Research On Energy Efficiency Optimization In Massive MIMO System

Since its inception,massive multiple-input multiple-output(Massive MIMO)technology is widely used in scenarios with high network demand due to its diversity gain and spatial gain characteristics.With technological changes,the number of communication devices has grown rapidly,and the number of antennas integrated in the base station has also increased,which has led to huge power consumption of the entire system.Therefore,how to reduce system power consumption and develop green communication has become a hot research topic today.In this context,this paper studies the energy efficiency optimization schemes of massive MIMO systems:In view of the high power consumption caused by the high-precision analog-to-digital converter(ADC)and the low system capacity caused by a single low-precision ADC,a millimeter-wave massive MIMO system with a hybrid ADC structure is considered.First,the approximate expression of the energy efficiency of the system is derived based on the random matrix theory.Then,the energy efficiency optimization problem is established under the conditions of satisfying the user's basic data transmission rate and power constraints.Then,the target problem is decomposed into two suboptimization problems of power control and precision selection,and the problem is equivalently converted.Finally,the Dinkebach method and the iterative algorithm of dynamically updating interference are used to realize the power distribution,and the dimensionality reduction update lowcomplexity algorithm is used to complete the accuracy selection of the ADC.The simulation results show that the proposed energy efficiency optimization algorithm can achieve the convergence of transmit power and ADC quantization accuracy with a relatively small number of iterations;by comparing with a single-precision ADC,it is verified that the structure of a mixed-precision ADC only sacrifices a small part of the frequency efficiency in exchange for a substantial increase in energy efficiency;comparisons with static interference algorithms,dynamic interference algorithms,and coordinated update algorithms have verified that the proposed algorithm can guarantee higher spectrum efficiency and achieve optimal energy efficiency.Aiming at the scenario where the receiver passively adapts to the channel in the massive MIMO system,a low-precision massive MIMO system based on the assistance of intelligent reflecting surface(IRS)is considered.First,the additive quantization noise model(AQNM)is used to analyze the quantization of the signal to obtain the signal-to-noise ratio at the receiving end.Then the phase shift matrix of IRS is designed with the goal of maximizing the signal-to-noise ratio at the receiving end.Then,the highest transmission power and the lowest transmission rate are used as constraints,and an optimization problem with the goal of maximizing energy efficiency is established.The nonconvex problem is converted into a convex problem by using the properties of fractional programming,and the constrained problem is converted into an unconstrained problem by using the Lagrange multiplier method.Finally,an iterative algorithm for jointly optimizing ADC quantization accuracy and user transmit power is proposed.Simulations show that the power consumption of the millimeter-wave massive MIMO system based on IRS-assisted low-precision ADC structure is significantly reduced,and the spectrum efficiency of the proposed algorithm is slightly lower than that of high precision ADC,but the energy efficiency is significantly better than the energy efficiency of the comparative literature.