9th International Conference on Communications and Networking in China

Research Article

Linear Precoding in Large Scale MIMO under 3D Channel Model

  • @INPROCEEDINGS{10.4108/icst.chinacom.2014.256307,
        author={zheng hu and rongke liu and shaoli kang and xin su},
        title={Linear Precoding in Large Scale MIMO under 3D Channel Model},
        proceedings={9th International Conference on Communications and Networking in China},
        keywords={large scale mimo 2d antenna array 3d channel 3d-umi scenario mrt zf},
  • zheng hu
    rongke liu
    shaoli kang
    xin su
    Year: 2015
    Linear Precoding in Large Scale MIMO under 3D Channel Model
    DOI: 10.4108/icst.chinacom.2014.256307
zheng hu1, rongke liu1,*, shaoli kang2, xin su2
  • 1: School of Electronic and Information Engineering, Beihang University, Beijing, China
  • 2: State Key Laboratory of Wireless Mobile Communications, China Academy of Telecommunications Technology
*Contact email: rongke.liu@buaa.edu.cn


Large scale MIMO is a new field for wireless communication. Theoretical analysis was usually done with independent distributed complex Gaussian channels and unlimited antennas. In this work, we exhibit the performance of linear precoding under the three dimension (3D) channel model calibrated by 3GPP in the 3D-UMi scenario. Considering the multicell multiuser MIMO (MU-MIMO), we assume that the base station (BS) has perfect channel state information (CSI) due to the reciprocity of TDD system. The BS is equipped with two dimension (2D) antenna array and the transmitted signal will experiences 3D radio propagation. We compare two linear precoding, maximum ratio transmission (MRT) and zero forcing(ZF), when the number of antennas is 16, 32 64 and 128. Also the polynomial expansion linear detector (PELD) method here is leveraged. Simulation results show that under the 3D channel model, as the number of antennas goes larger, the performance of both linear precoding goes better. Due to the limited number of antennas and the 3D propagation channel model, the interbeam interferences deteriorate the performance of MRT. The performance of ZF is obviously better than MRT. Though the ZF precoding can eliminate the inter-beam interference, processing complexity is huge. The PELD precoding can achieve a suitable performance as a tradeoff between MRT and ZF.