Research On Key Technologies For Ultra-Large Scale Array Beam Alignment And Tracking In High-Dynamic Scenes

With the continuous development of technology,UAV technology has been widely used in military,civilian,and commercial fields.However,UAV communication mostly operates in dynamic scenarios.Therefore,in order to improve the communication quality of UAVs in the millimeter-wave band,it is necessary to perform beam alignment and tracking.This paper focuses on the key technologies of beam alignment and tracking for ultralarge-scale MIMO in high dynamic scenarios.For beam alignment,the optimal codebook,Riemann codebook,is studied,and a new adaptive misalignment correction search(AMCS)is proposed to perform beam alignment using the Riemann codebook.In addition,the paper combines the AMCS algorithm with the and difference angle method to determine the initial estimate angle required for non-linear Kalman filtering to perform beam tracking on high dynamic unmanned aerial vehicles.The paper first introduces MIMO and its development history,and studies the hybrid beamforming system in LOS-MIMO scenarios.The paper also introduces the forms of uniform linear arrays and uniform planar arrays,and derives the steering vector and the commonly used codebooks in simulated beamforming systems,including the IEEE802.15.3c codebook,the N-phase codebook,and the DFT codebook,and draws the beam direction diagram.Next,the paper studies the commonly used beam search methods in beam alignment,including exhaustive search and layered search.By comparing the performance of the generated beam direction diagram of the same number of antennas and beams using the zero-forcing codebook,the genetic codebook,and the Riemann codebook,and conducting two searches under AWGN and LOS channels,the paper proposes a new improved beam search method,the AMCS algorithm,which addresses the inter-beam interference caused by adjacent beams.The AMCS algorithm preliminarily searches all possible directions to select the most favorable direction and corrects the search by transferring the beam to improve the beamforming gain.Finally,the paper studies the problems encountered in high dynamic unmanned aerial vehicle scenarios and proposes the and difference angle method and the specific implementation of the extended Kalman filter for complexity optimization.The paper combines the AMCS algorithm with the and difference angle method as the initial estimator to initialize the extended Kalman filter,and analyzes its performance and feasibility in various scenarios.