Research On Modern Wireless Communication Technology Based On Beam

Millimeter wave and Massive MIMO are key technologies in the next generation of mobile communications.Millimeter wave is conducive to the integration of large-scale antenna panels because of its short wavelength,and Massive MIMO can provide a high directional beam through beamforming to compensate for the transmission loss of millimeter wave signals.Millimeter-wave Massive MIMO technology can effectively improve system capacity and energy efficiency.Therefore,mm Wave Massive MIMO has become a hotspot in communication field at home and abroad.When beamforming is used at both the base station and the user terminal,efficient beam management can significantly improve the performance of mm Wave Massive MIMO system.This thesis focuses on beam management techniques in mm Wave Massive MIMO systems.The main research work of the thesis is as follows:(1)To reduce the complexity of hybrid precoding design,a hybrid precoding scheme is proposed.First,the singular value decomposition of the array response matrix is used to abstract the angle information of the precoding matrix by using the eigenvectors corresponding to the larger eigenvalues in the right unitary matrix.In order to further improve the spectral efficiency,more vectors related to the optimal precoding matrix are introduced to expand the vector set.Then,the vector set is used to generate a hybrid precoding matrix.Finally,the simulation shows that the performance of the proposed algorithm is close to that of Orthogonal Matching Pursuit(OMP),but the complexity is lower.(2)To improve the accuracy of beam tracking,a beam training scheme is proposed.Compared with the existing work,each transmit-receive beam pair is only trained once,this thesis assumes that the same beam pair can be trained multiple times during the training process.First,the Markov stochastic transfer model is used to simulate the changing law of AoA/AoD.Then,based on the principle of maximizing the probability of successful tracking,the training beam sequence design problem is modeled as an integer nonlinear programming problem,and the branch and bound algorithm is used to solve the optimization problem,and then the best beam pair is selected.Finally,the algorithm is simulated,the results show that the beam tracking accuracy of the proposed algorithm is better than the average distribution algorithm,and it is better than the POMDP algorithm under small AoA/AoD changes.(3)To reduce the beam training overhead and the interference of multi-user beam selection,an out-of-band aided beam selection algorithm is proposed.First,the spatial information from the frequency band below 6GHz is extracted to assist the millimeter wave band in beam selection,this can save the resource overhead of the millimeter wave band.Then,multiple mobile terminals exchange beam selection information by using D2D communication to coordinate beam selection between mobile terminals which can solve the uplink multi-user co-beam interference problem.Finally,a simulation analysis is performed,and the simulation results show that the out-of-band aided coordination algorithm performs better than the uncoordinated algorithm.