In this paper, we study the low-complexity channel reconstruction methods for downlink precoding in massive multiple-Input multiple-Output(MIMO) systems. When the user is allocated less streams than the number of its ...In this paper, we study the low-complexity channel reconstruction methods for downlink precoding in massive multiple-Input multiple-Output(MIMO) systems. When the user is allocated less streams than the number of its antennas, the base station(BS) or user usually utilizes the singular value decomposition(SVD) to get the effective channels, whose dimension is equal to the number of streams. This process is called channel reconstruction and done in BS for time division duplex(TDD) mode. However, with the increasing of antennas in BS, the computation burden of SVD is getting incredible. Here, we propose a series of novel low-complexity channel reconstruction methods for downlink precoding in 3D spatial channel model. We consider different correlations between elevation and azimuth antennas, and divide the large dimensional matrix SVD into two kinds of small-size matrix SVD. The simulation results show that the proposed methods only produce less than 10% float computation than the traditional SVD zero-forcing(SVD-ZF) precoding method, while keeping nearly the same performance of 1Gbps.展开更多
基金supported by the National High Technology Research and Development Program of China(863 Program)(Grant No.2014AA01A705)National Science and Technology Major Project of China(Grant No.2015ZX03001034)
文摘In this paper, we study the low-complexity channel reconstruction methods for downlink precoding in massive multiple-Input multiple-Output(MIMO) systems. When the user is allocated less streams than the number of its antennas, the base station(BS) or user usually utilizes the singular value decomposition(SVD) to get the effective channels, whose dimension is equal to the number of streams. This process is called channel reconstruction and done in BS for time division duplex(TDD) mode. However, with the increasing of antennas in BS, the computation burden of SVD is getting incredible. Here, we propose a series of novel low-complexity channel reconstruction methods for downlink precoding in 3D spatial channel model. We consider different correlations between elevation and azimuth antennas, and divide the large dimensional matrix SVD into two kinds of small-size matrix SVD. The simulation results show that the proposed methods only produce less than 10% float computation than the traditional SVD zero-forcing(SVD-ZF) precoding method, while keeping nearly the same performance of 1Gbps.
