On transmit antenna selection for multiuser MIMO systems with dirty paper coding
Manar Mohaisen,KyungHi Chang +1 more
- pp 3074-3078
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TLDR
Simulation results and analysis demonstrate that the proposed maxR algorithm requires only 1% of the computational efforts required by the optimal algorithm for a degradation of 1dB and 0.1dB in the case of linear zero-forcing and Tomlinson-Harashima precoding schemes, respectively.Abstract:
In this paper, we address the transmit antenna selection in multi-user MIMO systems with precoding. The optimum and reduced complexity sub-optimum antenna selection algorithms are introduced. QR-decomposition (QRD) based antenna selection is investigated and the reason behind its sub-optimality is analytically derived. We introduce the conventional QRD-based algorithm and propose an efficient QRD-based transmit antenna scheme (maxR) that is both implementation and performance efficient. Moreover, we derive explicit formulae for the computational complexities of the aforementioned algorithms. Simulation results and analysis demonstrate that the proposed maxR algorithm requires only 1% of the computational efforts required by the optimal algorithm for a degradation of 1dB and 0.1dB in the case of linear zero-forcing and Tomlinson-Harashima precoding schemes, respectively.read more
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References
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Writing on dirty paper (Corresp.)
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A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization
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Antenna selection in MIMO systems
S. Sanayei,Aria Nosratinia +1 more
TL;DR: Classic results on selection diversity, followed by a discussion of antenna selection algorithms at the transmit and receive sides, and extensions of classical results to antenna subset selection are presented.
Journal ArticleDOI
Matched-Transmission Technique for Channels With Intersymbol Interference
H. Harashima,H. Miyakawa +1 more
TL;DR: The performance of the MT technique is discussed from the view point of the output signal-to-noise ratio and the system is shown to attain asymptotically the bound performance predicted by the information theory.