Reduced-complexity maximum-likelihood decoding for 3D MIMO code
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.
Keywords
Cite
@article{arxiv.1401.1381,
title = {Reduced-complexity maximum-likelihood decoding for 3D MIMO code},
author = {Ming Liu and Jean-François Hélard and Matthieu Crussière and Maryline Hélard},
journal= {arXiv preprint arXiv:1401.1381},
year = {2014}
}
Comments
IEEE Wireless Communications and Networking Conference (WCNC 2013), Shanghai : China (2013)