Research On Beam Selection And Power Allocation For Millimeter Wave Massive MIMO Systems

Millimeter wave(mm-Wave)massive multiple-input multiple-output(MIMO)technology has been considered as one of the key technologies for future wireless communications,which makes full use of space resources and can significantly improve the spectral efficiency(SE)of the system without increasing the bandwidth.However,with the dramatic increase in the number of antennas at the base station,the power consumption of mm-Wave MIMO systems has become a bottleneck in the development of future wireless communications,and the search for the optimal deployment of energy efficiency(EE)maximization has become the hottest research area today.In this thesis,we study the beam selection and power allocation techniques in the context of Non-Orthogonal Multiple Access(NOMA)from the perspective of reducing the number of Radio frequency(RF)chains used in mm-Wave massive MIMO systems.The main research elements of this thesis are as follows.Firstly,the beam selection and power allocation algorithms in this thesis need to be performed in beam space,so this thesis applies Three-Dimensional(3D)lens antenna array to transform the traditional space into beam space,and in order to improve the SE of the system,NOMA technique is introduced in this thesis,so that one beam can serve multiple users at the same time.Secondly,the power allocation algorithm is an effective means to improve the system SE and EE,but the current power allocation algorithm does not consider the problem of excessive system power consumption caused by the excessive number of RF chains used.Therefore,before studying the power allocation algorithm,this thesis delves into the interference-aware(IA)beam selection algorithm,which reduces the number of RF chains used by selecting a small number of beams with the strongest amplitude to serve the users.However,the IA beam selection algorithm has the problem of poor SE for non-interfering users,which can lead to poor EE of the system as a whole.The improved algorithm is called Improved Interference aware beam selection algorithm in this thesis.The improved algorithm uses the maximum magnitude principle to select the appropriate beam,solves the inter-user interference problem existing in it by user grouping,and then uses the incremental/decremental algorithm to select the optimal beam for both interfering and non-interfering users,ensuring that the system SE is close to the condition of a fully digital system and the EE of the system is substantially improved.Finally,based on the beam selection algorithm,this thesis proposes the power allocation iteration(PAI)algorithm,which effectively improves the EE of the system by solving intra-beam interference and inter-beam interference for the beams selected by the beam selection algorithm,which is mathematically reflected as solving a non-convex optimization problem.Simulation results show that the improved IA beam selection algorithm in this thesis makes a significant improvement in both the SE and EE of the system by solving the inter-user interference problem.Moreover,the proposed PAI algorithm in this thesis makes the EE performance of the system further improved by solving intra-beam and inter-beam interference.