Suboptimal Algorithm of MLD Using Gradient Signal Search in Direction of Noise Enhancement for MIMO Channels

Thet Htun KHINE; Kazuhiko FUKAWA; Hiroshi SUZUKI

doi:10.1093/ietcom/e90-b.6.1424

Suboptimal Algorithm of MLD Using Gradient Signal Search in Direction of Noise Enhancement for MIMO Channels

Thet Htun KHINE, Kazuhiko FUKAWA, Hiroshi SUZUKI

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This paper proposes a suboptimal algorithm for the maximum likelihood detection (MLD) in multiple-input multiple-output (MIMO) communications. The proposed algorithm regards transmitted signals as continuous variables in the same way as a common method for the discrete optimization problem, and then searches for candidates of the transmitted signals in the direction of a modified gradient vector of the metric. The vector is almost proportional to the direction of the noise enhancement, from which zero-forcing (ZF) or minimum mean square error (MMSE) algorithms suffer. This method sets the initial guess to the solution by ZF or MMSE algorithms, which can be recursively calculated. Also, the proposed algorithm has the same complexity order as that of conventional suboptimal algorithms. Computer simulations demonstrate that it is much superior in BER performance to the conventional ones.

Publication: IEICE TRANSACTIONS on Communications Vol.E90-B No.6 pp.1424-1432

Publication Date: 2007/06/01

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Online ISSN: 1745-1345

DOI: 10.1093/ietcom/e90-b.6.1424

Type of Manuscript: PAPER

Category: Wireless Communication Technologies

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Thet Htun KHINE, Kazuhiko FUKAWA, Hiroshi SUZUKI, "Suboptimal Algorithm of MLD Using Gradient Signal Search in Direction of Noise Enhancement for MIMO Channels" in IEICE TRANSACTIONS on Communications, vol. E90-B, no. 6, pp. 1424-1432, June 2007, doi: 10.1093/ietcom/e90-b.6.1424.
Abstract: This paper proposes a suboptimal algorithm for the maximum likelihood detection (MLD) in multiple-input multiple-output (MIMO) communications. The proposed algorithm regards transmitted signals as continuous variables in the same way as a common method for the discrete optimization problem, and then searches for candidates of the transmitted signals in the direction of a modified gradient vector of the metric. The vector is almost proportional to the direction of the noise enhancement, from which zero-forcing (ZF) or minimum mean square error (MMSE) algorithms suffer. This method sets the initial guess to the solution by ZF or MMSE algorithms, which can be recursively calculated. Also, the proposed algorithm has the same complexity order as that of conventional suboptimal algorithms. Computer simulations demonstrate that it is much superior in BER performance to the conventional ones.
URL: https://globals.ieice.org/en_transactions/communications/10.1093/ietcom/e90-b.6.1424/_p

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@ARTICLE{e90-b_6_1424,
author={Thet Htun KHINE, Kazuhiko FUKAWA, Hiroshi SUZUKI, },
journal={IEICE TRANSACTIONS on Communications},
title={Suboptimal Algorithm of MLD Using Gradient Signal Search in Direction of Noise Enhancement for MIMO Channels},
year={2007},
volume={E90-B},
number={6},
pages={1424-1432},
abstract={This paper proposes a suboptimal algorithm for the maximum likelihood detection (MLD) in multiple-input multiple-output (MIMO) communications. The proposed algorithm regards transmitted signals as continuous variables in the same way as a common method for the discrete optimization problem, and then searches for candidates of the transmitted signals in the direction of a modified gradient vector of the metric. The vector is almost proportional to the direction of the noise enhancement, from which zero-forcing (ZF) or minimum mean square error (MMSE) algorithms suffer. This method sets the initial guess to the solution by ZF or MMSE algorithms, which can be recursively calculated. Also, the proposed algorithm has the same complexity order as that of conventional suboptimal algorithms. Computer simulations demonstrate that it is much superior in BER performance to the conventional ones.},
keywords={},
doi={10.1093/ietcom/e90-b.6.1424},
ISSN={1745-1345},
month={June},}

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TY - JOUR
TI - Suboptimal Algorithm of MLD Using Gradient Signal Search in Direction of Noise Enhancement for MIMO Channels
T2 - IEICE TRANSACTIONS on Communications
SP - 1424
EP - 1432
AU - Thet Htun KHINE
AU - Kazuhiko FUKAWA
AU - Hiroshi SUZUKI
PY - 2007
DO - 10.1093/ietcom/e90-b.6.1424
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E90-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2007
AB - This paper proposes a suboptimal algorithm for the maximum likelihood detection (MLD) in multiple-input multiple-output (MIMO) communications. The proposed algorithm regards transmitted signals as continuous variables in the same way as a common method for the discrete optimization problem, and then searches for candidates of the transmitted signals in the direction of a modified gradient vector of the metric. The vector is almost proportional to the direction of the noise enhancement, from which zero-forcing (ZF) or minimum mean square error (MMSE) algorithms suffer. This method sets the initial guess to the solution by ZF or MMSE algorithms, which can be recursively calculated. Also, the proposed algorithm has the same complexity order as that of conventional suboptimal algorithms. Computer simulations demonstrate that it is much superior in BER performance to the conventional ones.
ER -