terminal is the generation of local oscillator signals at the desired frequencies that are required for modulation and demodulation. Oscillators will be studied, starting from stability criteria of an electronic system, then leading to criteria for controlled instability or oscillation. Oscillator design will be discussed in detail, including that of crystal controlled oscillators which provide accurate time base. An introduction to phase-locked loops will be made, illustrating how it links a variable frequency oscillator to a very stable fixed frequency crystal oscillator, and how phase detector, charge pump and programmable dividers all serve to realize an agile frequency synthesizer that is very stable in each frequency synthesized. | |||||

Lecture notes | Script with slides and notes is available. | |||||

Prerequisites / Notice | The course Analog Integrated Circuits is recommended as preparation for this course. | |||||

227-0418-00L | Algebra and Error Correcting Codes | W | 6 credits | 4G | H.‑A. Loeliger | |

Abstract | The course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course includes a self-contained introduction of the pertinent basics of "abstract" algebra. | |||||

Learning objective | The course is an introduction to error correcting codes covering both classical algebraic codes and modern iterative decoding. The course includes a self-contained introduction of the pertinent basics of "abstract" algebra. | |||||

Content | Error correcting codes: coding and modulation, linear codes, Hamming space codes, Euclidean space codes, trellises and Viterbi decoding, convolutional codes, factor graphs and message passing algorithms, low-density parity check codes, turbo codes, polar codes, Reed-Solomon codes. Algebra: groups, rings, homomorphisms, quotient groups, ideals, finite fields, vector spaces, polynomials. | |||||

Lecture notes | Lecture Notes (english) | |||||

227-0420-00L | Information Theory II Does not take place this semester. | W | 6 credits | 2V + 2U | A. Lapidoth | |

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. | |||||

Learning 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 | |||||

227-0436-00L | Digital Communication and Signal Processing | W | 6 credits | 2V + 2U | A. Wittneben | |

Abstract | A comprehensive presentation of modern digital modulation, detection and synchronization schemes and relevant aspects of signal processing enables the student to analyze, simulate, implement and research the physical layer of advanced digital communication schemes. The course both covers the underlying theory and provides problem solving and hands-on experience. | |||||

Learning objective | Digital communication systems are characterized by ever increasing requirements on data rate, spectral efficiency and reliability. Due to the huge advances in very large scale integration (VLSI) we are now able to implement extremely complex digital signal processing algorithms to meet these challenges. As a result the physical layer (PHY) of digital communication systems has become the dominant function in most state-of-the-art system designs. In this course we discuss the major elements of PHY implementations in a rigorous theoretical fashion and present important practical examples to illustrate the application of the theory. In Part I we treat discrete time linear adaptive filters, which are a core component to handle multiuser and intersymbol interference in time-variant channels. Part II is a seminar block, in which the students develop their analytical and experimental (simulation) problem solving skills. After a review of major aspects of wireless communication we discuss, simulate and present the performance of novel cooperative and adaptive multiuser wireless communication systems. As part of this seminar each students has to give a 15 minute presentation and actively attends the presentations of the classmates. In Part III we cover parameter estimation and synchronization. Based on the classical discrete detection and estimation theory we develop maximum likelihood inspired digital algorithms for symbol timing and frequency synchronization. | |||||

Content | Part I: Linear adaptive filters for digital communication • Finite impulse response (FIR) filter for temporal and spectral shaping • Wiener filters • Method of steepest descent • Least mean square adaptive filters Part II: Seminar block on cooperative wireless communication • review of the basic concepts of wireless communication • multiuser amplify&forward relaying • performance evaluation of adaptive A&F relaying schemes and student presentations Part III: Parameter estimation and synchronization • Discrete detection theory • Discrete estimation theory • Synthesis of synchronization algorithms • Frequency estimation • Timing adjustment by interpolation | |||||

Lecture notes | Lecture notes. | |||||

Literature | [1] Oppenheim, A. V., Schafer, R. W., "Discrete-time signal processing", Prentice-Hall, ISBN 0-13-754920-2. [2] Haykin, S., "Adaptive filter theory", Prentice-Hall, ISBN 0-13-090126-1. [3] Van Trees, H. L., "Detection , estimation and modulation theory", John Wiley&Sons, ISBN 0-471-09517-6. [4] Meyr, H., Moeneclaey, M., Fechtel, S. A., "Digital communication receivers: synchronization, channel estimation and signal processing", John Wiley&Sons, ISBN 0-471-50275-8. | |||||

