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!!! NOTE: This course is no longer current and have been archived for reference purposes. [1]

Course Description: MIMO Systems and Adaptive Transmission (34331600 L 006)

Course Objectives

Multiple-Input Multiple-Output (MIMO) in wireless systems refers to the use of multiple transmission and reception antennas in order to create an additional “spatial" dimension for signalling over wireless channels, beyond the conventional time-frequency dimensions. MIMO has emerged as one of the most useful and promising approaches to achieve high spectral efficiency in modern wireless systems, and various MIMO technologies have been adopted in current wireless communication standards. This course provides a profound theoretical understanding of MIMO. The target is to enable students to make use of MIMO in their own hands-on implementation projects. In addition, special emphasis is given to adaptive transmission techniques, where the choice of the MIMO scheme, including power, bit-loading, number of multiplexed data streams, precoding scheme, user selection scheduling, is adaptively chosen according to the available channel state information.
Course Content

1. Introduction: Why parallel transmission is more efficient than serial?
2. MIMO channels
  • Singular value decomposition (SVD)
  • Parallel transport of multiple data streams over random channels

3. MIMO Capacity
  • Derivation from multivariate information theory
  • Normalization of the channel, effective path loss

4. MIMO Transmission
  • Channel estimation and how the transmitter can be informed about the channel
  • Using channel information at the receiver, at the transmitter and at both sides
  • Closed-loop operation as the best trade-o_ between performance and complexity
  • Real-time implementation

5. Link adaptation for MIMO
  • Overview on serial-link schemes
  • Extension to MIMO
  • Introduction to Multiuser MIMO

6. Applications
  • MIMO in wireless LANs
  • MIMO in cellular networks
  • Vectoring

7. Recent research in wireless and optical networks

Mainly intended for Study Programs
  • Elektrotechnik MSc; 1-1
  • Technische Informatik MSc; 1-1
  • Informatik MSc; 1-3
  • Technomathematik MSc; 1-3
  • Wirtschaftsingenieurw. MSc/Elektrotechnik; 1-3
Course Supporting Material
  • C. Eckart and G. Young, A Principal Axis Transformation for Non-Hermitian Matrices, Bull. Am. Math. Society, vol. 45, no. 2, pp.118-121, 1939.
  • G. Foschini and M. Gans, On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas, Wireless Personal Commun., vol. 6, pp.311-335, 1998. 
  • E. Telatar, Capacity of Multi-antenna Gaussian Channels, Europ. Trans. Telecommunications, vol. 10, no. 6, pp.585-595, 1999. 
  • S. Kullback, Information Theory and Statistics. Dover Publications, Inc. Mineola, New York, 1968.
  • B. Hochwald, T. Marzetta, V. Tarokh, Multiple-Antenna Channel Hardening and its Implications for Rate Feedback and Scheduling, IEEE Trans. Inf. Theory, vol. 50, no. 9, pp.1893-1909, Sept. 2004.
  • B. Steiner and P. Jung, Optimum and Suboptimum Channel Estimation for the Uplink of CDMA Mobile Radio Systems with Joint Detection, Europ. Trans. Telecom., vol. 5, no.1, pp.3950,1994. 
  • V. Jungnickel et al., A MIMO System with Reciprocal Transceivers for the Time-Division Duplex Mode, in Proc. IEEE Int. Symp. Antennas and Propagation Society, vol. 2, June 2004, pp.1267-1270.
  • M. Costa, Writing on Dirty Paper, IEEE Trans. Inf. Theory, vol. 29, no. 3, pp.439- 441,1983.
  • Q.H. Spencer et al., "Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels," IEEE Trans. Signal Processing, vol. 52, no. 2, pp.461-471, Feb. 2004.
  • V. van Zelst, T. C. W. Schenk, "Implementation of a MIMO OFDM-based wireless LAN system," IEEE Transactions on Signal Processing, vol.52, no.2, pp.483-494, Feb. 2004.
  • V. Jungnickel et al. Interference-Aware Scheduling in the Multiuser MIMO-OFDM Downlink, IEEE Communications Magazine, vol. 47, no. 6, pp.56 66, June 2009.
  • G. Ginis, J.M. Cioffi, "Vectored transmission for digital subscriber line systems," IEEE Journal on Selected Areas in Communications, vol.20, no.5, pp.1085-1104, Jun 2002. M.Sc. Degree 2014-2015 25
  • M. K. Karakayali et al., Network coordination for spectrally efficient communications in cellular systems, IEEE Wireless Communications, vol. 13, no. 4, pp.56-61, 2006
  • R. Irmer et al., "Coordinated multipoint: Concepts, performance, and field trial results, "IEEE Communications Magazine”, vol.49, no.2, pp.102-111, February 2011
  • V. Jungnickel et al., "The role of small cells, coordinated multipoint, and massive MIMO in 5G," IEEE Communications Magazine, vol.52, no.5, pp.44-51, May 2014
  • T. Morioka et al., "Enhancing optical communications with brand new fibers," IEEE Communications Magazine, vol.50, no.2, pp.31-42, February 2012.

  • C. E. Shannon, A Mathematical Theory of Communication," The Bell System Technical Journal, Vol. 27, pp. 379423, 623656, July, October, 1948.

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