Research On Beamforming Method In Massive MIMO

Massive MIMO is one of the most promising key technologies in the fifth generation of mobile communication systems. Compared to the traditional multiple input multiple output(MIMO), it has many advantages, such as high transfer rate, energy efficiency and spectral efficiency, and it has become a hotspot of the field of wireless communications. To achieve the high energy efficiency and spectral efficiency of Massive MIMO, it is very critical that the BSs use the appropriate beamforming algorithm. At present, most of the researches on Massive MIMO are focused on the perfect channel state information(CSI), the receiving end has single antenna, and the delay, the quantization error and other factors are not considered, then designing of beamforming method at BS. Due to the smart terminal with multiple antennas is more and more, and the number of antennas at the user is gradually increasing, so this design will affect the robustness of the system.The issue of Massive MIMO to expand research, the main research contents as follows:First of all, through researching the common channel models such as SCM(Spatial Channel Model), WINNER(Wireless World Initiative New Radio) II channel model, this paper presents simulation environment of Massive MIMO, it provides the fundamental guarantee for the performance analysis of Massive MIMO system and implementation and algorithm optimization of beamforming.Secondly, under the building simulation environment, considering single cell multiple users, using block diagonalization(BD) precoding algorithm to analyze the energy efficiency of downlink Massive MIMO, and deducing the closed expression of the system energy efficiency and spectral efficiency, the relationship between the energy efficiency and the radius of cell, the transmitting antenna number of BSs, through simulation validates that setting appropriate spectral efficiency, increasing the number of transmit antennas of BS, as well as reducing the cell radius can enhance the energy efficiency of the system.Finally, under the building simulation environment, due to multi-cell coordination scenario, on the basic of analyzing the influence of quantitation error and transmission overhead delay on the system capacity, considering estimation error, quantization error and delay, using transmitter and receiver interference alignment technology and minimum mean square error criterion, then the beamforming matrix of transmitter makes multiple interference of transmitter overlap at the receiver, receiving matrix is used to deal with interference. The results of computer simulation verify that compared with traditional MIMO system, energy efficiency of using beamforming algorithm was improved, reliability and effectiveness of the system obtained further promotion.