Prerequisites / Notice | Formal prerequisites: none Recommended: Communication Systems or equivalent | |||||

227-0438-00L | Fundamentals of Wireless Communication | W | 6 credits | 2V + 2U | E. Riegler | |

Abstract | The class focuses on fundamental communication-theoretic aspects of modern wireless communication systems. The main topics covered are the system-theoretic characterization of wireless channels, the principle of diversity, information theoretic aspects of communication over fading channels, and the basics of multi-user communication theory and cellular systems. | |||||

Learning objective | After attending this lecture, participating in the discussion sessions, and working on the homework problem sets, students should be able to - understand the nature of the fading mobile radio channel and its implications for the design of communication systems - analyze existing communication systems - apply the fundamental principles to new wireless communication systems, especially in the design of diversity techniques and coding schemes | |||||

Content | The goal of this course is to study the fundamental principles of wireless communication, enabling students to analyze and design current and future wireless systems. The outline of the course is as follows: Wireless Channels What differentiates wireless communication from wired communication is the nature of the communication channel. Motion of the transmitter and the receiver, the environment, multipath propagation, and interference render the channel model more complex. This part of the course deals with modeling issues, i.e., the process of finding an accurate and mathematically tractable formulation of real-world wireless channels. The model will turn out to be that of a randomly time-varying linear system. The statistical characterization of such systems is given by the scattering function of the channel, which in turn leads us to the definition of key propagation parameters such as delay spread and coherence time. Diversity In a wireless channel, the time varying destructive and constructive addition of multipath components leads to signal fading. The result is a significant performance degradation if the same signaling and coding schemes as for the (static) additive white Gaussian noise (AWGN) channel are used. This problem can be mitigated by diversity techniques. If several independently faded copies of the transmitted signal can be combined at the receiver, the probability of all copies being lost--because the channel is bad--decreases. Hence, the performance of the system will be improved. We will look at different means to achieve diversity, namely through time, frequency, and space. Code design for fading channels differs fundamentally from the AWGN case. We develop criteria for designing codes tailored to wireless channels. Finally, we ask the question of how much diversity can be obtained by any means over a given wireless channel. Information Theory of Wireless Channels Limited spectral resources make it necessary to utilize the available bandwidth to its maximum extent. Information theory answers the fundamental question about the maximum rate that can reliably be transmitted over a wireless channel. We introduce the basic information theoretic concepts needed to analyze and compare different systems. No prior experience with information theory is necessary. Multiple-Input Multiple-Output (MIMO) Wireless Systems The major challenges in future wireless communication system design are increased spectral efficiency and improved link reliability. In recent years the use of spatial (or antenna) diversity has become very popular, which is mostly due to the fact that it can be provided without loss in spectral efficiency. Receive diversity, that is, the use of multiple antennas on the receive side of a wireless link, is a well-studied subject. Driven by mobile wireless applications, where it is difficult to deploy multiple antennas in the handset, the use of multiple antennas on the transmit side combined with signal processing and coding has become known under the name of space-time coding. The use of multiple antennas at both ends of a wireless link (MIMO technology) has been demonstrated to have the potential of achieving extraordinary data rates. This chapter is devoted to the basics of MIMO wireless systems. Cellular Systems: Multiple Access and Interference Management This chapter deals with the basics of multi-user communication. We start by exploring the basic principles of cellular systems and then take a look at the fundamentals of multi-user channels. We compare code-division multiple-access (CDMA) and frequency-division multiple access (FDMA) schemes from an information-theoretic point of view. In the course of this comparison an important new concept, namely that of multiuser diversity, will emerge. We conclude with a discussion of the idea of opportunistic communication and by assessing this concept from an information-theoretic point of view. | |||||

Lecture notes | Lecture notes will be handed out during the lectures. | |||||

Literature | A set of handouts covering digital communication basics and mathematical preliminaries is available on the website. For further reading, we recommend - J. M. Wozencraft and I. M. Jacobs, "Principles of Communication Engineering," Wiley, 1965 - A. Papoulis and S. U. Pillai, "Probability, Random Variables, and Stochastic Processes," McGraw Hill, 4th edition, 2002 - G. Strang, "Linear Algebra and its Applications," Harcourt, 3rd edition, 1988 - T.M. Cover and J. A. Thomas, "Elements of Information Theory," Wiley, 1991 | |||||

Prerequisites / Notice | This class will be taught in English. The oral exam will be in German (unless you wish to take it in English, of course). A prerequisite for this course is a working knowledge in digital communications, random processes, and detection theory. | |||||

