Reserch On Millimeter Wave Beam Management Technology In High Dynamic Scenario

Millimeter wave communication technology relieves the pressure of existing communication bandwidth,while massive MIMO and beamforming technology can compensate the high path loss of millimeter wave and effectively improve the spectral efficiency of communication.Therefore,the combination of millimeter-wave and massive MIMO becomes the key technology of 5G.However,in the high dynamic scenario,the rapid movement of the terminal leads to the acceleration of channel changes.In order to ensure the link quality of the communication,frequent beam switching is needed.How to achieve fast beam alignment with low overhead has become an urgent problem.At the same time,the application of ultra-dense network(UDN)improves the system capacity,but the reduction of cell radius further increases the frequency of beam alignment and the overhead of beam training.In order to meet the above challenges,this paper focuses on the fast and efficient beam alignment technology in high dynamic scenarios,especially for UDN architecture.Firstly,in order to achieve fast and effective beam alignment in high dynamic scenario,this chapter defines a new parameter to measure the time-varying characteristics of the channel,which is called beam coherence time.It is used to measure the influence for the change of the angle of arrival on the received signal quality when the beam direction is offset.Then the relationship between the beam coherence time and the terminal moving speed,moving direction,beam width and other factors is clarified.Subsequently,the closed-form expression of the beam-steering codebook base beam coherence time is derived.The simulation results show that beam realignment in every beam coherence time reduces the training overhead of beam sweeping and improves the effective spectrum efficiency of the system.Secondly,in order to solve the problem of high beam training overhead caused by terminal movement in UDN,a multi-site coordinated beam tracking scheme is proposed.The scenario is a hyper-cellular network(HCN)with one control-BS(CBS)and multiple traffic-BSs(TBSs).The proposed sscheme consists of two stages.In the first stage,more accurate position measurement of the moving user equipment(UE)can be achieved by using uniform planar array(UPA),and Extended Kalman Filter(EKF)is exploited in CBS to predict the UE's location in the next slot.In the second stage,the relationship between multi-site and UE's location is used by the CBS to remotely infer the candidate beam between each TBS and the UE,and make a TBS handover decision when necessary.Given that it is the CBS in charge of beam tracking between all the TBSs and the UE centrally,the overhead for beam training and handover are both efficiently reduced.Simulation results based on realistic 3D scenario show that the proposed scheme can achieve 99%of the optimal spectral efficiency with fewer overhead for beam sweeping and handover signaling.Finally,in order to solve the problem of multi-site cooperated beam alignment without the light-of-sight,a long short term memory(LSTM)based multi-site cooperated beam alignment algorithm is proposed,the architecture is divided into two parts,which are encoder and decoder,and the attention mechanism is utilized to achieve effective information extraction in the model.In the network training stage,the LSTM network is trained according to the signal power and beam index of the base station and the terminal in the previous period;in the beam prediction stage,the best base station and the best beam direction in the future are predicted by using the time memory characteristics of LSTM.The simulation results show that the proposed algorithm can achieve accurate beam prediction.