Fundamentals of Wireless Communication
- 8th Semester D-ITET, 6 ECTS credit points
- Mathematics Master: Information and Communication Technology
- Doctoral and Post-Doctoral Studies: Department of Information Technology and Electrical Engineering
- Electrical Engineering and Information Technology Master: Core Courses (Kernfächer)
|Lecture:||Tuesday 10:15-12:00, ETZ E7|
|Discussion session:||Tuesday 8:15-10:00, ETZ E7, starting Feb. 26, 2019|
|Instructor:||Dr. Erwin Riegler|
|Teaching assistants:||Michael Tschannen, Recep Gül|
|Office Hours:||Wednesday, 17:15-18:00, ETF E 119 (Michael Tschannen)|
Note: This class will be taught in English. The oral exam will be in German (unless you wish to take it in English, of course).
The class focuses on fundamental aspects of modern wireless communication systems. Most of the mathematical concepts needed in the class will be reviewed in the discussion sessions.
To get credit for this class, you will need to pass an oral exam. The exam is also required for doctoral students.
We will post important announcements, links, and other relevant information here in the course of the semester, so please check back often.
Wireless communication has been around since the first successful transmission experiments by Marconi in the late 19th century. For most of the time, however, two-way communication over wireless links was difficult, and its usage thus restricted. Only broadcast services like radio and television were widely available. All of this changed about 30 years ago with the advent of digital mobile communication systems, first for voice telephony like in the GSM standard, and later for mobile data services like in the IEEE 802.11 series of standards. Enabling factors were the continuing trend in electronic integration, and the successful development of information and communication theoretic tools to deal with the wireless communication channel. Probably in no other field of engineering is the theoretical underpinning as closely tied to, and as necessary for actual system implementation as in wireless communication. The development has all but slowed down, and recent advances like multi-antenna systems (MIMO), adaptive transceiver algorithms, and ad-hoc networks will improve performance and quality of service for next generation wireless communication systems as well as open up new fields for wireless technology, like distributed sensing and control.
The goal of this course is to develop the fundamental principles of wireless communication, enabling students to analyze and design current and future systems. The outline of the course is as follows:
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 characterization 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 parameters such as delay spread and coherence time. Finally, we derive a discretized version of the channel model, which will be used in the remainder of the course.
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 will 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, and we compute the maximum diversity order achievable as a function of the channel's scattering function.
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 of reliable transmission 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. The wireless channel constitutes a hostile propagation medium, which suffers from fading (caused by destructive addition of multipath components) and interference from other users. Diversity provides the receiver with several (ideally independent) replica of the transmitted signal and is therefore a powerful means to combat fading and interference and thereby improve link reliability. Common forms of diversity are time diversity (due to Doppler spread) and frequency diversity (due to delay spread). 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 shown to yield an impressive increase in spectral efficiency, and has been adapted in, e.g., IEEE 802.11n, IEEE 802.11ac, and LTE. This chapter is devoted to the basics of MIMO wireless systems.
Cellular Systems: Multiple Access and Interference Management
This chapter is devoted to the basics of multi-user communication.
We will start by exploring the basic principles of cellular systems and then take a fundamental look at multi-user channels.
We will then 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 will conclude with a discussion of the idea of opportunistic communication and by assessing this concept from an information-theoretic point of view.
There will be 6 homework assignments. Every other week, a new assignment will be handed out. You can hand in your solutions and get feedback from us, but it is not mandatory to turn in solutions. Complete solutions to the homework assignments will be posted on the course web page.
Homework Problem SetsHomework problem sets and solutions will be posted here.
There is an oral exam (in German, unless you wish to take it in English, of course).
Most of the handouts from class will be posted here, except for the ones where copyright issues prevent us from doing so.
- Syllabus (most important information about the class)
- Summary of basic probability theory
- Delay spread of several measured channels and physical-layer parameters of common wireless systems
If you are somewhat rusty on basic digital communication concepts used over and over again in this class, the following notes by Prof. R.G. Gallager (MIT) are helpful. Our experience from the last years has shown that it is a good idea to review these handouts before we start with the chapter on diversity.
We use some basic results from linear algebra and Gaussian random vectors. Here are some notes by Prof. I.E. Telatar (EPFL) to help you with these matters.
The part on channel modeling is based on the concept of randomly linear time-varying systems. A landmark paper on this topic was written by P.A. Bello back in the early sixties, introducing the concepts we use in class. There is an online version available (only accessible within the ETH network).
If you want to go into more depth or need additional background, please check out these books and papers:
|D. N. C. Tse and P. Viswanath, Fundamentals of Wireless Communication. Cambridge University Press, 2005|
Our lectures on diversity follow Chapter 3, and the part on information theory for wireless channels follows Chapter 5 of this book. The MIMO part follows Chapter 8, and the topics about cellular systems are covered in Chapters 4 and 6.
We highly recommend that you read through these chapters in parallel to the respective lectures.
There is an online version of this book available.
|J. M. Wozencraft and I. M. Jacobs, Principles of Communication Engineering. Wiley, 1965|
This is the book that popularized the signal space approach. It is still one of the best introductory texts around, focusing on the fundamentals rather than obfuscating them through unnecessary details. The notation is somewhat old-fashioned, and wireless communication is hardly covered at all. But if you need to recapitulate some of your digital communication knowledge, this is the book of choice.
|G. D. Forney, Jr. and G. Ungerboeck, Modulation and Coding for Linear Gaussian Channels, IEEE Transactions on Information Theory, 1998 (electronic copy, only accessible within the ETH network).|
This is an outstanding review of digital communication principles.|
|S. G. Wilson, Digital Modulation and Coding. Prentice Hall, 1996|
A book on digital communication in the style of Wozencraft and Jacobs, but with a somewhat more modern notation. It also includes a discussion about communication over fading channels. The signal space approach is used throughout, and the distinction between coding and modulation is made very precise. It requires some familiarity with digital communication, but has a very clear exposition of the fundamental concepts needed in class.
|A. Papoulis and S. U. Pillai, Probability, Random Variables, and Stochastic Processes. McGraw Hill, 4th edition, 2002|
The classic textbook for engineering probability theory, quite extensive in its coverage. It is excellent for reference and if you want to dig deeper.|
|G. Strang, Linear Algebra and its Applications. Harcourt, 3rd edition, 1988|
Linear algebra as easy as it gets. The book covers most of the material we need in this course. It is not as dry as other mathematical texts and stresses intuition more than mathematical rigor.|
|T. M. Cover and J. A. Thomas, Elements of Information Theory. Wiley, 2nd edition, 2006 (electronic copy, only accessible within the ETH network).|
We will need some information theory later on in the course. It is not a prerequisite and we will do our best to explain the concepts used from scratch. But if you want to probe further, or read the material for yourself, have a look at Chapters 1-3 and 8-10.|
|A. Lapidoth, A Foundation in Digital Communication. Cambridge University Press, 2009 (electronic copy, only accessible within the ETH network)|
|A mathematically rigorous introduction to digital communication.|