227-0558-00L | Principles of Distributed Computing | W | 6 credits | 2V + 2U + 1A | R. Wattenhofer, M. Ghaffari | |

Abstract | We study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques. | |||||

Learning objective | Distributed computing is essential in modern computing and communications systems. Examples are on the one hand large-scale networks such as the Internet, and on the other hand multiprocessors such as your new multi-core laptop. This course introduces the principles of distributed computing, emphasizing the fundamental issues underlying the design of distributed systems and networks: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing. We will cover a fresh topic every week. | |||||

Content | Distributed computing models and paradigms, e.g. message passing, shared memory, synchronous vs. asynchronous systems, time and message complexity, peer-to-peer systems, small-world networks, social networks, sorting networks, wireless communication, and self-organizing systems. Distributed algorithms, e.g. leader election, coloring, covering, packing, decomposition, spanning trees, mutual exclusion, store and collect, arrow, ivy, synchronizers, diameter, all-pairs-shortest-path, wake-up, and lower bounds | |||||

Lecture notes | Available. Our course script is used at dozens of other universities around the world. | |||||

Literature | Lecture Notes By Roger Wattenhofer. These lecture notes are taught at about a dozen different universities through the world. Distributed Computing: Fundamentals, Simulations and Advanced Topics Hagit Attiya, Jennifer Welch. McGraw-Hill Publishing, 1998, ISBN 0-07-709352 6 Introduction to Algorithms Thomas Cormen, Charles Leiserson, Ronald Rivest. The MIT Press, 1998, ISBN 0-262-53091-0 oder 0-262-03141-8 Disseminatin of Information in Communication Networks Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, Walter Unger. Springer-Verlag, Berlin Heidelberg, 2005, ISBN 3-540-00846-2 Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes Frank Thomson Leighton. Morgan Kaufmann Publishers Inc., San Francisco, CA, 1991, ISBN 1-55860-117-1 Distributed Computing: A Locality-Sensitive Approach David Peleg. Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8 | |||||

Prerequisites / Notice | Course pre-requisites: Interest in algorithmic problems. (No particular course needed.) | |||||

252-0407-00L | Cryptography Foundations | W | 7 credits | 3V + 2U + 1A | U. Maurer | |

Abstract | Fundamentals and applications of cryptography. Cryptography as a mathematical discipline: reductions, constructive cryptography paradigm, security proofs. The discussed primitives include cryptographic functions, pseudo-randomness, symmetric encryption and authentication, public-key encryption, key agreement, and digital signature schemes. Selected cryptanalytic techniques. | |||||

Learning objective | The goals are: (1) understand the basic theoretical concepts and scientific thinking in cryptography; (2) understand and apply some core cryptographic techniques and security proof methods; (3) be prepared and motivated to access the scientific literature and attend specialized courses in cryptography. | |||||

Content | See course description. | |||||

Lecture notes | yes. | |||||

Prerequisites / Notice | Familiarity with the basic cryptographic concepts as treated for example in the course "Information Security" is required but can in principle also be acquired in parallel to attending the course. | |||||

227-0147-00L | VLSI II: Design of Very Large Scale Integration Circuits | W | 6 credits | 5G | F. K. Gürkaynak, L. Benini | |

Abstract | This second course in our VLSI series is concerned with how to turn digital circuit netlists into safe, testable and manufacturable mask layout, taking into account various parasitic effects. Low-power circuit design is another important topic. Economic aspects and management issues of VLSI projects round off the course. | |||||

Learning objective | Know how to design digital VLSI circuits that are safe, testable, durable, and make economic sense. | |||||

Content | The second course begins with a thorough discussion of various technical aspects at the circuit and layout level before moving on to economic issues of VLSI. Topics include: - The difficulties of finding fabrication defects in large VLSI chips. - How to make integrated circuit testable (design for test). - Synchronous clocking disciplines compared, clock skew, clock distribution, input/output timing. - Synchronization and metastability. - CMOS transistor-level circuits of gates, flip-flops and random access memories. - Sinks of energy in CMOS circuits. - Power estimation and low-power design. - Current research in low-energy computing. - Layout parasitics, interconnect delay, static timing analysis. - Switching currents, ground bounce, IR-drop, power distribution. - Floorplanning, chip assembly, packaging. - Layout design at the mask level, physical design verification. - Electromigration, electrostatic discharge, and latch-up. - Models of industrial cooperation in microelectronics. - The caveats of virtual components. - The cost structures of ASIC development and manufacturing. - Market requirements, decision criteria, and case studies. - Yield models. - Avenues to low-volume fabrication. - Marketing considerations and case studies. - Management of VLSI projects. Exercises are concerned with back-end design (floorplanning, placement, routing, clock and power distribution, layout verification). Industrial CAD tools are being used. | |||||

