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mmse vector precoding with joint transmitter and receiver design for MIMO systems

SIGNAL PROCESSING 2007年第11期87卷 2823-2833页

作者： Liu, Feng Jiang, Lingge He, Chen Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

The transmitter side (Tx) vector precoding (VP) shows excellent performance. However, joint transmitter and receiver (Tx-Rx) design might achieve further improvement. In this paper, we propose a novel joint Tx-Rx VP for multiple input multiple output (MIMO) systems. A unitary matrix is used at the receiver to partially equalize the channel. We design the joint Tx-Rx VP with the minimum mean square error (mmse) criterion and deduce the general closed-form solution. Then we apply several methods including the singular value decomposition, QR decomposition and geometric mean decomposition (GMD) to specify the general joint Tx-Rx VP design. Moreover, by using the extended channel, we achieve an improved scheme to obtain further performance gain. Simulation results show that the specification with GMD method outperforms the other specifications and the Tx mmse VP. The improved joint Tx-Rx mmse VP with GMD is superior to other mmse VP schemes. (c) 2007 Elsevier B.V. All rights reserved.

关键词： MIMO systems mmse vector precoding joint transmitter and receiver design geometric mean decomposition

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A mmse vector precoding with Block Diagonalization for Multiuser MIMO Downlink

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IEEE TRANSACTIONS ON COMMUNICATIONS 2012年第2期60卷 569-577页

作者： Park, Jungyong Lee, Byungju Shim, Byonghyo Korea Univ Sch Informat & Commun Seoul 136713 South Korea

Block diagonalization (BD) algorithm is a generalization of the channel inversion that converts multiuser multi-input multi-output (MIMO) broadcast channel into single-user MIMO channel without inter-user interference. In this paper, we combine the BD technique with a minimum mean square error vector precoding (mmse-VP) for achieving further gain in performance with minimal computational overhead. Two key ingredients to make our approach effective are the QR decomposition based block diagonalization and joint optimization of transmitter and receiver parameters in the mmse sense. In fact, by optimizing precoded signal vector and perturbation vector in the transmitter and receiver jointly, we pursue an optimal balance between the residual interference mitigation and the noise enhancement suppression. From the sum rate analysis as well as the bit error rate simulations (both uncoded and coded cases) in realistic multiuser MIMO downlink, we show that the proposed BD-MVP brings substantial performance gain over existing multiuser MIMO algorithms.

关键词： Multiuser MIMO block diagonalization QR decomposition mmse vector precoding Cholesky factorization

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Low complexity mmse vector precoding using lattice reduction for MIMO systems

Low complexity MMSE vector precoding using lattice reduction...

引用

IEEE International Conference on Communications (ICC 2007)

作者： Liu, Feng Jiang, Lingge He, Chen Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9781424403523

In this paper, a lattice-reduction-aided (LRA) minimum mean square error (mmse) vector precoding (VP) is proposed for multiple input multiple output (MIMO) systems. Three schemes are provided for the perturbation vector design by Babai's approximation procedures based on lattice reduction method to reduce the complexity. Performance and complexity analysis are provided. Simulation results show that the proposed schemes significantly outperform the conventional mmse Tomlinson-Harashima precoding (THP) and the zero forcing (ZF) VP. Compared with the mmse VP via closest-point search, our LRA approach provides a simple alternative with little performance loss.

关键词： mmse vector precoding lattice reduction MIMO systems

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