Research On Key Technologies Of MIMO-NOMA System

As the fifth-generation mobile communication system for 2020 and the future,higher requirements are placed on system capacity and spectrum utilization.Non-Orthogonal Multiple Access(NOMA)technology further enhances system capacity and spectrum efficiency by introducing new dimensions.Multiple Input Multiple Output(MIMO)technology leverages space resources to increase system capacity and spectrum utilization without increasing bandwidth.This thesis studies several key technologies combining NOMA with MIMO technology.The main work of this thesis is as follows:Firstly,for the beamforming problem of MIMO-NOMA system,an improved algorithm based on zero-forcing beamforming(ZFBF)is proposed.The algorithm calculates the beamforming vector of the cluster through the equivalent cluster channel matrix,and introduces the decoding scale weighting factor,multiplies the user received signal before decoding to increase the required signal strength while reducing inter-cluster interference,improving the performance of the algorithm..Secondly,for the user clustering problem of MIMO-NOMA system,this thesis designs an improved multi-user clustering algorithm based on the difference of channel gain and user correlation.The algorithm sorts the user channel gains in descending order and sets the correlation threshold to ensure a certain channel gain interval and correlation between the users of the same cluster.The appropriate values of the correlation threshold are given by simulation,and the performance advantages of the proposed algorithm compared with the traditional user clustering algorithm are verified.Thirdly,for the power allocation problem of MIMO-NOMA system based on capacity maximization,a step-optimized power allocation algorithm is proposed.The algorithm divides the power allocation problem into two sub-problems: inter-cluster power allocation and intra-cluster superimposed user allocation.The water-filling principle and binary search are used to complete the power allocation between the cluster and the intra-cluster superimposed users,which effectively improves the system capacity.The simulation results show that the performance of the inter-cluster water-filling algorithm and the intra-cluster binary search algorithm is better than the EPA and FTPA algorithms,and the system capacity of the inter-cluster and intra-cluster algorithm is close to the full-space search algorithm.