Lecture notes | H. Kaeslin: "Top-Down Digital VLSI Design, from Gate-Level Circuits to CMOS Fabrication", Lecture Notes Vol.2 , 2015. All written documents in English. | |||||

Literature | H. Kaeslin: "Top-Down Digital VLSI Design, from Architectures to Gate-Level Circuits and FPGAs", Elsevier, 2014, ISBN 9780128007303. | |||||

Prerequisites / Notice | Highlight: Students are offered the opportunity to design a circuit of their own which then gets actually fabricated as a microchip! Students who elect to participate in this program register for a term project at the Integrated Systems Laboratory in parallel to attending the VLSI II course. Prerequisites: "VLSI I: from Architectures to Very Large Scale Integration Circuits and FPGAs" or equivalent knowledge. Further details: https://vlsi2.ethz.ch | |||||

Recommended Subjects These courses are recommended, but you are free to choose courses from any other special field. Please consult your tutor. | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

227-0120-00L | Communication Networks | W | 6 credits | 4G | L. Vanbever | |

Abstract | The students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used in networks, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience. | |||||

Learning objective | The students will understand the fundamental concepts of communication networks, with a focus on computer networking. They will learn to identify relevant mechanisms that are used to networks work, and will see a reasonable set of examples implementing such mechanisms, both as seen from an abstract perspective and with hands-on, practical experience. | |||||

Lecture notes | Lecture notes and material for the course will be available before each course on: http://comm-net.ethz.ch/ | |||||

Prerequisites / Notice | Prerequisites: A layered model of communication systems (represented by the OSI Reference Model) has previously been introduced. | |||||

227-0216-00L | Control Systems II | W | 6 credits | 4G | R. Smith | |

Abstract | Introduction to basic and advanced concepts of modern feedback control. | |||||

Learning objective | Introduction to basic and advanced concepts of modern feedback control. | |||||

Content | This course is designed as a direct continuation of the course "Regelsysteme" (Control Systems). The primary goal is to further familiarize students with various dynamic phenomena and their implications for the analysis and design of feedback controllers. Simplifying assumptions on the underlying plant that were made in the course "Regelsysteme" are relaxed, and advanced concepts and techniques that allow the treatment of typical industrial control problems are presented. Topics include control of systems with multiple inputs and outputs, control of uncertain systems (robustness issues), limits of achievable performance, and controller implementation issues. | |||||

Lecture notes | The slides of the lecture are available to download. | |||||

Literature | Skogestad, Postlethwaite: Multivariable Feedback Control - Analysis and Design. Second Edition. John Wiley, 2005. | |||||

Prerequisites / Notice | Prerequisites: Control Systems or equivalent | |||||

227-0384-00L | Ultrasound Fundamentals, Imaging, and Medical Applications Number of participants limited to 25. | W | 4 credits | 3G | O. Göksel | |

Abstract | Ultrasound is the only imaging modality that is nonionizing (safe), real-time, cost-effective, and portable, with many medical uses in diagnosis, intervention guidance, surgical navigation, and as a therapeutic option. In this course, we introduce conventional and prospective applications of ultrasound, starting with the fundamentals of ultrasound physics and imaging. | |||||

Learning objective | Students can use the fundamentals of ultrasound, to analyze and evaluate ultrasound imaging techniques and applications, in particular in the field of medicine, as well as to design and implement basic applications. | |||||

