3D Beam Forming And Beam Tracking Based On Millimeter Wave Massive Mimo Systems

Millimeter-wave communication currently becomes a hotspot of sciantific research due to the explosive growth of wireless communication data traffic and the increaing demand on telecomunications services.Milimeter-waves are accompanied with serious propagation loss during transmission.To solve this problem,it's necessary to form a more refined beam by means of joint transceiver beamforming,to provide a larger antenna array gain.On the one hand,a more refined communication beam increases the complexity of beam searching,which will further increase the delay of beam alignment during the initial signal access.On the other hand,dynamic factors may impact the directional transmission link,which leads to the instability or even total interruption of the established communicaiton link.Regarding to the problems above,this thesis focuses on the beam forming and beam tracking technology in millimeter-wave massive MIMO system.Firstly,to address the problem of high complexity and low success rate of the fast beam searching,a fast beam search scheme based on beam overlapping in a 3D MIMO scenario is designed,which divides the search interval into Q subintervals(where Q is an integer power of 2)and uses Gray mapping to code the subinterval number of each stage.Each bit of the subinterval corresponds to the coverage range of a training beam,and a total of log2 Q 3D training beams are generated accordingly.Fast beam seaching is then performed based on these training beams.In the 3D MIMO scenario,the designed search scheme not only reduces the search complexity significantly compared with the existing algorithms,which is only 50%of the search complexity of binary search algorithm,but also achieves a higher search success rate of 95%.Secondly,directional beam communication is easily affected by the changing environment and other dynamic factors,leading to the interruption of the original communication link.In order to improve the anti-interference capability and solve the problem of beam misalignment,this thesis first introduces a system anti-interference factor to improve the prediction and observation covariance matrix in the Unscented Particle Filter(UPF)algorithm.Next,in order to solve the problem of particle diversity loss due to the particle resampling in the UPF,an Adaptive Genetic Algorithm(AGA)is introduced,which optimizes the performance of the particle swarm and improves the estimation accuracy of the algorithm while preserving the particle diversiry.Finally,the Adaptive Genetic Algorithm-Unscented Particle Filter(AGA-UPF)algorithm is applied to the millimeter-wave system to implement beam tracking.The simulation results show that when the SNR is 20dB and above,the effective tracking time of the algorithm can reach 100 time slots;compared with the UPF algorithm,the estimation error of the AGA-UPF algorithm is reduced by about 8%;Compared with the PF and UKF algorithms,the estimation error is reduced by approximately 15%and 20%.The AGA-UPF algorithm can maintain high tracking accuracy and low estimation error in millimeter-wave communication systems with large variations.