Research On Millimeter Wave Massive MIMO Beamforming In High Speed Rail Communication

High-speed rail communication is an important part of traffic communications.With the development of wireless communication and the improvement of passenger demand,the quality of high-speed rail communication needs to be significantly improved.High-speed rail communication is mainly divided into two parts:vehicle-to-ground communication and in-vehicle communication.Vehicle-to-ground communication and in-vehicle communication are also divided into uplink and downlink transmission.This article focuses on the downlink transmission part of the vehicle-to-ground communication.Millimeter wave has high frequency and short wavelength,which can significantly improve the data transmission rate.It is the research focus of next generation wireless communication.Millimeter wave communication can reduce the size of the antenna and facilitate the use of large-scale antenna technology.Large-scale multi-input and multi-output(MIMO)can reduce the loss of millimeter waves due to long-distance transmission.In particular,beamforming technology can increase the coverage of edge signals,improve overall throughput,and suppress interference.Therefore,the combination of millimeter wave communication and large-scale MIMO beamforming can significantly improve the system performance of wireless communication,thus providing strong support for the development of next-generation high-speed rail communication technology.In this paper,millimeter-wave massive MIMO communication and the special scenes of high-speed rail are combined,and the beamforming technology is mainly studied.The main contents and results of this paper are as follows:(1)Combining the traditional MIMO beamforming method,a beamforming method based on direction of arrival(DOA)is analyzed.The beamforming methods such as optimal beamforming,traditional beamforming,and beamforming based on DOA are compared by simulation.It is found that high-speed rail is better suited to beamforming based on DOA position.method.(2)The single and dual beam switching beamforming method is analyzed.The switching points of the beam switching are obtained by four aspects of beam width,angle of arrival difference,interference coefficient and signal-to-noise ratio.And the simulation compares the spectral efficiency of single-dual beam switching beamforming and single-and dual-beam beamforming methods,and finds that the former can improve the spectrum efficiency.(3)Based on the DOA beamforming method,the angle estimation error is considered.The spectral efficiency formula of beamforming considering angle error is re-derived.The simulation compares the spectral efficiency with angular error and angle estimation accuracy,and the spectral efficiency when the angle error takes different values.The results show that the speetral efficiency with angular error is lower than the ideal spectral efficiency of high-speed rail communication,but the result is closer to reality.(4)Under the principle of ensuring the average power is constant,the power regulation mechanism is introduced at the transmitting end,and the spectral efficiency expression is re-derived.The simulation results show that the path loss caused by the increase of distance can be offset by controlling the power of the transmitting end,so that the signal transmission rate of the train is unchanged during the running,and keep the passenger's communication stable.(5)The high-speed rail uses a distributed massive MIMO antenna array model to simulate the spectral efficiency of single beam beamforming,dual beam beamforming,full beam beamforming and adaptive beamforming.Simulation results show that the spectral efficiency can be improved by using adaptive beamforming.Then,the spectrum efficiency and the optimum beam number of the adaptive beamforming system are simulated and analyzed when the distance and the number of base station antennas are different.(6)This paper improves the adaptive beamforming algorithm.By combining the idea of iteration with the traditional beamforming algorithm,the computational complexity is reduced.By combining the actual demand of users with antenna selection algorithm,resources are saved.