Content | Ultrasound is used in wide range of products, from car parking sensors, to assessing fault lines in tram wheels. Medical imaging is the eye of the doctor into body; and ultrasound is the only imaging modality that is nonionizing (safe), real-time, cheap, and portable. Some of its medical uses include diagnosing breast and prostate cancer, guiding needle insertions/biopsies, screening for fetal anomalies, and monitoring cardiac arrhythmias. Ultrasound physically interacts with the tissue, and thus can also be used therapeutically, e.g., to deliver heat to treat tumors, break kidney stones, and targeted drug delivery. Recent years have seen several novel ultrasound techniques and applications – with many more waiting in the horizon to be discovered. This course covers ultrasonic equipment, physics of wave propagation, numerical methods for its simulation, image generation, beamforming (basic delay-and-sum and advanced methods), transducers (phased-, linear-, convex-arrays), near- and far-field effect, imaging modes (e.g., A-, M-, B-mode), Doppler and harmonic imaging, ultrasound signal processing techniques (e.g., filtering, time-gain-compensation, displacement tracking), image analysis techniques (deconvolution, real-time processing, tracking, segmentation, computer-assisted interventions), acoustic-radiation force, plane-wave imaging, contrast agents, micro-bubbles, elastography, biomechanical characterization, high-intensity focused ultrasound and therapy, lithotripsy, histotripsy, photo-acoustics phenomenon and opto-acoustic imaging, as well as sample non-medical applications such as the basics of non-destructive testing (NDT). | |||||

Prerequisites / Notice | Hands-on exercises will help apply concepts learned in the module, and will involve a mix of designing, implementing, and evaluating in simulation environments, such as Matlab FieldII and k-Wave toolboxes. Prerequisites: Familiarity with basic numerical methods. Basic programming skills and experience in Matlab. | |||||

227-0434-10L | Mathematics of Information | W | 8 credits | 3V + 2U + 2A | H. Bölcskei | |

Abstract | The class focuses on fundamental mathematical aspects of data sciences: Information theory (lossless and lossy compression), sampling theory, compressed sensing, dimensionality reduction (Johnson-Lindenstrauss Lemma), randomized algorithms for large-scale numerical linear algebra, approximation theory, neural networks as function approximators, mathematical foundations of deep learning. | |||||

Learning objective | After attending this lecture, participating in the exercise sessions, and working on the homework problem sets, students will have acquired a working knowledge of the most commonly used mathematical theories in data science. Students will also have to carry out a research project, either individually or in groups, with presentations at the end of the semester. | |||||

Content | 1. Information theory: Entropy, mutual information, lossy compression, rate-distortion theory, lossless compression, arithmetic coding, Lempel-Ziv compression 2. Signal representations: Frames in finite-dimensional spaces, frames in Hilbert spaces, wavelets, Gabor expansions 3. Sampling theorems: The sampling theorem as a frame expansion, irregular sampling, multi-band sampling, density theorems, spectrum-blind sampling 4. Sparsity and compressed sensing: Uncertainty principles, recovery algorithms, Lasso, matching pursuits, compressed sensing, non-linear approximation, best k-term approximation, super-resolution 5. High-dimensional data and dimensionality reduction: Random projections, the Johnson-Lindenstrauss Lemma, sketching 6. Randomized algorithms for large-scale numerical linear algebra: Large-scale matrix computations, randomized algorithms for approximate matrix factorizations, matrix sketching, fast algorithms for large-scale FFTs 7. Mathematics of (deep) neural networks: Universal function approximation with single-and multi-layer networks, fundamental limits on compressibility of signal classes, Kolmogorov epsilon-entropy of signal classes, geometry of decision surfaces, convolutional neural networks, scattering networks | |||||

Lecture notes | Detailed lecture notes will be provided as we go along. | |||||

Prerequisites / Notice | This course is aimed at students with a background in basic linear algebra, analysis, and probability. We will, however, review required mathematical basics throughout the semester in the exercise sessions. | |||||

227-0441-00L | Mobile Communications: Technology and Quality of Service | W | 6 credits | 4G | M. Kuhn | |

Abstract | Based on an introduction to wireless communications, the lecture course covers: WLAN and cellular networks, PHY technologies, MAC schemes, mechanisms supporting QoS in wireless networks, QoS measurements and evaluation, benchmarking. | |||||

Learning objective | Introduction to mobile wireless communications, including characteristics of the wireless channel, PHY layer technologies (for example MIMO, OFDM etc.) and MAC layer schemes; comparison of different cellular standards; definition of QoS and support of QoS in wireless networks; understanding QoS measurements, their evaluation and benchmarking in cellular networks. | |||||

Content | - Introduction - Wireless channel, propagation of electromagnetic waves, antenna structures - Mobile communication, modulation techniques, OFDM, MIMO - Wireless networks (cellular networks, access networks) - Wireless standards (e.g. UMTS, LTE, IEEE 802.11) - Services in wireless networks - Quality of service (QoS) in wireless networks (definitions, Key Performance Indicators, mechanisms used to support QoS) - QoS measurements (e.g. voice quality, coverage, delay, throughput) and their statistical evaluation - Benchmarking (methodology, statistical methods and models) Weekly exercises included in the lecture | |||||

