Joint MMSE Vector Precoding Based on GMD Method for MIMO Systems

01/2007; DOI: 10.1093/ietcom/e90-b.9.2617
Source: OAI

ABSTRACT We propose a geometric mean decomposition (GMD) based vector precoding (VP) for multiple input multiple output (MIMO) systems. Minimum mean square error (MMSE) criterion is used for the joint VP design. The application of GMD method eliminates the imbalance among subchannel gains and obtains a better perturbation vector than the conventional method. We then exploit the extended channel matrix for further performance improvement. Simulation results show the proposed schemes significantly outperform the existing VP schemes.

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    ABSTRACT: In this paper, we propose an advanced joint transceiver design for block-diagonal geometric-mean-decomposition (BD-GMD) based multiuser multiple-input-multiple-output (MIMO) systems. First, we use the lattice reduction (LR) method to design the BD-GMD-based advanced detection and precoding for an uplink and a downlink, respectively. Then, we exploit the vector perturbation (VP) technique to further improve the system performance of the multiuser downlink. To directly reduce the high complexity of VP by a sphere encoder, we provide an LR-based sphere encoder and LR-based approximations for perturbation symbols. Performance and complexity analyses are given to show the advantages of the proposed schemes. Particularly, the diversity-gain analysis shows some insights of the existing and proposed schemes. Simulation results verify the performance improvement as well as the theoretical analysis.
    IEEE Transactions on Vehicular Technology 03/2010; · 2.06 Impact Factor
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    ABSTRACT: The Geometric Mean Decomposition (GMD) for MIMO channel matrix can obtain identical subbchannel gains, which is a useful property to improve performance gains of precoding. In this paper, we combine the vector precoding with GMD for channel matrix to design the transceiver for MIMO transmission system. Under the proposed transceiver structure, the minimum square error (MSE) of receive symbols are obtained. To minimize the MSE, two schemes in terms of perturbation vector are proposed. In the first scheme, the perturbation vector has only continuous values, thus it is regarded as interference for MSE. In the second scheme, the perturbation vector is generalized to have both continuous and discrete values, so it is partially dealt with as interference after modulo operation. In these two schemes, the optimum perturbation vectors are presented in MMSE criterion respectively.
    Neural Networks and Signal Processing, 2008 International Conference on; 07/2008
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    ABSTRACT: Uniform channel decomposition (UCD), as an improvement of geometric mean decomposition (GMD), is capable of decomposing a multiple-input-multiple-output (MIMO) channel into multiple subchannels having an identical capacity. Vector precoding (VP) is a powerful scheme, which is capable of mitigating multiuser interference (MUI) at the transmitter, provided that the channels of the users are known. In this paper, a novel joint transceiver design based on the UCD and the minimum bit error rate (MBER) VP principles is proposed for MIMO systems, in which the precoding and equalization matrices are calculated by UCD, whereas the perturbation vector is chosen to minimize the system's bit error ratio (BER). This UCD-MBER-VP transceiver design outperforms several state-of-the-art benchmark algorithms in terms of achievable BER performance without imposing an increased computational complexity, particularly for rank-deficient systems.
    IEEE Transactions on Vehicular Technology 08/2010; · 2.06 Impact Factor

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