Research On Beamforming Technology Under Massive MIMO

This thesis investigates the beamforming technology in Massive Multiple Input Multiple Output(Massive MIMO)based on the transmission protocol of the 5G physical layer.A link-level simulation platform is first built based on the 5G New Radio(NR)protocol to provide the simulation and verification platform for the following research work.The thesis then analyzes and studies the precoding schemes,channel estimation process,power control and equalization algorithms as well as the corresponding theoretical analysis and simulation under the so called antenna selective scenario in 5G system,where the base station can obtain full channel state information(CSI)by receiving uplink sounding reference signals from all antennas at the mobile stations,.At last,we considers the so called antenna non-selective scenario indicating that the mobile stations transmit the uplink sounding signals with just one antenna or a few antennas to the base station,causing the base station unable to obtain the full downlink CSI for precoding.The performance and system capacity for antenna non-selective scenario has a dramatic loss compared with antenna selection scenario,therefore a series of enhanced algorithms have been proposed in this thesis.Firstly,the pre-coding algorithm of multi-user MIMO(MU-MIMO)in the antenna selective scenario is studied and simulated based on the previous 5G NR link-level simulation platform.Based on the traditional zero forcing(ZF)precoding algorithm,a low complexity ZF utilizing only partial CSI to do precoding,termed as partial ZF(PZF)is proposed,and its theoretical performance gain and computational complexity are also presented.Then,this thesis analyzes the power control scheme in the antenna selective scenario,developing a power control scheme to minimize the bit error rate(BER)based on water-filling algorithm and comparing it with other power contol schemes with simulation.Secondly,this thesis proposes a two layer codebook assisted precoding structure with an outer layer and an inner layer precoding respectively for antenna non-selective scenario.The outer layer precoding adopts DFT codebook,and the inner layer precoding adopts Type ? codebook.Accordingly,a new sub-array partition mothod is proposed for dividing the antenna arrays for the outer layer,which improves the performance of the system with full bandwidth precoding.Finally,considering the large performance loss problem under antenna non-selective scenerio,the code book assisted reconstructive precoding scheme with the proposed partial zero-forcing based on limited sounding information is proposed,named SFR-PZF..Afterwards,an interference measurment assisted scheme is developed for SFR-PZF to improve its performance under heavy interference scenarios.Besides,For the selection of terminal precoding matrix indicator(PMI),a selection algorithm based on singular value decomposition is proposed.This paper at last studies the user scheduling and power control enhancing scheme under antenna non-selective scenerios,presenting a series of improved schemes to achieve 80% of the throughput under antenna selective scenarios.