Lecture notes | Lecture slides are available. | |||||

Literature | Will be announced in the lecture. | |||||

Prerequisites / Notice | English | |||||

227-0455-00L | Terahertz: Technology & Applications | W | 4 credits | 6G | K. Sankaran | |

Abstract | This block course will provide a solid foundation for understanding physical principles of THz applications. We will discuss various building blocks of THz technology - components dealing with generation, manipulation, and detection of THz electromagnetic radiation. We will introduce THz applications in the domain of imaging, communications, and energy harvesting. | |||||

Learning objective | This is an introductory course on Terahertz (THz) technology and applications. Devices operating in THz frequency range (0.1 to 10 THz) have been increasingly studied in the recent years. Progress in nonlinear optical materials, ultrafast optical and electronic techniques has strengthened research in THz application developments. Due to unique interaction of THz waves with materials, applications with new capabilities can be developed. In theory, they can penetrate somewhat like X-rays, but are not considered harmful radiation, because THz energy level is low. They should be able to provide resolution as good as or better than magnetic resonance imaging (MRI), possibly with simpler equipment. Imaging, very-high bandwidth communication, and energy harvesting are the most widely explored THz application areas. We will study the basics of THz generation, manipulation, and detection. Our emphasis will be on the physical principles and applications of THz in the domain of imaging, communication and energy harvesting. The second part of the block course will be a short project work related to the topics covered in the lecture. The learnings from the project work should be presented in the end. | |||||

Content | PART I: - INTRODUCTION - Chapter 1: Introduction to THz Physics Chapter 2: Components of THz Technology - THz TECHNOLOGY MODULES - Chapter 3: THz Generation Chapter 4: THz Detection Chapter 5: THz Manipulation - APPLICATIONS - Chapter 6: THz Imaging Chapter 7: THz Communication Chapter 8: THz Energy Harvesting PART 2: - PROJECT WORK - Short project work related to the topics covered in the lecture. Short presentation of the learnings from the project work. Full guidance and supervision will be given for successful completion of the short project work. | |||||

Lecture notes | Soft-copy of lectures notes will be provided. | |||||

Literature | - Yun-Shik Lee, Principles of Terahertz Science and Technology, Springer 2009 - Ali Rostami, Hassan Rasooli, and Hamed Baghban, Terahertz Technology: Fundamentals and Applications, Springer 2010 | |||||

Prerequisites / Notice | Good foundation in electromagnetics is required. Knowledge of microwave or optical communication is helpful, but not mandatory. | |||||

227-0478-00L | Acoustics II | W | 6 credits | 4G | K. Heutschi | |

Abstract | Advanced knowledge of the functioning and application of electro-acoustic transducers. | |||||

Learning objective | Advanced knowledge of the functioning and application of electro-acoustic transducers. | |||||

Content | Electrical, mechanical and acoustical analogies. Transducers, microphones and loudspeakers, acoustics of musical instruments, sound recording, sound reproduction, digital audio. | |||||

Lecture notes | available | |||||

252-0526-00L | Statistical Learning Theory | W | 6 credits | 2V + 3P | J. M. Buhmann | |

Abstract | The course covers advanced methods of statistical learning : Statistical learning theory;variational methods and optimization, e.g., maximum entropy techniques, information bottleneck, deterministic and simulated annealing; clustering for vectorial, histogram and relational data; model selection; graphical models. | |||||

Learning objective | The course surveys recent methods of statistical learning. The fundamentals of machine learning as presented in the course "Introduction to Machine Learning" are expanded and in particular, the theory of statistical learning is discussed. | |||||

Content | # Theory of estimators: How can we measure the quality of a statistical estimator? We already discussed bias and variance of estimators very briefly, but the interesting part is yet to come. # Variational methods and optimization: We consider optimization approaches for problems where the optimizer is a probability distribution. Concepts we will discuss in this context include: * Maximum Entropy * Information Bottleneck * Deterministic Annealing # Clustering: The problem of sorting data into groups without using training samples. This requires a definition of ``similarity'' between data points and adequate optimization procedures. # Model selection: We have already discussed how to fit a model to a data set in ML I, which usually involved adjusting model parameters for a given type of model. Model selection refers to the question of how complex the chosen model should be. As we already know, simple and complex models both have advantages and drawbacks alike. # Statistical physics models: approaches for large systems approximate optimization, which originate in the statistical physics (free energy minimization applied to spin glasses and other models); sampling methods based on these models | |||||

