Additional teaching materials for the Communication and Signal Processing (CSP) major of German-Russian Institute of Advanced Technologies (GRIAT): Multiple Input Multiple Output (MIMO) technology.

• Desirable background:
  • Rician flat fading (SISO)
• Tutorials:
  • MIMO channel capacity
  • Space-Time Codes (Alamouti)
• Self-education:
  • Spatial correlation (tasks)

This work is prepared for students of MS-CSP (Communication and Signal Processing) program (GRIAT) primarily. However, everyone who is interested in considered topics is welcome!

Why should you learn MIMO technology basics?

MIMO is a part of the most of modern wireless communication standards. For example, this is implemented in LTE/LTE-A networks and in Wi-Fi devices since 802.11n (Wi-Fi 4).

Moreover, the evolution of the MIMO - Massive MIMO is a part of the 5G networks. This fact means scientific interest, and science is impossible without basics.

Realizing 5G Sub-6-GHz Massive MIMO Using GaN

Additionally, MIMO topic is a good opportunity to train your linear algebra skills!

• Paulraj, Arogyaswami, Rohit Nabar, and Dhananjay Gore. Introduction to space-time wireless communications. Cambridge university press, 2003.
• Salehi, M., and J. Proakis. "Digital communications." McGraw-Hill Education 31 (2007): 32.
• Haykin, Simon S. Digital communications. New York: Wiley, 1988.
• Goldsmith, Andrea. Wireless communications. Cambridge university press, 2005.
• Sklar, Bernard. Digital communications: fundamentals and applications. 2001.

The work on this project inspired me to write several popular science articles in my native language. Probably, it can be also helpful for someone:

• Оцениваем пропускную способность MIMO канала (алгоритм Water-pouring прилагается)
• MU-MIMO: один из алгоритмов реализации
• MIMO spatial diversity: Аламоути, DET и прочее пространственное разнесение
• Почти самый простой MIMO канал с замираниями (модель Кронекера прилагается)

And several matherials about adaptive and array signal processing:

• Adaptive beamforming (Python 3 source code)
• Adaptive filters (Python 3 / MATLAB source codes)
• Моделируем алгоритм MUSIC для задач определения направления прихода электромагнитной волны
• Оптимальная линейная фильтрация: от метода градиентного спуска до адаптивных фильтров

I'll be appreciate your stars because in my oppinion this is one of the brightest indicators of a good work!

You also can send your comments and suggestion by e-mail: [email protected]

The feedback is valuable for me!

Have a nice reading, good day, and good luck!

M.Sc. Vladimir Fadeev