By Bruno Clerckx
This booklet is exclusive in proposing channels, thoughts and criteria for the following iteration of MIMO instant networks. via a unified framework, it emphasizes how propagation mechanisms influence the approach functionality lower than real looking energy constraints. Combining an outstanding mathematical research with a actual and intuitive method of space-time sign processing, the booklet gradually derives leading edge designs for space-time coding and precoding in addition to multi-user and multi-cell recommendations, bearing in mind that MIMO channels are usually faraway from perfect. Reflecting advancements because the first version was once released, this e-book has been completely revised, and now contains new sections and 5 new chapters, respectively facing receiver layout, multi-user MIMO, multi-cell MIMO, MIMO implementation in criteria, and MIMO system-level evaluation.
- Extended creation to multi-dimensional propagation, together with polarization aspects
- Detailed and comparative description of actual types and analytical representations of unmarried- and multi-link MIMO channels, overlaying the most recent standardized models
- Thorough review of space-time coding innovations, protecting either classical and newer schemes below info idea and mistake chance perspectives
- Intuitive representation of the way real-world propagation impacts the skill and the mistake functionality of MIMO transmission schemes
- Detailed info theoretic research of a number of entry, broadcast and interference channels
- In-depth presentation of multi-user variety, source allocation and (non-)linear MU-MIMO precoding options with ideal and imperfect channel knowledge
- Extensive assurance of cooperative multi-cell MIMO-OFDMA networks, together with community source allocation optimization, coordinated scheduling, beamforming and gear regulate, interference alignment, joint processing, significant and community MIMO
- Applications of MIMO and Coordinated Multi-Point (CoMP) in LTE, LTE-A and WiMAX
- Theoretical derivations and effects contrasted with useful procedure point reviews highlighting the functionality of unmarried- and multi-cell MIMO ideas in real looking deployments
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Extra info for Mimo Wireless Networks. Channels, Techniques and Standards for Multi-Antenna, Multi-User and Multi-Cell Systems
Matched beamforming may also be combined with a selection algorithm, analogous to the generalized selection algorithm described above for SIMO systems. The transmitter selects n t antennas out of n t to be used in the beamformer. Quite naturally, this technique achieves a full diversity gain of n t , but a reduced transmit array gain. 3 Null-Steering and Optimal Beamforming We have seen that matched beamforming maximizes the SNR in AWGN channels. Yet, in the presence of co-channel interference, matched beamforming is not optimal anymore.
38) where n = h H n. This scheme is known as maximal ratio combining (MRC), for the reason that it maximizes the average output SNR ρ¯out . The average SNR is indeed equal to ρ¯out = Es E σn2 = ρE h h 4 h 2 2 = ρnr . 39) It is interesting to note that the last equality holds true irrespective of the correlation between the different h n . In MRC diversity schemes, the array gain ga is thus always equal to nr , or equivalently, the output SNR is the sum of the SNR levels of all branches. As far as the MRC diversity gain is concerned, let us first consider the case of BPSK transmission.
6 Multiple-Input Multiple-Output systems 21 Dominant Eigenmode Transmission with Antenna Selection The dominant eigenmode transmission introduced above may be generalized to include a selection algorithm at either the transmitter or the receiver. We focus in the following on transmit selection, but all considerations remain valid if the receiver performs the selection (remember that both the transmitter and the receiver have a perfect channel knowledge). The dominant eigenmode transmission with antenna selection [MWCW05] works as follows.