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arXiv · 1401.1381

Reduced-complexity maximum-likelihood decoding for 3D MIMO code

Ming Liu·Jean-François Hélard·Matthieu Crussière·Maryline Hélard
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Abstract

The 3D MIMO code is a robust and efficient space-time coding scheme for the distributed MIMO broadcasting. However, it suffers from the high computational complexity if the optimal maximum-likelihood (ML) decoding is used. In this paper we first investigate the unique properties of the 3D MIMO code and consequently propose a simplified decoding algorithm without sacrificing the ML optimality. Analysis shows that the decoding complexity is reduced from O(M^8) to O(M^{4.5}) in quasi-static channels when M-ary square QAM constellation is used. Moreover, we propose an efficient implementation of the simplified ML decoder which achieves a much lower decoding time delay compared to the classical sphere decoder with Schnorr-Euchner enumeration.

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Ming Liu, Jean-François Hélard, Matthieu Crussière, Maryline Hélard. 2014-01-07. Reduced-complexity maximum-likelihood decoding for 3D MIMO code. https://doi.org/10.1109/wcnc.2013.6555219

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