Research On Energy Efficiency Optimization Algorithm For Massive MIMO System

With the rapid development of wireless communication,the power consumption of the communication system is rapidly increasing,and the emission of carbon dioxide and other greenhouse gases is also gradually increasing.In order to meet the needs of green communication,the energy efficiency research of the system has become one of the hot issues in 5G communication research.As one of the key technologies of 5G,massive MIMO technology has a large number of antennas at the base station,thereby significantly increasing the capacity of the communication system.However,as the number of antennas increases,the total energy consumed by the system also increases,resulting in a reduction in the total energy efficiency of the system.Therefore,the research on the energy efficiency of massive MIMO systems has become an important research content in the field of wireless communication.This thesis considers the single-cell multi-user massive MIMO uplink communication system,and studies the resource allocation scheme with the goal of maximizing energy efficiency.The main research contents are as follows:An energy-efficient resource allocation scheme is proposed in this thesis,considering the impact of the number of base station antennas and user transmit power on the energy efficiency performance.A mathematical formulation of optimization issue is provided with the objective of maximizing system energy efficiency under the minimum data rate requirement of user and the endurance of the user terminal,meanwhile the base station uses zero-forcing precoding.First,it is proved that energy efficiency is a convex function of the user's transmit power,a closed-form expression using the Lambert W function is proposed to obtain the user's optimal transmit power.An iterative algorithm is proposed to solve the optimal number of base station transmitting antennas.Th en the properties of the quadratic transformation and an iterative optimization algorithm are used to maximize the energy efficiency.Specifically,both the number of antennas and the user's transmit power are adjusted.Simulation results show that compared with the existing algorithm,the energy efficiency of the algorithm is increased by 5.2%,and the spectrum efficiency is increased by 6.05%.An resource allocation algorithm is proposed based on optimal energy efficiency in this thesis,under the condition that the channel state information of the system is unknown.Since most of the existing energy efficiency studies assume that the base station has known channel state information,it is difficult to obtain accurate channel state information in an actual communication system.A mathematical formulation of optimization issue is provided with the objective of maximizing system energy efficiency under user service quality and channel estimation error requirements,meanwhile the case of using pilot signal estimation to obtain channel state information,the pilot sequence length,data power and pilot power are adjusted synchronously.By transforming the originally fractional optimization problem into an equivalent subtractive form using the properties of the fractional planning,then the block coordinate descent algorithm is adopted to alternately optimize the energy efficiency function by adjusting the data power and pilot power jointly.The simulation results show that compared with the existing algorithm,the energy efficiency of the algorithm is increased by 5.31%,and the spectral efficiency is increased by 5.34%.