MIMO Systems

Module Number: EI7436

Duration: 1 Semester

Occurence: Winter Semester

Number of ECTS: 6


Professor in charge: Wolfgang Utschick

Amount of work

Contact hours: 60

Self-study hours: 120

Total: 180

Description of achievement and assessment methods

Examination with the following elements:- written examination (evaluation of basic theoretical concepts presented in the lecture and tutorials). Up to 20% of the examination can be conducted in the form of multiple choice questions.- voluntary projects (in-depth understanding by programming related algorithms and evaluating practical scenarios). The voluntary projects account for maximally thirty percent of the final grade.

Exam tpye: written

Exam duration (min.): 90

Possibility of retaking: In the next semester: Yes. At the end of the semester: No

Homework: No

Lecture: No

Conversation: No

Written paper: No

Recommended requirements

Linear algebra, analysis, constrained optimization, communications, signal processing, information theory.


Linear and non-linear algorithms for baseband signal processing in multiple input multiple output (MIMO) communication systems (point-to-point, multiple access, and broadcast setup).For point-to-point communication: - capacity for error-free knowledge about the channel state at the transmitter- waterfilling- diagonalization of the MIMO channel- capacity for statistical channel knowledge of the transmitter- rate bounds for erroneous channel state knowledge at the receiverFor multiple access channels: - capacity region via successive interference cancellation- iterative waterfilling- maximum likelihood detection (MLD, sphere decoder)- decision feedback equalization (DFE, optimization of detection order, V-BLAST), linear equalizationFor broadcast channels: - sum rate capacity via dirty paper coding- capacity region, vector precoding (VP)- Tomlinson-Harashima precoding (THP, optimization of precoding order)- linear precoding.

Study goals

At the end of the module, students are able to remember, understand and apply the theory, the basic methodologies and algorithms, the categorization of different perspectives and the current trends for multiple input multiple output (MIMO) systems in wireless communications which represents a key technology in current and future wireless communication systems, and students are able to analyse, evaluate and create MIMO systems and respective numerical algorithms in wireless communications systems and beyond.

Teaching and learning methods

  • Learning method: In addition to the individual methods of the students, consolidated knowledge is aspired by repeated lessons in exercises and tutorials.The students can deepen and broaden their competences by completing additional voluntary projects where they are analysing, evaluating and creating own solutions for practical problems.
  • Teaching method: During the lectures, the students are instructed in a teacher-centered style. The exercises are held in a student-centered way.

Media formats

The following kinds of media are used:

  • Presentations
  • Lecture notes
  • Exercises with solutions as download


The following literature is recommended:

  • E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith, A. Paulraj, and H. V. Poor. MIMO Wireless Communications, Cambridge University Press, 2007.
  •  D. Tse and P. Viswanath. Fundamentals of Wireless Communications, Cambridge University Press, 2005
  • A. Goldsmith. Wireless Communications, Cambridge University Press, 2005.
  • S. M. Kay, Fundamentals of Statistical Signal Processing
  • Estimation Theory. Prentice Hall, 1993
  • T. M. Cover and J. A. Thomas. Elements of Information Theory, Wiley, 1991.