Linear transmit processing in MIMO communications systems

We examine and compare the different types of linear transmit processing for multiple input, multiple output systems, where we assume that the receive filter is independent of the transmit filter contrary to the joint optimization of transmit and receive filters. We can identify three filter types s...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2005-08, Vol.53 (8), p.2700-2712
Main Authors: Joham, M., Utschick, W., Nossek, J.A.
Format: Article
Language:English
Subjects:
Additive noise
Applied sciences
Closed-form solution
Communication systems
Constraint optimization
Convergence
Detection, estimation, filtering, equalization, prediction
Errors
Exact sciences and technology
Exact solutions
Information filtering
Information filters
Information, signal and communications theory
linear precoding
Linear transmit processing
Matched filters
Mathematical analysis
MIMO
multiple input
multiple output systems (MIMO)
Nonlinear filters
Optimization
pre-equalization
prerake
Signal and communications theory
Signal to noise ratio
Signal, noise
Simulation
Studies
Telecommunications and information theory
Wiener filter
Wiener filtering
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Summary:We examine and compare the different types of linear transmit processing for multiple input, multiple output systems, where we assume that the receive filter is independent of the transmit filter contrary to the joint optimization of transmit and receive filters. We can identify three filter types similar to receive processing: the transmit matched filter, the transmit zero-forcing filter, and the transmit Wiener filter. We show that the transmit filters are based on similar optimizations as the respective receive filters with an additional constraint for the transmit power. Moreover, the transmit Wiener filter has similar convergence properties as the receive Wiener filter, i.e., it converges to the matched filter and the zero-forcing filter for low and high signal-to-noise ratio, respectively. We give closed-form solutions for all transmit filters and present the fundamental result that their mean-square errors are equal to the errors of the respective receive filters, if the information symbols and the additive noise are uncorrelated. However, our simulations reveal that the bit-error ratio results of the transmit filters differ from the results for the respective receive filters.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2005.850331