Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

查看全文 作　　者：Rui Chen Jiandong Li Changle Li Wei [1]Liu

机构地区：[1]State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, P. R. China

出　　处：《Journal of Systems Engineering and Electronics》索引2012年第23卷第1期,共8页

基　　金：supported by the National Science Fund for Distinguished Young Scholars (60725105);the National Basic Research Program of China (2009CB320404);the Program for Changjiang Scholars and Innovative Research Team in University (IRT0852);the 111 Project(B08038);the National Natural Science Foundation of China (60702057);the Special Research Fund of State Key Laboratory (ISN1102003);the National Science and Technology Major Project (2011ZX03001-007-01) 摘　　要：The lattice-reduction (LR) has been developed to improve the performance of the zero-forcing (ZF) precoder in multiple input multiple output (MIMO) systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter (CSIT), an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex LenstraLenstra-Lova′sz (LLL) algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error (LMMSE) precoder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate (BER). Assuming a time division duplexing (TDD) MIMO system, correlated block flat fading channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying (QPSK) modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when E b / N0 is greater than 10 dB and 12 dB at all correlation coefficients. 关键词：MIMO信道 LMMSE 性能分析预编码晶格线性最小均方误差 MIMO系统资助

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Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

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