MIMO Wireless Communications: From Real-World Propagation to by Claude Oestges

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By Claude Oestges

Uniquely, this e-book proposes strong space-time code designs for real-world instant channels. via a unified framework, it emphasizes how propagation mechanisms resembling space-time frequency correlations and coherent parts effect the MIMO approach functionality less than practical strength constraints. Combining a great mathematical research with a actual and intuitive method of space-time coding, the booklet gradually derives leading edge designs, considering that MIMO channels are usually faraway from ideal.

The a number of chapters of this ebook offer an important, whole and clean perception into the functionality behaviour of space-time codes in practical situations and represent an excellent resource of the most recent advancements in MIMO propagation and space-time coding for researchers, R&D engineers and graduate students.

Features include
• actual types and analytical representations of MIMO propagation channels, highlighting the strengths and weaknesses of varied models
• assessment of space-time coding options, masking either classical and more moderen schemes lower than details idea and mistake chance perspectives
• In-depth presentation of ways real-world propagation impacts the ability and the mistake functionality of MIMO transmission schemes
• cutting edge and useful designs of strong space-time coding, precoding and antenna choice options for life like propagation (including single-carrier and MIMO-OFDM transmissions)

"This ebook deals very important insights into how space-time coding could be adapted for real-world MIMO channels. The dialogue of MIMO propagation versions is usually intuitive and well-developed."
Arogyaswami J. Paulraj, Professor, Stanford collage, CA

"Finally a publication dedicated to MIMO from a brand new standpoint that bridges the limits among propagation, channel modeling, sign processing and space-time coding. it really is of excessive reference worth, combining intuitive and conceptual motives with specific, stringent derivations of easy evidence of MIMO."
Ernst Bonek, Emeritus Professor, Technische Universität Wien, Austria

* offers space-time coding options for real-world MIMO channels
* comprises new layout methodologies and standards that warrantly the robustness of space-time coding in genuine lifestyles instant communications applications
* Evaluates the functionality of space-time coding in genuine global stipulations

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Additional resources for MIMO Wireless Communications: From Real-World Propagation to Space-Time Code Design

Example text

Nnr ,k ]T is the sampled noise vector, containing the noise contribution at each receive antenna, such that the noise is white in both time and spatial dimensions, E nk nl∗ = σn2 Inr δ (k − l). From now on, we assume that the channel remains constant over a symbol duration, and drop the time index k for better legibility. It must be clear from the context that m and n designate antennas and not sampled time instants. Using the same channel normalization as above, we also have that the average squared Frobenius norm of H is equal to E H 2 F = nt nr .

Nnr ,k ]T is the sampled noise vector, containing the noise contribution at each receive antenna, such that the noise is white in both time and spatial dimensions, E nk nl∗ = σn2 Inr δ (k − l). From now on, we assume that the channel remains constant over a symbol duration, and drop the time index k for better legibility. It must be clear from the context that m and n designate antennas and not sampled time instants. Using the same channel normalization as above, we also have that the average squared Frobenius norm of H is equal to E H 2 F = nt nr .

If these multiple antennas are sufficiently spaced (say, by one wavelength), one might expect that the different diversity branches fade independently, provided that the physical channel shows favorable properties (see Chapter 2). Receive diversity may be implemented via two rather different combining methods: • selection combining: the combiner selects the branch with the highest SNR among the nr receive signals, which is then used for detection • gain combining: the signal used for detection is a linear combination of all branches, z = wT y, where w = [w1 , .

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