Lecture notes | A draft of a script will be provided; transparencies of the lectures will be made available. | |||||

Literature | Hastie, Tibshirani, Friedman: The Elements of Statistical Learning, Springer, 2001. L. Devroye, L. Gyorfi, and G. Lugosi: A probabilistic theory of pattern recognition. Springer, New York, 1996 | |||||

Prerequisites / Notice | Requirements: knowledge of the Machine Learning course basic knowledge of statistics, interest in statistical methods. It is recommended that Introduction to Machine Learning (ML I) is taken first; but with a little extra effort Statistical Learning Theory can be followed without the introductory course. | |||||

Computers and Networks | ||||||

Core Subjects These core subjects are particularly recommended for the field of "Computers and Networks". | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

227-0558-00L | Principles of Distributed Computing | W | 6 credits | 2V + 2U + 1A | R. Wattenhofer, M. Ghaffari | |

Abstract | We study the fundamental issues underlying the design of distributed systems: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques. | |||||

Learning objective | Distributed computing is essential in modern computing and communications systems. Examples are on the one hand large-scale networks such as the Internet, and on the other hand multiprocessors such as your new multi-core laptop. This course introduces the principles of distributed computing, emphasizing the fundamental issues underlying the design of distributed systems and networks: communication, coordination, fault-tolerance, locality, parallelism, self-organization, symmetry breaking, synchronization, uncertainty. We explore essential algorithmic ideas and lower bound techniques, basically the "pearls" of distributed computing. We will cover a fresh topic every week. | |||||

Content | Distributed computing models and paradigms, e.g. message passing, shared memory, synchronous vs. asynchronous systems, time and message complexity, peer-to-peer systems, small-world networks, social networks, sorting networks, wireless communication, and self-organizing systems. Distributed algorithms, e.g. leader election, coloring, covering, packing, decomposition, spanning trees, mutual exclusion, store and collect, arrow, ivy, synchronizers, diameter, all-pairs-shortest-path, wake-up, and lower bounds | |||||

Lecture notes | Available. Our course script is used at dozens of other universities around the world. | |||||

Literature | Lecture Notes By Roger Wattenhofer. These lecture notes are taught at about a dozen different universities through the world. Distributed Computing: Fundamentals, Simulations and Advanced Topics Hagit Attiya, Jennifer Welch. McGraw-Hill Publishing, 1998, ISBN 0-07-709352 6 Introduction to Algorithms Thomas Cormen, Charles Leiserson, Ronald Rivest. The MIT Press, 1998, ISBN 0-262-53091-0 oder 0-262-03141-8 Disseminatin of Information in Communication Networks Juraj Hromkovic, Ralf Klasing, Andrzej Pelc, Peter Ruzicka, Walter Unger. Springer-Verlag, Berlin Heidelberg, 2005, ISBN 3-540-00846-2 Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes Frank Thomson Leighton. Morgan Kaufmann Publishers Inc., San Francisco, CA, 1991, ISBN 1-55860-117-1 Distributed Computing: A Locality-Sensitive Approach David Peleg. Society for Industrial and Applied Mathematics (SIAM), 2000, ISBN 0-89871-464-8 | |||||

Prerequisites / Notice | Course pre-requisites: Interest in algorithmic problems. (No particular course needed.) | |||||

Recommended Subjects These courses are recommended, but you are free to choose courses from any other special field. Please consult your tutor. | ||||||

Number | Title | Type | ECTS | Hours | Lecturers | |

101-0178-01L | Uncertainty Quantification in Engineering | W | 3 credits | 2G | B. Sudret, S. Marelli | |

Abstract | Uncertainty quantification aims at studying the impact of aleatory and epistemic uncertainty onto computational models used in science and engineering. The course introduces the basic concepts of uncertainty quantification: probabilistic modelling of data (copula theory), uncertainty propagation techniques (Monte Carlo simulation, polynomial chaos expansions), and sensitivity analysis. | |||||

Learning objective | After this course students will be able to properly pose an uncertainty quantification problem, select the appropriate computational methods and interpret the results in meaningful statements for field scientists, engineers and decision makers. The course is suitable for any master/Ph.D. student in engineering or natural sciences, physics, mathematics, computer science with a basic knowledge in probability theory. | |||||

