Research On Energy Efficiency Optimization Algorithm For Massive MIMO System

As one of the key technologies of 5G,massive multiple-input multiple-output(Multiple Input Multiple Output,MIMO)technology can effectively improve the spectral efficiency and energy efficiency of the system,and it has received extensive attention and research due to its ability to cope with the high data rates required by users.However,as the use of large-scale antennas leads to a dramatic increase in RF links and generates large energy consumption,How to improve the energy efficiency of the system is the core problem that needs to be solved in large-scale MIMO.Antenna selection and precoding techniques are two important techniques to improve the energy efficiency of large-scale MIMO systems,so they are investigated in this paper to optimize the energy efficiency of large-scale MIMO system.The main research work is as follows:This paper considers the downlink of a single-cell multi-user large-scale MIMO system,By using zero forcing(Zero Forcing,ZF)precoding processing,the impact of the number of transmitting antennas,transmitting power and the optimal transmitting antenna matrix on the energy efficiency of the system is taken account of the perspective of maximizing energy efficiency,and an energy-efficient optimal resource allocation algorithm based on antenna selection under the ZF criterion is proposed.Firstly,the optimal expressions for the number of transmitting antennas and transmitting power of the base station are derived using the Lambert W function,and the optimal transmitting power and number of transmitting antennas are obtained by iterative solution;Secondly,the optimal transmit antenna matrix is found.The main idea of this method is to aim to maximizing system energy efficiency,It uses a low-complexity antenna selection strategy,and selects the final transmitting antenna matrix using convex optimization,The purpose of the algorithm is to reduce the computational complexity of the system and improve the energy efficiency of the system;Finally,the number of transmitting antennas,transmitting power and transmitting antenna matrix of the base station are jointly adjusted to optimise the energy efficiency of the system.The simulation results show that the proposed algorithm can effectively reduce the computational complexity and improve the system energy efficiency and capacity.Although ZF precoding scheme can eliminate inter user interference to some extent,it also leads to weighted amplification of additive noise.Therefore,in order to improve the system performance,this paper proposes a signal to leakage and noise radio(Signal to Leakage and Noise Radio,SLNR)precoding algorithm combined with antenna selection to optimize the system energy efficiency.Firstly,it is shown that the system performance of the SLNR precoding scheme is better than that of the ZF precoding scheme;secondly,the optimal transmit antenna matrix is obtained by using the improved antenna selection algorithm.The main idea of the method is to maximize the user’s received power and maximize the system capacity as the optimization objectives,and uses convex optimization to select the best transmit antenna matrix;then,based on the criterion of maximizing SLNR,the optimal user precoding matrix is obtained;finally,the system energy efficiency is optimized by jointly adjusting the transmit antenna matrix and the precoding matrix.The simulation results show that the proposed joint algorithm significantly improves the system energy efficiency and capacity.