Authors:
Andreas Ahrens
1
;
Francisco Cano-Broncano
2
and
César Benavente-Peces
2
Affiliations:
1
University of Technology Business and Design, Germany
;
2
Universidad Politécnica de Madrid, Spain
Keyword(s):
Multiple-input Multiple-output System, Singular-value Decomposition, Geometric Mean Decomposition, Bit Allocation, Power Allocation, Antennas Correlation,Wireless Transmission, Tomlinson-harashima Precoding.
Related
Ontology
Subjects/Areas/Topics:
Channel Coding, Modulation and Multi-User Detection
;
Detection, Decoding and Diversity Techniques
;
MIMO Systems and Techniques
;
Telecommunications
;
Wireless Information Networks and Systems
Abstract:
Singular-value decomposition (SVD)-based multiple-input multiple output (MIMO) systems, where the whole MIMO channel is decomposed into a number of unequally weighted single-input single-output (SISO) channels, have attracted a lot of attention in the wireless community. The unequal weighting of the SISO channels has led to intensive research on bit- and power allocation even in MIMO channel situation with poor scattering conditions identified as the antennas correlation effect. In this situation, the unequal weighting of the SISO channels becomes even much stronger. In comparison to the SVD-assisted MIMO transmission, geometric mean decomposition (GMD)-based MIMO systems are able to compensate the drawback of weighted SISO channels when using SVD, where the decomposition result is nearly independent of the antennas correlation effect. The remaining interferences after the GMD-based signal processing can be easily removed by using dirty paper precoding as demonstrated in this work. O
ur results show that GMD-based MIMO transmission has the potential to significantly simplify the bit and power loading processes and outperforms the SVD-based MIMO transmission as long as the same QAM-constellation size is used on all equally-weighted SISO channels.
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