Beam Management And Optimization Of Large-scale Multiple Antennas For High-frequency Networking

With the explosive growth of mobile data services and the number of terminals,higher requirements have been placed on the system capacity and spectrum efficiency of the Fifth Generation(5G)mobile communication network.Millimeter Wave(mmWave)technology,Massive Multiple-Input Multiple-Output(Massive MIMO)and multiple transmission and reception point(multi-TRP)technologies have emerged as key 5G technologies.Millimeter wave has abundant spectrum resources and attracts much attention in recent years.But its wavelength is short and the path loss is serious,so it does not have advantages in signal transmission.Combined with Massive MIMO technology,it can be configured with large-scale antennas to form shaped beams with better directivity,thereby obtaining high gain and making up for the path loss.Traditional beamforming technology in mm Wave system has the problems of complex training process and high signaling overhead.At the same time,cell densification will cause more serious intra-cell and inter-cell interference.Furthermore,due to the narrow beam of mm Wave,user movement or occlusion of obstacles object will cause beam misalignment between the transmitter and receiver,which will result in beam failure.In response to the above problems,this thesis focuses on beam management and optimization of large-scale multiple antennas for high-frequency networking represented by mmWave.The main contributions and innovation points are as follows:To solve the problem of large signaling overhead caused by beam tracking when users are moving at high speed in mmWave system,a frame structure with dynamic bundled timeslot and variable bandwidth configuration are proposed to reduce the impact of high speed movement on beam tracking and signaling overhead.Based on the frame structure,combining the position and speed prediction,feedback throughput of the bundled timeslots,the reinforcement learning theory is applied to give parameterized optimization strategies of beam width and the number of bundled timeslots.And then an actor-critic enabling mobility-aware adaptive beam tracking algorithm is proposed to maximize the performance of long-term throughput of the system.System-level simulation results show that the adaptive beam tracking algorithm proposed shows obvious advantages in reducing system signaling overhead.And compared with the traditional full scan and Kalman filter based beam tracking algorithms,it can improve the average throughput by 11.34%and 24.86%respectively.To solve the nonuniform difference in the beam number between base stations and the complexity of interference in mm Wave multiple base stations networking scenario,a joint optimization algorithm of beam selection and power allocation based on Lagrange duality under nonuniform beam cardinality is proposed.And the target of the algorithm is to reduce inter-cell and intra-cell interference between beams and maximize the spectrum efficiency.In addition,due to the discrete of beam selection variables and the non-convexity of the objective function,the relaxation method and logarithmic approximation method are used to transform the original problem into a convex optimization problem.Simulation results show that the proposed algorithm has good convergence performance.Compared with the traditional "Max-SINR" and "Max-Directional gain" beam selection algorithms,the proposed algorithm can achieve 10.56% and 11.85% improvement respectively in spectrum efficiency when considering the nonuniform beam cardinality.Currently,there is still a lack of beam failure recovery mechanism in multi-TRP scenario in high frequency networking.Considering the joint transmission characteristics of multi-TRP technology,a Joint Beam Failure Recovery(J-BFR)mechanism is firstly proposed with the goal of increasing system reliability.Then,a Partial Beam Failure Recovery(P-BFR)mechanism is put forward to reduce the number of beam failure transmissions and improve the system throughput.Finally,a beam failure recovery request format is designed for the proposed beam failure recovery mechanisms.The simulation results show that the proposed mechanisms could significantly enhance the capability to support beam failure recovery in multi-TRP cooperative scenario.In the Ultra Reliable and Low Latency Communications(URLLC)scenario,compared with the traditional beam failure recovery mechanism,the throughput of the proposed J-BFR mechanism improves by 7.85%.