Mobile Communications, Complete - Interaktive Studienpläne der TU Ilmenau

Basics in stochastics and calculus

After completing this module, the students are able to understand current areas of mobile communication systems. They have a deep understanding of universal (timeless) principles that are applicable in several research areas and disciplines. They can confidently use several fundamental mathematical properties and "tricks", e.g., in the areas of linear algebra, stochastic processes, and time-varying systems.

Fundamental concepts of mobile communication systems are developed in class, ranging from channel modeling to advanced multiple antenna systems. Moreover, important topics for the design of future wireless communication systems are also emphasized.

After participating in this course, the students are able to assess current hot topics from research and development in wireless communications (e.g., 5G, 6G). They are able to read and understand current IEEE journal and conference publications in this area. Moreover, they have been enabled to develop new research ideas and results that build on this published "state-of-the-art."

1 Introduction
+ Overview of mobile communication standards and applications (1G - 5G)
+ 5G Vision and Requirements
+ The Wireless Channel
- Path loss
- Shadowing
- Fast fading

2 Mobile Communication Channels
+ Review: Representation of Bandpass Signals and Systems

2.1 Propagation Modelling
+ Time variance (Doppler)
+ Time-varying multipath channels
- Transmission functions of the time-varying channel (1st set of Bello functions)
- 4 ways to calculate the received signals
- Identification of linear time-varing (LTV) systems

2.2 Statistical Characterization of Multipath Channels
+ Rayleigh channel (fading)
+ Rician channel
+ Channel Correlation Functions and Power Spectra of Fading Multipath Channels
- Time-variations of the channel
- Characterization of a WSSUS channel (2nd set of Bello functions)

2.3 The effect of signal characteristics on the choice of a channel model
+ Frequency non-selective channels
+ Frequency selective channels
- Truncated tapped delay line model of a frequency selective channel

2.4 Space-Time Channel and Signal Models
+ Generalization of the time-varying channel impulse response
- First set of Bello functions extended to the spatial domain
- Example: specular L paths model (continued)
+ Homogeneous channels (WSSUS-HO model)
+ Correlation functions and power spectra extended to the spatial domain
- Second set of Bello functions extended to the spatial domain
- Coherence time, coherence frequency, coherence distance
+ Transmission functions extended to transmit and receive antenna arrays (MIMO)
- Definition of the array manifold
+ Notation for SISO, SIMO, MISO, and MIMO channels
- Example: L paths model (continued)
+ Classical IID Channel Model
+ Extended MIMO Channel Models
- Spatial fading correlation at the transmit and the receive arrays
> Review of the eigenvalue decomposition (EVD)
> General model
> Kronecker model
- Additional Line-of-Sight (LOS) component
+ Sampled signal model for SISO, SIMO, MISO, and MIMO channels

3 Capacity of Space-Time Channels

3.1 Differential Entropy and Mutual Information for Continuous Ensembles (review)

3.2 Capacity Theorem for the AWGN SISO Case (review)

3.3 Capacity of the Flat Fading MIMO channel
+ Differential entropy for CSCG random vectors
+ Choosing Rss (with and without CSI @ the transmitter)
- Singular Value Decomposition (SVD)
- Special case: uncorrelated Rayleigh fading and Mt very large
+ Parallel Spatial Sub-Channels
- Design of the precoder and the decoder for MIMO systems with CSI at the transmitter
- Optimum power allocation (waterpouring algorithm) with CSI at the transmitter
+ SIMO Channel Capacity
+ MISO Channel Capacity
+ Capacity of Random MIMO Channels
- Ergodic vs. non-ergodic channels
- Ergodic capacity
> Examples, e.g., Rice, correlation
- Outage capacity

3.4 Capacity of the Frequency Selective MIMO channel
+ Space-Frequency Waterpouring

4 Transmission Techniques

4.1 Bit error probability
+ Binary signaling over Rayleigh fading channel

4.2 Diversity techniques for fading multipath channels
+ Frequency diversity
+ Time diversity
+ Space diversity
+ Post-processing techniques
- Selection combining, equal gain combining, maximum ratio combining, square-law combining

