Maximum-Likelihood Precoder Selection for ML Detector in MIMO-OFDM Systems

Sung-Yoon JUNG  Jong-Ho LEE  Daeyoung PARK  

IEICE TRANSACTIONS on Communications   Vol.E95-B    No.5    pp.1856-1859
Publication Date: 2012/05/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E95.B.1856
Print ISSN: 0916-8516
Type of Manuscript: LETTER
Category: Wireless Communication Technologies
MIMO,  OFDM,  precoding,  precoder selection,  ML detector,  

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Spatial Multiplexing with precoding provides an opportunity to enhance the capacity and reliability of multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. However, precoder selection may require knowledeg of all subcarriers, which may cause a large amount of feedback if not properly designed. In addition, if the maximum-likelihood (ML) detector is employed, the conventional precoder selection that maximizes the minimum stream SNR is not optimal in terms of the error probability. In this paper, we propose to reduce the feedback overhead by introducing a ML clustering concept in selecting the optimal precoder for ML detector. Numerical results show that the proposed precoder selection based on the ML clustering provides enhanced performance for ML receiver compared with conventional interpolation and clustering algorithms.