Research On Massive MIMO Beamforming In LOS

In recent years,with the rapid development of wireless communication technology,mankind has entered an era of the Internet of everything.With the rise of various intelligent terminals,the demand for wireless data has reached an unprecedented height,which has brought huge challenges to current fourth-generation communication system(4G).As one of the key technologies of the fifth generation communication system(5G),Massive Multiple Input Multiple Output(Massive MIMO)technology has great potential to meet the explosive demand of data.In a massive MIMO wireless communication system,a large number of antennas are installed in a base station,and the huge number of antennas forms a beam with stronger directivity and a narrower width,which significantly improves the signal power received by users.In addition,the large-scale antenna provides a huge degree of freedom in space,enabling more users to reuse the same time-frequency resources to communicate with the base station,which greatly improves the spectrum utilization.Currently,in order to improve the performance of massive MIMO systems,beamforming algorithms have become the focus of research in the industry.Therefore,this article will focus on the research of single-user and multi-user beamforming algorithms for massive MIMO systems in LOS scenarios.The specific works are as follows:1.The beamforming algorithms of massive MIMO single-user system are studied.First,the traditional single-user beamforming algorithms are introduced from two aspects,including the beamforming algorithms based on angle information and the beamforming algorithms based on channel information.The advantages and disadvantages of various algorithms are analyzed and compared in detail.Then,aiming at the drawback that the traditional beamforming algorithms can not form the maximum beam gain at the target user in LOS scenario,two improved single-user beamforming algorithms are proposed.From the aspect of user channel information,this thesis extracts the main path channel information of users and uses EBB algorithm to calculate the beamforming vector.From the aspect of angle information,this thesis constructs a corresponding convex optimization problem to solve the beamforming vector by maximizing the beam gain of the target user.Finally,the above algorithms are simulated and compared by MATLAB software.The results show that the two improved algorithms proposed in this thesis effectively improve the performance of a single-user system.2.The beamforming algorithms for massive MIMO multi-user system are studied.Firstly,the common multi-user beamforming algorithms are introduced,their derivation processes are introduced in detail,and their advantages and disadvantages are analyzed and compared.It is found that the traditional multi-user beamforming algorithms not only can suppress the interference between users,but also sacrifice too much beam gain of target users.Aiming at this shortcoming,an improved multi-user beamforming algorithm is proposed,whose main idea is to suppress the interference between users while ensuring the gain of the target users.The algorithm is divided into two steps: the first step is to extract the main path information,and the EBB algorithm is used to calculate the initial weight to obtain the initial beam.In the second step,the beam gain outside the range of the beam main lobe is reduced to obtain the target beam.Meanwhile,the gain of the main lobe is constrained,and the convex optimization problem is constructed to solve the optimal beamforming vector.Finally,the simulation results on the MATLAB platform show that the improved algorithm proposed in this thesis improves the performance of the multi-user system.