Content | The course introduces uncertainty quantification through a set of practical case studies that come from civil, mechanical, nuclear and electrical engineering, from which a general framework is introduced. The course in then divided into three blocks: probabilistic modelling (introduction to copula theory), uncertainty propagation (Monte Carlo simulation and polynomial chaos expansions) and sensitivity analysis (correlation measures, Sobol' indices). Each block contains lectures and tutorials using Matlab and the in-house software UQLab (www.uqlab.com). | |||||

Lecture notes | Detailed slides are provided for each lecture. A printed script gathering all the lecture slides may be bought at the beginning of the semester. | |||||

Prerequisites / Notice | A basic background in probability theory and statistics (bachelor level) is required. A summary of useful notions will be handed out at the beginning of the course. A good knowledge of Matlab is required to participate in the tutorials and for the mini-project. | |||||

227-0126-00L | Advanced Topics in Networked Embedded Systems Number of participants limited to 12. | W | 2 credits | 1S | L. Thiele, J. Beutel, Z. Zhou | |

Abstract | The seminar will cover advanced topics in networked embedded systems. A particular focus are cyber-physical systems and sensor networks in various application domains. | |||||

Learning objective | The goal is to get a deeper understanding on leading edge technologies in the discipline, on classes of applications, and on current as well as future research directions. | |||||

Content | The seminar enables Master students, PhDs and Postdocs to learn about latest breakthroughs in wireless sensor networks, networked embedded systems and devices, and energy-harvesting in several application domains, including environmental monitoring, tracking, smart buildings and control. Participants are requested to actively participate in the organization and preparation of the seminar. | |||||

227-0198-00L | Wearable Systems II: Design and Implementation The course is offered for the last time in the Spring Semester 2018. Please note the specific provisions for the performance assessment. | W | 6 credits | 4G | G. Tröster | |

Abstract | Concepts and methods to integrate mobile computers into our daily outfit. Textile sensors: strain, pressure, temperature, ECG, EMG New substrates (eTextile, Smart Textile), organic material (foils) State-of-the-art in Wearable Systems and components Economical conditions Evaluation of research institutions, groups, projects and proposals. | |||||

Learning objective | To integrate wearable computers also commercially successful in our daily outfit, innovative sensing and communication technologies as well as economical and ethical aspects have to be considered. The course deals with > Textile Sensors: strain, pressure, temperature, ECK, EMG, ... > Packaging: new substrates (eTextiles), organic material (foils) > State-of-the-art and research in Wearable components and systems. > Privacy and Ethics Using a business plan we will practice the commercialisation of our 'Wearable Computers'. Supported by a wiki-tool the course is organized as a seminar, in which the addressed topics are jointly discussed considering the aspect 'Concept of a research proposal'. According to the ETH 'critical thinking initiative' we will analyse and reflect implementation concepts incorporating the social and scientific context. Presentations alternate with workshops and discussions. Instead of an oral examination a thesis in a form of a project proposal can be submitted. The audience determines the used language (German or English) | |||||

Content | To integrate wearable computers also commercially successful in our daily outfit, innovative sensing and communication technologies as well as economical and ethical aspects have to be considered. The course deals with > Textile Sensors: strain, pressure, temperature, ECK, EMG, ... > Packaging: new substrates (eTextiles), organic material (foils) > State-of-the-art and research in Wearable components and systems.. > Privacy and Ethics Using a business plan we will practice the commercialisation of our 'Wearable Computers'. Supported by a wiki-tool the course is organized as a seminar, in which the addressed topics are jointly discussed considering the aspect 'Concept of a research proposal'. According to the ETH 'critical thinking initiative' we will analyse and reflect implementation concepts incorporating the social and scientific context. Presentations alternate with workshops and discussions. Instead of an oral examination a thesis in a form of a project proposal can be submitted. The audience determines the used language (German or English) | |||||

Lecture notes | A wiki-tool will be available for the internal communication; that includes lecture notes for all lessons, assignments and solutions. http://www.ife.ee.ethz.ch/education/wearable-systems-ii.html | |||||

Literature | Will be provided in the course material | |||||

Prerequisites / Notice | Supported by a wiki-tool the course is organized as a seminar, in which the addressed topics are jointly discussed considering the aspect 'Concept of a research proposal'. According to the ETH 'critical thinking initiative' we will analyse and reflect implementation concepts incorporating the social and scientific context. Presentations alternate with workshops and discussions. Instead of an oral examination a thesis in a form of a project proposal can be submitted. The audience determines the date and the used language (German or English) No special prerequisites, also not the participation of 'Wearable Systems 1' |

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