4.3 Approximation of the Probability of Symbol Error
+ Fading channel with D-fold diversity
+ Chernoff bound
+ Coding gain vs. diversity gain

5 Space-Time Processing

5.1 Receive antenna diversity (SIMO channel): MRC

5.2 Transmit antenna diversity
+ MISO channel unknown to the transmitter: Alamouti scheme (1998)
+ MISO channel known to the transmitter: MRT
+ MIMO channel unknown to the transmitter: Alamouti scheme (1998)
+ MIMO channel known to the transmitter: DET
+ Definiton of the effective diversity order
+ Summary: Diversity of space-time-frequency selective channels

5.3 Space-Time Coding without channel state information (CSI) at the transmitter
+ Space-Time Coding for frequency flat channels
+ Space-Time codeword design criteria
- definition of the pairwise error probability (PEP)
- rank criterion
- determinant criterion
+ Orthogonal Space-Time Block Codes (OSTBCs)
- OSTBCs for real-valued constellations
- OSTBCs for complex-valued constellations
+ Spatial Multiplexing (SM) as a Space-Time Code
+ Encoder Structures for Spatial Multiplexing (SM)
- horizontal encoding
- vertical encoding
- diagonal encoding (D-BLAST transmission)

5.4 Gains achievable with smart antennas
+ Array Gain
+ Diversity Gain
+ Spatial Multiplexing Gain
+ Interference Reduction Gain
- frequency reuse and cluster sizes

5.5 Multi-User MIMO Systems
+ Block Diagonalization

5.6 Multiple access schemes
+ OFDM
+ Single carrier vs. OFDM vs. spread spectrum

Skript, Overheadprojektor, Beamer Script, projector

• A. Goldsmith, Wireless Communications.
  Cambridge University Press, 2005.

   

• C. E. Shannon, A mathematical theory of communication.
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• G. Strang, Introduction to Linear Algebra.
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• G. Strang, Linear Algebra and Its Applications.
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• A. Paulraj, R. Nabar, and D. Gore, Introduction to Space-Time Wireless Communications.
  Cambridge University Press, 2003.

   

• A. Hottinen, O. Tirkkonen, and R. Wichman, Multi-antennas Transceiver Techniques for 3G and Beyond.
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• S. Haykin, Communication Systems.
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• S. Haykin and M. Moher, Modern Wireless Communications.
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• F. Jondral and A. Wiesler, Grundlagen der Wahrscheinlichkeitsrechnung und stochastischer Prozesse für Ingenieure.
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• A. Papoulis, Probability, Random Variables, and Stochastic Processes.
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• T. S. Rappaport, Wireless Communications.
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• J. Proakis, Digital Communications.
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• G. L. Stüber, Mobile Communication.
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• R. Steele and L. Hanzo, eds., Mobile Radio Communications.
  Wiley, 2nd edition, 1999.

   

• S. Saunders, Antennas and Propagation for Wireless Communication Systems.
  Wiley, 1999.

   

• A. Graham, Kronecker Products and Matrix Calculus with Applications.
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• E. G. Larson, P. Stoica, and G. Ganesan, Space-Time Block Coding for Wireless Communications.
  Cambridge University Press, 2003.

   

• H. Bölcskei, D. Gesbert, C. B. Papadias, and A.-J. van der Veen, eds., Space-Time Wireless Systems From Array Processing to MIMO Communications.
  Cambridge University Press, 2006.

   

• E. Biglieri, R. Calderbank, A. Constantinides, A. Goldsmith, A. Paulraj, and H. V. Poor, MIMO Wireless Communications.
  Cambridge University Press, 2007.

   

• C. Oestges and B. Clerckx, MIMO wireless communictions.
  Academic Press, 1 ed., 2007.

   

• Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, ``Zero-forcing methods for downlink spatial multiplexing in multi-user MIMO channels,'' IEEE Transactions on Signal Processing, vol. 52, pp. 461-471, Feb. 2004, received the 2009 Best Paper Award of the IEEE Signal Processing Society.

   

• Q. H. Spencer, C. B. Peel, A. L. Swindlehurst, and M. Haardt, ``An introduction to the multi-user MIMO downlink,'' IEEE Communications Magazine, pp. 60-67, Oct. 2004, special issue on MIMO Systems.